From c0f8197157dfa609d97bfc5e2ea0d66527f29d99 Mon Sep 17 00:00:00 2001 From: Pranav Sharma Date: Tue, 15 Aug 2023 16:04:34 -0700 Subject: [PATCH 01/12] Add README to Nuget and fix license file name (#17170) ### Description Add README to Nuget and fix license file name ### Motivation and Context Fixes https://github.com/microsoft/onnxruntime/issues/17055 --- tools/nuget/generate_nuspec_for_native_nuget.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/tools/nuget/generate_nuspec_for_native_nuget.py b/tools/nuget/generate_nuspec_for_native_nuget.py index e6d47597697d6..706adca6febde 100644 --- a/tools/nuget/generate_nuspec_for_native_nuget.py +++ b/tools/nuget/generate_nuspec_for_native_nuget.py @@ -1097,8 +1097,11 @@ def generate_files(line_list, args): "' ) + # README + files_list.append("') + # Process License, ThirdPartyNotices, Privacy - files_list.append("') + files_list.append("') files_list.append( " Date: Wed, 16 Aug 2023 08:52:09 +0800 Subject: [PATCH 02/12] [WebNN EP] Support BatchNormalization op (#17071) Adds support for BatchNormalization via WebNN meanVarianceNormalization. --- .../core/providers/webnn/builders/helper.h | 1 + .../builders/impl/normalization_op_builder.cc | 118 +++++++++++------- .../webnn/builders/op_builder_factory.cc | 1 + 3 files changed, 72 insertions(+), 48 deletions(-) diff --git a/onnxruntime/core/providers/webnn/builders/helper.h b/onnxruntime/core/providers/webnn/builders/helper.h index e507d321294d6..cdad9b22a8ab8 100644 --- a/onnxruntime/core/providers/webnn/builders/helper.h +++ b/onnxruntime/core/providers/webnn/builders/helper.h @@ -134,6 +134,7 @@ static const InlinedHashMap op_map = { {"ArgMax", "argMax"}, {"ArgMin", "argMin"}, {"AveragePool", "averagePool2d"}, + {"BatchNormalization", "meanVarianceNormalization"}, {"Cast", "cast"}, {"Ceil", "ceil"}, {"Clip", "clamp"}, diff --git a/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc index 76aa892bf36ed..756a838cc0c3e 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc @@ -34,7 +34,7 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder const logging::Logger& logger) const { const auto& op_type = node.OpType(); const auto& input_defs = node.InputDefs(); - ORT_RETURN_IF_NOT(input_defs.size() >= 2, "Layer/Instance/GroupNormalization requires at least two inputs."); + ORT_RETURN_IF_NOT(input_defs.size() >= 2, op_type, " requires at least two inputs."); emscripten::val input = model_builder.GetOperand(input_defs[0]->Name()); std::vector input_shape; @@ -46,10 +46,27 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder std::vector scale_shape; ORT_RETURN_IF_NOT(GetShape(*input_defs[1], scale_shape, logger), "Cannot get scale shape"); const auto scale_size = scale_shape.size(); - ORT_RETURN_IF_NOT(scale_size >= 1 && scale_size <= rank, "The scale size should be less than or equal to input size."); + // Except LayerNormalization, other normalization ops' scale input should be 1-D. + if (op_type == "LayerNormalization") { + ORT_RETURN_IF_NOT(scale_size >= 1 && scale_size <= rank, + "The scale size should be less than or equal to input size."); + } else { + ORT_RETURN_IF_NOT(scale_size == 1, "The scale size should be one."); + } + + if (input_defs.size() >= 3 && !input_defs[2]->Name().empty()) { + // Bias input exists, and bias's shape should be the same as scale's shape. + std::vector bias_shape; + ORT_RETURN_IF_NOT(GetShape(*input_defs[2], bias_shape, logger), "Cannot get bias shape"); + ORT_RETURN_IF_NOT(bias_shape == scale_shape, "The bias' shape should be equal to scale's shape."); + } + std::vector new_scale_shape; if (scale_size < rank) { - if (op_type == "LayerNormalization") { + if (op_type == "BatchNormalization") { + scale_shape.insert(scale_shape.begin(), 1); + scale_shape.insert(scale_shape.end(), rank - 2, 1); + } else if (op_type == "LayerNormalization") { // Align right with leading ones. scale_shape.insert(scale_shape.begin(), rank - scale_size, 1); } else if (op_type == "InstanceNormalization") { @@ -66,48 +83,25 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "Unsupported normalization op: ", op_type); } - std::vector new_scale_shape; std::transform(scale_shape.cbegin(), scale_shape.cend(), std::back_inserter(new_scale_shape), - [](int64_t dim) -> int32_t { return SafeInt(dim); }); + [](int64_t dim) -> uint32_t { return SafeInt(dim); }); emscripten::val reshape_scale = model_builder.GetOperand(input_defs[1]->Name()); emscripten::val reshape_output_scale = model_builder.GetBuilder().call("reshape", reshape_scale, emscripten::val::array(new_scale_shape)); options.set("scale", reshape_output_scale); - } else { - options.set("scale", model_builder.GetOperand(input_defs[1]->Name())); - } - if (input_defs.size() == 3) { - // Inputs contain optional bias - std::vector bias_shape; - ORT_RETURN_IF_NOT(GetShape(*input_defs[2], bias_shape, logger), "Cannot get bias shape"); - const auto bias_size = bias_shape.size(); - ORT_RETURN_IF_NOT(bias_size >= 1 && bias_size <= rank, "The bias size should be less than or equal to input size."); - - // Enlarge new shape to input.rank. - if (bias_size < rank) { - if (op_type == "LayerNormalization") { - bias_shape.insert(bias_shape.begin(), rank - bias_size, 1); - } else if (op_type == "InstanceNormalization") { - bias_shape.insert(bias_shape.begin(), 1); - bias_shape.insert(bias_shape.end(), rank - bias_size - 1, 1); - } else if (op_type == "GroupNormalization") { - bias_shape.insert(bias_shape.begin(), 1); - bias_shape.insert(bias_shape.end(), 1); - } else { - return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "Unsupported normalization op: ", op_type); - } - - std::vector new_bias_shape; - std::transform(bias_shape.cbegin(), bias_shape.cend(), - std::back_inserter(new_bias_shape), - [](int64_t dim) -> int32_t { return SafeInt(dim); }); + if (input_defs.size() >= 3 && !input_defs[2]->Name().empty()) { + // Bias input exists, and bias's shape is the same as scale's shape. emscripten::val reshape_bias = model_builder.GetOperand(input_defs[2]->Name()); emscripten::val reshape_output_bias = - model_builder.GetBuilder().call("reshape", reshape_bias, emscripten::val::array(new_bias_shape)); + model_builder.GetBuilder().call("reshape", reshape_bias, emscripten::val::array(new_scale_shape)); options.set("bias", reshape_output_bias); - } else { + } + } else { + options.set("scale", model_builder.GetOperand(input_defs[1]->Name())); + if (input_defs.size() >= 3 && !input_defs[2]->Name().empty()) { + // Bias input exists, and bias's shape is the same as scale's shape. options.set("bias", model_builder.GetOperand(input_defs[2]->Name())); } } @@ -116,16 +110,35 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder options.set("epsilon", helper.Get("epsilon", 1e-05f)); emscripten::val output = emscripten::val::undefined(); - if (op_type == "LayerNormalization") { + if (op_type == "BatchNormalization") { + ORT_RETURN_IF_NOT(input_defs.size() == 5, "BatchNormalization requires five inputs."); + emscripten::val mean = model_builder.GetOperand(input_defs[3]->Name()); + emscripten::val variance = model_builder.GetOperand(input_defs[4]->Name()); + // Enlarge 1-D mean and variance to new scale shape. + emscripten::val reshape_mean = + model_builder.GetBuilder().call("reshape", mean, emscripten::val::array(new_scale_shape)); + emscripten::val reshape_variance = + model_builder.GetBuilder().call("reshape", variance, emscripten::val::array(new_scale_shape)); + + std::vector axes = {0}; + for (uint32_t i = 2; i < rank; i++) { + axes.push_back(i); + } + + options.set("axes", emscripten::val::array(axes)); + options.set("mean", reshape_mean); + options.set("variance", reshape_variance); + output = model_builder.GetBuilder().call("meanVarianceNormalization", input, options); + } else if (op_type == "LayerNormalization") { int64_t axis = helper.Get("axis", -1); axis = HandleNegativeAxis(axis, rank); - std::vector axes(rank - narrow(axis)); + std::vector axes(rank - SafeInt(axis)); std::iota(axes.begin(), axes.end(), axis); options.set("axes", emscripten::val::array(axes)); output = model_builder.GetBuilder().call("meanVarianceNormalization", input, options); } else if (op_type == "InstanceNormalization") { - std::vector axes; - for (size_t i = 2; i < rank; i++) { + std::vector axes; + for (uint32_t i = 2; i < rank; i++) { axes.emplace_back(i); } options.set("axes", emscripten::val::array(axes)); @@ -133,21 +146,21 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder } else if (op_type == "GroupNormalization") { ORT_RETURN_IF_NOT(helper.HasAttr("num_groups"), "GroupNormalization num_group must be provided."); int32_t group_count = helper.Get("num_groups", -1); - std::vector orig_shape, new_shape; + std::vector orig_shape, new_shape; std::transform(input_shape.cbegin(), input_shape.cend(), std::back_inserter(orig_shape), - [](int64_t dim) -> int32_t { return SafeInt(dim); }); + [](int64_t dim) -> uint32_t { return SafeInt(dim); }); // Add N and Group. ORT_RETURN_IF_NOT(rank >= 2, "Input for GroupNormalization cannot be a scalar or 1D"); - new_shape.emplace_back(SafeInt(input_shape[0])); - new_shape.emplace_back(SafeInt(group_count)); + new_shape.emplace_back(SafeInt(input_shape[0])); + new_shape.emplace_back(SafeInt(group_count)); ORT_RETURN_IF_NOT(group_count > 0 && input_shape[1] % group_count == 0, "GroupNormalization num_group must be divisible by group."); - new_shape.emplace_back(SafeInt(std::reduce(input_shape.begin() + 2, input_shape.end(), - input_shape[1] / group_count, std::multiplies()))); + new_shape.emplace_back(SafeInt(std::reduce(input_shape.begin() + 2, input_shape.end(), + input_shape[1] / group_count, std::multiplies()))); // Input will be reshaped to (N, group count, channels per group x D1 x D2 ... Dn) and recovered after normalization. - options.set("axes", emscripten::val::array(std::vector{2})); + options.set("axes", emscripten::val::array(std::vector{2})); output = model_builder.GetBuilder().call("reshape", input, emscripten::val::array(new_shape)); output = model_builder.GetBuilder().call("meanVarianceNormalization", output, options); output = model_builder.GetBuilder().call("reshape", output, emscripten::val::array(orig_shape)); @@ -166,8 +179,11 @@ bool NormalizationOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initi const WebnnDeviceType /* device_type */, const logging::Logger& logger) const { const auto& input_defs = node.InputDefs(); + const auto& op_type = node.OpType(); + NodeAttrHelper helper(node); + if (input_defs.size() < 2) { - LOGS(logger, VERBOSE) << "LayerNormalization requires at least two inputs."; + LOGS(logger, VERBOSE) << op_type << " requires at least two inputs."; return false; } @@ -179,7 +195,12 @@ bool NormalizationOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initi const auto& output_defs = node.OutputDefs(); if (output_defs.size() != 1) { - LOGS(logger, VERBOSE) << node.OpType() << " output count must be one."; + LOGS(logger, VERBOSE) << op_type << " output count must be one."; + return false; + } + + if (op_type == "BatchNormalization" && helper.Get("training_mode", 0)) { + LOGS(logger, VERBOSE) << "BatchNormalization with training_mode set to true is not supported."; return false; } @@ -192,6 +213,7 @@ void CreateNormalizationOpBuilder(const std::string& op_type, OpBuilderRegistrat constexpr static std::string_view op_types[] = { + "BatchNormalization", "GroupNormalization", "InstanceNormalization", "LayerNormalization", diff --git a/onnxruntime/core/providers/webnn/builders/op_builder_factory.cc b/onnxruntime/core/providers/webnn/builders/op_builder_factory.cc index 5d1761a732954..65dc8ddbeaf90 100644 --- a/onnxruntime/core/providers/webnn/builders/op_builder_factory.cc +++ b/onnxruntime/core/providers/webnn/builders/op_builder_factory.cc @@ -108,6 +108,7 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() { } { // Normalization + CreateNormalizationOpBuilder("BatchNormalization", op_registrations); CreateNormalizationOpBuilder("GroupNormalization", op_registrations); CreateNormalizationOpBuilder("InstanceNormalization", op_registrations); CreateNormalizationOpBuilder("LayerNormalization", op_registrations); From 3cdf42548fcccaee05ce5a5e0f9ee563105c8665 Mon Sep 17 00:00:00 2001 From: shaahji <96227573+shaahji@users.noreply.github.com> Date: Tue, 15 Aug 2023 18:38:14 -0700 Subject: [PATCH 03/12] Issue #17098: Shape inferencing fails during quantization for large models (#17100) --- .../python/tools/quantization/shape_inference.py | 12 +++++++++++- 1 file changed, 11 insertions(+), 1 deletion(-) diff --git a/onnxruntime/python/tools/quantization/shape_inference.py b/onnxruntime/python/tools/quantization/shape_inference.py index 4b5cb9b24263e..eff3dc0bcdc35 100644 --- a/onnxruntime/python/tools/quantization/shape_inference.py +++ b/onnxruntime/python/tools/quantization/shape_inference.py @@ -81,7 +81,17 @@ def quant_pre_process( if not skip_symbolic_shape: # Need to save the inferenced model to file so as to run the optimizer input_model_path = str(temp_path / "symbolic_shape_inferred.onnx") - onnx.save(model, input_model_path) + if save_as_external_data: + onnx.save_model( + model, + input_model_path, + save_as_external_data=True, + all_tensors_to_one_file=all_tensors_to_one_file, + size_threshold=external_data_size_threshold, + convert_attribute=False, + ) + else: + onnx.save(model, input_model_path) model = None opt_model_path = str(temp_path / "optimized.onnx") From ccf14e891e91900c9336b3444c4618f655d4fffd Mon Sep 17 00:00:00 2001 From: Arthur Islamov Date: Wed, 16 Aug 2023 05:58:05 +0400 Subject: [PATCH 04/12] [js/web] JSEP node assignment optimization (#17128) ### Description Since WebGPU supports only float32 and int32, having Gather, Reshape, Shape, Squeeze and Unsqueeze ops with other data types create additional MemCpy ops and slow down the overall execution as all other OPs with other tensor types will be done on CPU. Before this patch SD Unet had these numbers: Node(s) placed on [CPUExecutionProvider]. Number of nodes: 1141 Node(s) placed on [JsExecutionProvider]. Number of nodes: 4025 memcpy tokens: 2001 After patch: Node(s) placed on [CPUExecutionProvider]. Number of nodes: 1735 Node(s) placed on [JsExecutionProvider]. Number of nodes: 2243 memcpu tokens: 813 It also gives more than 5X performance benefit. From 12sec for one Unet step to 2.2sec on RTX 3090 Ti, so we are almost getting to native performance. UPD: with latest changes from main branch and multi-threading it went down to 1.6sec. Will try re-exporting my model to onnx with maximum optimizations, like using MultiHeadAttention to decrease node count. Maybe after implementing that it can go in less than 1 sec --- js/web/lib/wasm/jsep/webgpu/ops/gather.ts | 2 +- .../core/providers/js/js_data_types.cc | 20 +++++++++++++++++++ onnxruntime/core/providers/js/js_data_types.h | 10 ++++++++++ .../core/providers/js/operators/gather.cc | 17 ++++------------ .../core/providers/js/operators/reshape.cc | 7 ++++--- .../core/providers/js/operators/shape_op.cc | 7 ++++--- .../core/providers/js/operators/squeeze.cc | 7 ++++--- .../core/providers/js/operators/unsqueeze.cc | 7 ++++--- 8 files changed, 51 insertions(+), 26 deletions(-) create mode 100644 onnxruntime/core/providers/js/js_data_types.cc create mode 100644 onnxruntime/core/providers/js/js_data_types.h diff --git a/js/web/lib/wasm/jsep/webgpu/ops/gather.ts b/js/web/lib/wasm/jsep/webgpu/ops/gather.ts index 113bf7c7cc822..a915a4bbd969c 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/gather.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/gather.ts @@ -100,7 +100,7 @@ export const gather = (context: ComputeContext, attributes: GatherAttributes): v const metadata = { name: 'Gather', inputTypes: [GpuDataType.default, GpuDataType.default], - cacheHint: attributes.cacheKey + inputs[0].dataType.toString(10) + inputs[1].dataType.toString(10), + cacheHint: attributes.cacheKey, }; context.compute(createGatherProgramInfo(metadata, context.inputs, attributes)); diff --git a/onnxruntime/core/providers/js/js_data_types.cc b/onnxruntime/core/providers/js/js_data_types.cc new file mode 100644 index 0000000000000..69d5bd4f9de8f --- /dev/null +++ b/onnxruntime/core/providers/js/js_data_types.cc @@ -0,0 +1,20 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "core/providers/cpu/tensor/shape_op.h" + +namespace onnxruntime { +namespace js { + +using SupportedTypes = + TypeList< + float, + int32_t, + uint32_t>; + +const std::vector& JsepSupportedDataTypes() { + static const std::vector supportedDataTypes = BuildKernelDefConstraintsFromTypeList(); + return supportedDataTypes; +} +} // namespace js +} // namespace onnxruntime \ No newline at end of file diff --git a/onnxruntime/core/providers/js/js_data_types.h b/onnxruntime/core/providers/js/js_data_types.h new file mode 100644 index 0000000000000..d6b6ac00401b3 --- /dev/null +++ b/onnxruntime/core/providers/js/js_data_types.h @@ -0,0 +1,10 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "core/framework/data_types.h" + +namespace onnxruntime { +namespace js { +std::vector& JsepSupportedDataTypes(); +} +} // namespace onnxruntime \ No newline at end of file diff --git a/onnxruntime/core/providers/js/operators/gather.cc b/onnxruntime/core/providers/js/operators/gather.cc index ec1ae71243fe8..e9c6f5c79294f 100644 --- a/onnxruntime/core/providers/js/operators/gather.cc +++ b/onnxruntime/core/providers/js/operators/gather.cc @@ -2,21 +2,12 @@ // Licensed under the MIT License. #include "core/providers/js/js_kernel.h" - +#include "core/providers/js/js_data_types.h" #include "gather.h" namespace onnxruntime { namespace js { -using AllSupportedSize = - TypeList< - float, - double, - int64_t, - uint64_t, - int32_t, - uint32_t>; - ONNX_OPERATOR_VERSIONED_KERNEL_EX( Gather, kOnnxDomain, @@ -24,7 +15,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 10, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", BuildKernelDefConstraintsFromTypeList()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("Tind", BuildKernelDefConstraintsFromTypeList>()), Gather); @@ -35,7 +26,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 12, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", BuildKernelDefConstraintsFromTypeList()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("Tind", BuildKernelDefConstraintsFromTypeList>()), Gather); @@ -45,7 +36,7 @@ ONNX_OPERATOR_KERNEL_EX( 13, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", BuildKernelDefConstraintsFromTypeList()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("Tind", BuildKernelDefConstraintsFromTypeList>()), Gather); diff --git a/onnxruntime/core/providers/js/operators/reshape.cc b/onnxruntime/core/providers/js/operators/reshape.cc index d8959c89f3fe7..bd6772649a1ae 100644 --- a/onnxruntime/core/providers/js/operators/reshape.cc +++ b/onnxruntime/core/providers/js/operators/reshape.cc @@ -2,6 +2,7 @@ // Licensed under the MIT License. #include "reshape.h" +#include "core/providers/js/js_data_types.h" namespace onnxruntime { namespace js { @@ -12,7 +13,7 @@ ONNX_OPERATOR_KERNEL_EX( 14, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("shape", DataTypeImpl::GetTensorType()) .Alias(0, 0) .InputMemoryType(OrtMemTypeCPU, 1), @@ -24,7 +25,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 13, 13, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("shape", DataTypeImpl::GetTensorType()) .Alias(0, 0) .InputMemoryType(OrtMemTypeCPU, 1), @@ -36,7 +37,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 5, 12, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("shape", DataTypeImpl::GetTensorType()) .Alias(0, 0) .InputMemoryType(OrtMemTypeCPU, 1), diff --git a/onnxruntime/core/providers/js/operators/shape_op.cc b/onnxruntime/core/providers/js/operators/shape_op.cc index ec0de3c04a11e..733580a469d4c 100644 --- a/onnxruntime/core/providers/js/operators/shape_op.cc +++ b/onnxruntime/core/providers/js/operators/shape_op.cc @@ -2,6 +2,7 @@ // Licensed under the MIT License. #include "core/providers/js/js_kernel.h" +#include "core/providers/js/js_data_types.h" #include "core/providers/cpu/tensor/shape_op.h" namespace onnxruntime { @@ -15,7 +16,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( (*KernelDefBuilder::Create()) // properly force CPU/GPU synch inside the kernel .OutputMemoryType(OrtMemTypeCPU, 0) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("T1", DataTypeImpl::GetTensorType()), Shape); @@ -27,7 +28,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( (*KernelDefBuilder::Create()) // properly force CPU/GPU synch inside the kernel .OutputMemoryType(OrtMemTypeCPU, 0) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("T1", DataTypeImpl::GetTensorType()), Shape); @@ -39,7 +40,7 @@ ONNX_OPERATOR_KERNEL_EX( (*KernelDefBuilder::Create()) // properly force CPU/GPU synch inside the kernel .OutputMemoryType(OrtMemTypeCPU, 0) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("T1", DataTypeImpl::GetTensorType()), Shape); diff --git a/onnxruntime/core/providers/js/operators/squeeze.cc b/onnxruntime/core/providers/js/operators/squeeze.cc index a51fecfd8b6ff..e858ade348cd4 100644 --- a/onnxruntime/core/providers/js/operators/squeeze.cc +++ b/onnxruntime/core/providers/js/operators/squeeze.cc @@ -2,6 +2,7 @@ // Licensed under the MIT License. #include "squeeze.h" +#include "core/providers/js/js_data_types.h" namespace onnxruntime { namespace js { @@ -12,7 +13,7 @@ ONNX_OPERATOR_KERNEL_EX( 13, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("axes", DataTypeImpl::GetTensorType()) .Alias(0, 0) .InputMemoryType(OrtMemTypeCPU, 1), @@ -24,7 +25,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 11, 12, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .Alias(0, 0), Squeeze); @@ -34,7 +35,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 1, 10, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .Alias(0, 0), Squeeze); diff --git a/onnxruntime/core/providers/js/operators/unsqueeze.cc b/onnxruntime/core/providers/js/operators/unsqueeze.cc index c7f90a6727479..1485e800e5e76 100644 --- a/onnxruntime/core/providers/js/operators/unsqueeze.cc +++ b/onnxruntime/core/providers/js/operators/unsqueeze.cc @@ -2,6 +2,7 @@ // Licensed under the MIT License. #include "unsqueeze.h" +#include "core/providers/js/js_data_types.h" namespace onnxruntime { namespace js { @@ -12,7 +13,7 @@ ONNX_OPERATOR_KERNEL_EX( 13, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .TypeConstraint("axes", DataTypeImpl::GetTensorType()) .Alias(0, 0) .InputMemoryType(OrtMemTypeCPU, 1), @@ -24,7 +25,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 11, 12, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .Alias(0, 0), Unsqueeze); @@ -34,7 +35,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX( 1, 10, kJsExecutionProvider, (*KernelDefBuilder::Create()) - .TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes()) + .TypeConstraint("T", JsepSupportedDataTypes()) .Alias(0, 0), Unsqueeze); From 178e5991ac8c03c5764addd3bf04469a4a691d84 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 16 Aug 2023 02:00:38 +0000 Subject: [PATCH 05/12] Bump protobufjs from 6.11.3 to 6.11.4 in /js/node (#17177) --- js/node/package-lock.json | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/js/node/package-lock.json b/js/node/package-lock.json index 48c85aab2ef6b..bd01302262273 100644 --- a/js/node/package-lock.json +++ b/js/node/package-lock.json @@ -690,9 +690,9 @@ } }, "node_modules/protobufjs": { - "version": "6.11.3", - "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.3.tgz", - "integrity": "sha512-xL96WDdCZYdU7Slin569tFX712BxsxslWwAfAhCYjQKGTq7dAU91Lomy6nLLhh/dyGhk/YH4TwTSRxTzhuHyZg==", + "version": "6.11.4", + "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.4.tgz", + "integrity": "sha512-5kQWPaJHi1WoCpjTGszzQ32PG2F4+wRY6BmAT4Vfw56Q2FZ4YZzK20xUYQH4YkfehY1e6QSICrJquM6xXZNcrw==", "dev": true, "hasInstallScript": true, "dependencies": { @@ -1549,9 +1549,9 @@ } }, "protobufjs": { - "version": "6.11.3", - "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.3.tgz", - "integrity": "sha512-xL96WDdCZYdU7Slin569tFX712BxsxslWwAfAhCYjQKGTq7dAU91Lomy6nLLhh/dyGhk/YH4TwTSRxTzhuHyZg==", + "version": "6.11.4", + "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.4.tgz", + "integrity": "sha512-5kQWPaJHi1WoCpjTGszzQ32PG2F4+wRY6BmAT4Vfw56Q2FZ4YZzK20xUYQH4YkfehY1e6QSICrJquM6xXZNcrw==", "dev": true, "requires": { "@protobufjs/aspromise": "^1.1.2", From 2575b9aaa156c7ec4e4e6ca15b405c6fd6ae1b89 Mon Sep 17 00:00:00 2001 From: Justin Chu Date: Tue, 15 Aug 2023 23:30:56 -0400 Subject: [PATCH 06/12] Improve comments in winml/ (#17163) Follow up of #17144. Manually fixed indentation in block comments and replaced all tabs with spaces. --- winml/adapter/winml_adapter_c_api.h | 170 +++++++++--------- .../test/api/LearningModelBindingAPITest.cpp | 39 +--- 2 files changed, 91 insertions(+), 118 deletions(-) diff --git a/winml/adapter/winml_adapter_c_api.h b/winml/adapter/winml_adapter_c_api.h index 3053be59a3a59..6c77664b92c37 100644 --- a/winml/adapter/winml_adapter_c_api.h +++ b/winml/adapter/winml_adapter_c_api.h @@ -7,9 +7,9 @@ #include "winrt/windows.foundation.collections.h" /** - * All APIs exported by winml_adapter_c_api.h are part of the private interface dedicated to supporting the WinML API. - * This contract is subject to change based on the needs of the WinML API and is not intended for direct use by callers - * of the onnxruntime c-api and usage of APIs in this header are *not* supported by the onnxruntime product. + * All APIs exported by winml_adapter_c_api.h are part of the private interface dedicated to supporting the WinML API. + * This contract is subject to change based on the needs of the WinML API and is not intended for direct use by callers + * of the onnxruntime c-api and usage of APIs in this header are *not* supported by the onnxruntime product. */ ORT_RUNTIME_CLASS(Model); @@ -75,18 +75,18 @@ struct OrtThreadPoolOptions { struct WinmlAdapterApi { /** * OverrideSchema - * This api is used to override schema inference functions for a variety of ops across opsets. - * This exists because certain ops were failing to infer schemas and caused performance - * issues for DML as it was forced to create resources during evaluation. - * This can be removed when schema inference functions have been updated. + * This api is used to override schema inference functions for a variety of ops across opsets. + * This exists because certain ops were failing to infer schemas and caused performance + * issues for DML as it was forced to create resources during evaluation. + * This can be removed when schema inference functions have been updated. */ OrtStatus*(ORT_API_CALL* OverrideSchema)() NO_EXCEPTION; /** - * EnvConfigureCustomLoggerAndProfiler - * This api is used to add a custom logger and profiler to the ors environment. - * This exists because existing methods on the c-abi to create the environment only support a custom logger. - * Since WinML hooks the profiler events, we expose the profiler and an associated profiling function. + * EnvConfigureCustomLoggerAndProfiler + * This api is used to add a custom logger and profiler to the ors environment. + * This exists because existing methods on the c-abi to create the environment only support a custom logger. + * Since WinML hooks the profiler events, we expose the profiler and an associated profiling function. */ OrtStatus*(ORT_API_CALL* EnvConfigureCustomLoggerAndProfiler)( _In_ OrtEnv* env, @@ -102,34 +102,34 @@ struct WinmlAdapterApi { /** * CreateModelFromPath - * This api creates an OrtModel based on a specified model path. - * There is no inferencing or evaluation setup performed. Only ONNX load is done to reflect on the model's inputs/outputs and other properties. - * This is used by WinML to support model reflection APIs. + * This api creates an OrtModel based on a specified model path. + * There is no inferencing or evaluation setup performed. Only ONNX load is done to reflect on the model's inputs/outputs and other properties. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* CreateModelFromPath)(_In_ const char* model_path, _In_ size_t size, _Outptr_ OrtModel** out) NO_EXCEPTION; /** * CreateModelFromData - * This api creates an OrtModel from a buffer. - * There is no inferencing or evaluation setup performed. Only ONNX load is done to reflect on the model's inputs/outputs and other properties. - * This is used by WinML to support model reflection APIs. + * This api creates an OrtModel from a buffer. + * There is no inferencing or evaluation setup performed. Only ONNX load is done to reflect on the model's inputs/outputs and other properties. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* CreateModelFromData)(_In_opt_ void* data, _In_ size_t size, _Outptr_ OrtModel** out) NO_EXCEPTION; /** * CloneModel - * This api copies the OrtModel along with its internal proto buffer and cached metadata. - * The OrtSession type expects to own the model proto buffer. - * WinML uses this to yield copies of the model proto held by OrtModel to OrtSession. + * This api copies the OrtModel along with its internal proto buffer and cached metadata. + * The OrtSession type expects to own the model proto buffer. + * WinML uses this to yield copies of the model proto held by OrtModel to OrtSession. */ OrtStatus*(ORT_API_CALL* CloneModel)(_In_ const OrtModel* in, _Outptr_ OrtModel** out)NO_EXCEPTION; /** * ModelGetAuthor - * This api gets the model author from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the model author from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetAuthor)( _In_ const OrtModel* model, _Out_ const char** const author, _Out_ size_t* len @@ -137,23 +137,23 @@ struct WinmlAdapterApi { /** * ModelGetName - * This api gets the model name from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the model name from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetName)(_In_ const OrtModel* model, _Out_ const char** const name, _Out_ size_t* len) NO_EXCEPTION; /** * ModelSetName - * This api set the model name from the OrtModel. - * This is used by the Windows ML Samples Gallery to change the model name for telemetry. + * This api set the model name from the OrtModel. + * This is used by the Windows ML Samples Gallery to change the model name for telemetry. */ OrtStatus*(ORT_API_CALL* ModelSetName)(_In_ const OrtModel* model, _In_ const char* name)NO_EXCEPTION; /** * ModelGetDomain - * This api gets the model domain from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the model domain from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetDomain)( _In_ const OrtModel* model, _Out_ const char** const domain, _Out_ size_t* len @@ -161,8 +161,8 @@ struct WinmlAdapterApi { /** * ModelGetDescription - * This api gets the model description from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the model description from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetDescription)( _In_ const OrtModel* model, _Out_ const char** const description, _Out_ size_t* len @@ -170,29 +170,29 @@ struct WinmlAdapterApi { /** * ModelGetVersion - * This api gets the model version from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the model version from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetVersion)(_In_ const OrtModel* model, _Out_ int64_t* version)NO_EXCEPTION; /** * ModelGetInputCount - * This api gets the number of inputs from the OrtModel. It closely matches the API of a similar name similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the number of inputs from the OrtModel. It closely matches the API of a similar name similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetInputCount)(_In_ const OrtModel* model, _Out_ size_t* count)NO_EXCEPTION; /** * ModelGetOutputCount - * This api gets the number of outputs from the OrtModel. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the number of outputs from the OrtModel. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetOutputCount)(_In_ const OrtModel* model, _Out_ size_t* count)NO_EXCEPTION; /** * ModelGetInputName - * This api gets the input name from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the input name from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetInputName)( _In_ const OrtModel* model, _In_ size_t index, _Out_ const char** input_name, _Out_ size_t* count @@ -200,8 +200,8 @@ struct WinmlAdapterApi { /** * ModelGetOutputName - * This api gets the output name from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the output name from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetOutputName)( _In_ const OrtModel* model, _In_ size_t index, _Out_ const char** output_name, _Out_ size_t* count @@ -209,8 +209,8 @@ struct WinmlAdapterApi { /** * ModelGetInputDescription - * This api gets the input description from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the input description from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetInputDescription)( _In_ const OrtModel* model, _In_ size_t index, _Out_ const char** input_description, _Out_ size_t* count @@ -218,8 +218,8 @@ struct WinmlAdapterApi { /** * ModelGetOutputDescription - * This api gets the output description from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the output description from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetOutputDescription)( _In_ const OrtModel* model, _In_ size_t index, _Out_ const char** output_description, _Out_ size_t* count @@ -227,8 +227,8 @@ struct WinmlAdapterApi { /** * ModelGetInputTypeInfo - * This api gets the input OrtTypeInfo from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the input OrtTypeInfo from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetInputTypeInfo)( _In_ const OrtModel* model, _In_ size_t index, _Outptr_ OrtTypeInfo** type_info @@ -236,8 +236,8 @@ struct WinmlAdapterApi { /** * ModelGetOutputTypeInfo - * This api gets the output OrtTypeInfo from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. - * This is used by WinML to support model reflection APIs. + * This api gets the output OrtTypeInfo from the OrtModel given an index. It closely matches the API of a similar name for retrieving model metadata from OrtSession. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetOutputTypeInfo)( _In_ const OrtModel* model, _In_ size_t index, _Outptr_ OrtTypeInfo** type_info @@ -245,15 +245,15 @@ struct WinmlAdapterApi { /** * ModelGetMetadataCount - * This api gets the number of metadata entries from the OrtModel. - * This is used by WinML to support model reflection APIs. + * This api gets the number of metadata entries from the OrtModel. + * This is used by WinML to support model reflection APIs. */ OrtStatus*(ORT_API_CALL* ModelGetMetadataCount)(_In_ const OrtModel* model, _Out_ size_t* count)NO_EXCEPTION; /** * ModelGetMetadata - * This api gets the model metadata from the OrtModel. - * This is used by WinML to deduce whether model input and output formats are supported by the WinML tensorization code paths. + * This api gets the model metadata from the OrtModel. + * This is used by WinML to deduce whether model input and output formats are supported by the WinML tensorization code paths. */ OrtStatus*(ORT_API_CALL* ModelGetMetadata)( _In_ const OrtModel* model, @@ -266,17 +266,17 @@ struct WinmlAdapterApi { /** * ModelEnsureNoFloat16 - * This api checks whether the model requires float 16 support. - * This is used by WinML to fail gracefully when float 16 support is not available on the device. + * This api checks whether the model requires float 16 support. + * This is used by WinML to fail gracefully when float 16 support is not available on the device. * * Can this API be moved into the EP during session initialization. Currently we do an early fp16 check to avoid initialization when it is not supported. */ OrtStatus*(ORT_API_CALL* ModelEnsureNoFloat16)(_In_ const OrtModel* model)NO_EXCEPTION; /** - * SaveModel - * This api save the model to the fiven file - */ + * SaveModel + * This api save the model to the fiven file + */ OrtStatus*(ORT_API_CALL* SaveModel)(_In_ const OrtModel* in, _In_ const wchar_t* const file_name, _In_ size_t len) NO_EXCEPTION; @@ -284,14 +284,14 @@ struct WinmlAdapterApi { /** * OrtSessionOptionsAppendExecutionProvider_CPU - * This api is used to add the cpu EP to OrtSessionOptions so that WinML Gpu session are configures with CPU fallback. + * This api is used to add the cpu EP to OrtSessionOptions so that WinML Gpu session are configures with CPU fallback. */ OrtStatus*(ORT_API_CALL* OrtSessionOptionsAppendExecutionProvider_CPU)(_In_ OrtSessionOptions* options, int use_arena) NO_EXCEPTION; /** * OrtSessionOptionsAppendExecutionProvider_DML - * This api is used to add the DML EP to OrtSessionOptions. + * This api is used to add the DML EP to OrtSessionOptions. */ OrtStatus*(ORT_API_CALL* OrtSessionOptionsAppendExecutionProvider_DML)( _In_ OrtSessionOptions* options, ID3D12Device* device, ID3D12CommandQueue* queue, bool metacommands_enabled @@ -301,7 +301,7 @@ struct WinmlAdapterApi { /** * CreateSessionWithoutModel - * This api is used to create a Session that is completely uninitialized. While there are other Session creation APIs in the + * This api is used to create a Session that is completely uninitialized. While there are other Session creation APIs in the * c-abi, WinML uses this so that it can perform optimizations prior to loading the model, and initializing. * Moreover, WinML needs a new api to support the OrtModel type, and prevent the parsing model protobufs again on session creation. */ @@ -315,7 +315,7 @@ struct WinmlAdapterApi { /** * SessionGetExecutionProvider - * This api is used to get a handle to an OrtExecutionProvider. + * This api is used to get a handle to an OrtExecutionProvider. * Currently WinML uses this to talk directly to the DML EP and configure settings on it. */ OrtStatus*(ORT_API_CALL* SessionGetExecutionProvider)( @@ -324,14 +324,14 @@ struct WinmlAdapterApi { /** * SessionInitialize - * This api is used to initialize an OrtSession. This is one component of creating a usable OrtSession, and is a part of CreateSession in the c-abi. + * This api is used to initialize an OrtSession. This is one component of creating a usable OrtSession, and is a part of CreateSession in the c-abi. * Currently WinML uses this to finalize session creation, after configuring a variety of properties on the OrtSession. */ OrtStatus*(ORT_API_CALL* SessionInitialize)(_In_ OrtSession* session)NO_EXCEPTION; /** * SessionRegisterGraphTransformers - * This api is used to enable DML specific graph transformations on an OrtSession. + * This api is used to enable DML specific graph transformations on an OrtSession. * * Ideally these transformations should be configured by the contract between the runtime and the EP and not overridden by WinML. */ @@ -339,40 +339,40 @@ struct WinmlAdapterApi { /** * SessionRegisterCustomRegistry - * This api is used to support custom operators as they were shipped in WinML RS5. + * This api is used to support custom operators as they were shipped in WinML RS5. */ OrtStatus*(ORT_API_CALL* SessionRegisterCustomRegistry)(_In_ OrtSession* session, _In_ IMLOperatorRegistry* registry) NO_EXCEPTION; /** * SessionLoadAndPurloinModel - * This api is used to load an OrtModel into an OrtSession. + * This api is used to load an OrtModel into an OrtSession. * - * Don't free the 'out' value as this API will defunct and release the OrtModel internally. + * Don't free the 'out' value as this API will defunct and release the OrtModel internally. */ OrtStatus*(ORT_API_CALL* SessionLoadAndPurloinModel)(_In_ OrtSession* session, _In_ OrtModel* model)NO_EXCEPTION; /** * SessionStartProfiling - * This api is used to start profiling OrtSession. The existing mechanism only allows configuring profiling at session creation. + * This api is used to start profiling OrtSession. The existing mechanism only allows configuring profiling at session creation. * - * WinML uses this to toggle profilling on and off based on if a telemetry providers are being listened to. + * WinML uses this to toggle profilling on and off based on if a telemetry providers are being listened to. */ OrtStatus*(ORT_API_CALL* SessionStartProfiling)(_In_ OrtEnv* env, _In_ OrtSession* session)NO_EXCEPTION; /** * SessionEndProfiling - * This api is used to end profiling OrtSession. The existing mechanism only allows configuring profiling at session creation. + * This api is used to end profiling OrtSession. The existing mechanism only allows configuring profiling at session creation. * - * WinML uses this to toggle profilling on and off based on if a telemetry providers are being listened to. + * WinML uses this to toggle profilling on and off based on if a telemetry providers are being listened to. */ OrtStatus*(ORT_API_CALL* SessionEndProfiling)(_In_ OrtSession* session)NO_EXCEPTION; /** * SessionCopyOneInputAcrossDevices - * This api is used to copy and create an OrtValue input to prepare the input on the correct device. + * This api is used to copy and create an OrtValue input to prepare the input on the correct device. * - * WinML uses this to copy gpu device OrtValues to the CPU and vice-versa. + * WinML uses this to copy gpu device OrtValues to the CPU and vice-versa. */ OrtStatus*(ORT_API_CALL* SessionCopyOneInputAcrossDevices)( _In_ OrtSession* session, @@ -385,7 +385,7 @@ struct WinmlAdapterApi { /** * SessionGetNumberOfIntraOpThreads - * This api returns the number of intra operator threads set on the OrtSession. + * This api returns the number of intra operator threads set on the OrtSession. * * WinML uses this to determine that the correct number of threads was set correctly through OrtSessionOptions. */ @@ -394,7 +394,7 @@ struct WinmlAdapterApi { /** * SessionGetIntrapOpThreadSpinning - * This api returns false if the ort session options config entry "session.intra_op.allow_spinning" is set to "0", and true otherwise + * This api returns false if the ort session options config entry "session.intra_op.allow_spinning" is set to "0", and true otherwise * * WinML uses this to determine that the intra op thread spin policy was set correctly through OrtSessionOptions */ @@ -403,7 +403,7 @@ struct WinmlAdapterApi { /** * SessionGetNamedDimensionsOverrides - * This api returns the named dimension overrides that are specified for this session + * This api returns the named dimension overrides that are specified for this session * * WinML uses this to determine that named dimension overrides were set correctly through OrtSessionOptions. */ @@ -414,7 +414,7 @@ struct WinmlAdapterApi { /** * DmlExecutionProviderFlushContext - * This api is used to flush the DML EP. + * This api is used to flush the DML EP. * * WinML communicates directly with DML to perform this as an optimization. */ @@ -422,7 +422,7 @@ struct WinmlAdapterApi { /** * DmlExecutionProviderReleaseCompletedReferences - * This api is used to release completed references after first run the DML EP. + * This api is used to release completed references after first run the DML EP. * * WinML communicates directly with DML to perform this as an optimization. */ @@ -431,7 +431,7 @@ struct WinmlAdapterApi { /** * DmlCopyTensor - * This api is used copy a tensor allocated by the DML EP Allocator to the CPU. + * This api is used copy a tensor allocated by the DML EP Allocator to the CPU. * * WinML uses this when graphs are evaluated with DML, and their outputs remain on the GPU but need to be copied back to the CPU. */ @@ -440,7 +440,7 @@ struct WinmlAdapterApi { /** * GetProviderMemoryInfo - * This api gets the memory info object associated with an EP. + * This api gets the memory info object associated with an EP. * * WinML uses this to manage caller specified D3D12 inputs/outputs. It uses the memory info here to call DmlCreateGPUAllocationFromD3DResource. */ @@ -449,7 +449,7 @@ struct WinmlAdapterApi { /** * GetProviderAllocator - * This api gets associated allocator used by a provider. + * This api gets associated allocator used by a provider. * * WinML uses this to create tensors, and needs to hold onto the allocator for the duration of the associated value's lifetime. */ @@ -459,7 +459,7 @@ struct WinmlAdapterApi { /** * FreeProviderAllocator - * This api frees an allocator. + * This api frees an allocator. * * WinML uses this to free the associated allocator for an ortvalue when creating tensors. * Internally this derefs a shared_ptr. @@ -468,7 +468,7 @@ struct WinmlAdapterApi { /** * ExecutionProviderSync - * This api syncs the EP. + * This api syncs the EP. * * WinML uses this to sync EP inputs/outputs directly. */ @@ -476,7 +476,7 @@ struct WinmlAdapterApi { /** * CreateCustomRegistry - * This api creates a custom registry that callers can populate with custom ops. + * This api creates a custom registry that callers can populate with custom ops. * * WinML uses this to support custom ops. */ @@ -484,7 +484,7 @@ struct WinmlAdapterApi { /** * ValueGetDeviceId - * This api returns the device id of the OrtValue. + * This api returns the device id of the OrtValue. * * WinML uses this to determine if an OrtValue is created on the needed device. */ @@ -492,7 +492,7 @@ struct WinmlAdapterApi { /** * SessionGetInputRequiredDeviceId - * This api returns the required device id for a model input. + * This api returns the required device id for a model input. * * WinML uses this to determine if an OrtValue is created on the needed device. */ diff --git a/winml/test/api/LearningModelBindingAPITest.cpp b/winml/test/api/LearningModelBindingAPITest.cpp index 0f9847c7f4656..b77421e191020 100644 --- a/winml/test/api/LearningModelBindingAPITest.cpp +++ b/winml/test/api/LearningModelBindingAPITest.cpp @@ -368,8 +368,8 @@ static void VerifyInvalidBindExceptions() { auto ensureWinmlInvalidBinding = std::bind(matchException, std::placeholders::_1, WINML_ERR_INVALID_BINDING); /* - Verify tensor bindings throw correct bind exceptions - */ + Verify tensor bindings throw correct bind exceptions + */ // Bind invalid image as tensorfloat input auto image = FileHelpers::LoadImageFeatureValue(L"227x227.png"); @@ -394,8 +394,8 @@ static void VerifyInvalidBindExceptions() { WINML_EXPECT_THROW_SPECIFIC(binding.Bind(L"X", tensorInvalidShape), winrt::hresult_error, ensureWinmlInvalidBinding); /* - Verify sequence bindings throw correct bind exceptions - */ + Verify sequence bindings throw correct bind exceptions + */ // Bind invalid image as sequence output WINML_EXPECT_THROW_SPECIFIC(binding.Bind(L"Y", image), winrt::hresult_error, ensureWinmlInvalidBinding); @@ -410,35 +410,8 @@ static void VerifyInvalidBindExceptions() { WINML_EXPECT_THROW_SPECIFIC(binding.Bind(L"Y", tensorBoolean), winrt::hresult_error, ensureWinmlInvalidBinding); /* - Verify image bindings throw correct bind exceptions - */ - - // WINML_EXPECT_NO_THROW(LoadModel(L"fns-candy.onnx")); - - // LearningModelSession imageSession(m_model); - // LearningModelBinding imageBinding(imageSession); - - // auto inputName = m_model.InputFeatures().First().Current().Name(); - - // // Bind invalid map as image input - // WINML_EXPECT_THROW_SPECIFIC(imageBinding.Bind(inputName, abiMap), winrt::hresult_error, ensureWinmlInvalidBinding); - - // // Bind invalid sequence as image input - // WINML_EXPECT_THROW_SPECIFIC(imageBinding.Bind(inputName, abiSequence), winrt::hresult_error, ensureWinmlInvalidBinding); - - // // Bind invalid tensor type as image input - // WINML_EXPECT_THROW_SPECIFIC(imageBinding.Bind(inputName, tensorBoolean), winrt::hresult_error, ensureWinmlInvalidBinding); - - // // Bind invalid tensor size as image input - // auto tensorFloat = TensorFloat::Create(std::vector { 1, 1, 100, 100 }); - // WINML_EXPECT_THROW_SPECIFIC(imageBinding.Bind(inputName, tensorFloat), winrt::hresult_error, ensureWinmlInvalidBinding); - - // // Bind invalid tensor shape as image input - // WINML_EXPECT_THROW_SPECIFIC(imageBinding.Bind(inputName, tensorInvalidShape), winrt::hresult_error, ensureWinmlInvalidBinding); - - /* - Verify map bindings throw correct bind exceptions - */ + Verify map bindings throw correct bind exceptions + */ WINML_EXPECT_NO_THROW(APITest::LoadModel(L"dictvectorizer-int64.onnx", learningModel)); LearningModelSession mapSession(learningModel); From 35363dd9a5ebdd0d58ecdca6f4b18229f8ae5d99 Mon Sep 17 00:00:00 2001 From: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Date: Tue, 15 Aug 2023 21:00:23 -0700 Subject: [PATCH 07/12] [js/web] a few optimizations for test runner (#17174) ### Description 1. allows passing session options to operator test (eg. graph optimization level) 2. add a short flag '-x' for '--wasm-number-threads' as it is frequently used. --- js/web/script/test-runner-cli-args.ts | 6 +++--- js/web/test/test-main.ts | 3 ++- js/web/test/test-runner.ts | 5 +++-- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/js/web/script/test-runner-cli-args.ts b/js/web/script/test-runner-cli-args.ts index 3528c8d639fb1..f2f44b795abe0 100644 --- a/js/web/script/test-runner-cli-args.ts +++ b/js/web/script/test-runner-cli-args.ts @@ -66,7 +66,7 @@ Options: *** Backend Options *** - --wasm-number-threads Set the WebAssembly number of threads + -x, --wasm-number-threads Set the WebAssembly number of threads --wasm-init-timeout Set the timeout for WebAssembly backend initialization, in milliseconds --wasm-enable-simd Set whether to enable SIMD --wasm-enable-proxy Set whether to enable proxy worker @@ -264,9 +264,9 @@ function parseWasmOptions(_args: minimist.ParsedArgs): InferenceSession.WebAssem } function parseWasmFlags(args: minimist.ParsedArgs): Env.WebAssemblyFlags { - const numThreads = args['wasm-number-threads']; + const numThreads = args.x || args['wasm-number-threads']; if (typeof numThreads !== 'undefined' && typeof numThreads !== 'number') { - throw new Error('Flag "wasm-number-threads" must be a number value'); + throw new Error('Flag "x"/"wasm-number-threads" must be a number value'); } const initTimeout = args['wasm-init-timeout']; if (typeof initTimeout !== 'undefined' && typeof initTimeout !== 'number') { diff --git a/js/web/test/test-main.ts b/js/web/test/test-main.ts index d19a4a7b0e26c..e614cc8e67e71 100644 --- a/js/web/test/test-main.ts +++ b/js/web/test/test-main.ts @@ -137,7 +137,8 @@ for (const group of ORT_WEB_TEST_CONFIG.op) { let context: ProtoOpTestContext|OpTestContext; before('Initialize Context', async () => { - context = useProtoOpTest ? new ProtoOpTestContext(test) : new OpTestContext(test); + context = useProtoOpTest ? new ProtoOpTestContext(test, ORT_WEB_TEST_CONFIG.options.sessionOptions) : + new OpTestContext(test); await context.init(); if (ORT_WEB_TEST_CONFIG.profile) { if (context instanceof ProtoOpTestContext) { diff --git a/js/web/test/test-runner.ts b/js/web/test/test-runner.ts index 5552a8e299926..916243e3d4c0f 100644 --- a/js/web/test/test-runner.ts +++ b/js/web/test/test-runner.ts @@ -574,7 +574,7 @@ export class ProtoOpTestContext { private readonly loadedData: Uint8Array; // model data, inputs, outputs session: ort.InferenceSession; readonly backendHint: string; - constructor(test: Test.OperatorTest) { + constructor(test: Test.OperatorTest, private readonly sessionOptions: ort.InferenceSession.SessionOptions = {}) { const opsetImport = onnx.OperatorSetIdProto.create(test.opset); const operator = test.operator; const attribute = (test.attributes || []).map(attr => { @@ -714,7 +714,8 @@ export class ProtoOpTestContext { } } async init(): Promise { - this.session = await ort.InferenceSession.create(this.loadedData, {executionProviders: [this.backendHint]}); + this.session = await ort.InferenceSession.create( + this.loadedData, {executionProviders: [this.backendHint], ...this.sessionOptions}); } async dispose(): Promise { From 8289e8b6efab41db766fd22b61f1a1f82c742834 Mon Sep 17 00:00:00 2001 From: Guenther Schmuelling Date: Tue, 15 Aug 2023 21:14:20 -0700 Subject: [PATCH 08/12] [js/webgpu] fix a few shader errors (#17171) Fix for segment anything decoder, reduceMax with rank1 and concat. --- .../lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts | 2 +- js/web/lib/wasm/jsep/webgpu/ops/concat.ts | 2 +- js/web/lib/wasm/jsep/webgpu/ops/reduce.ts | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/js/web/lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts b/js/web/lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts index 34c739ed05e64..1d490aa9028ff 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts @@ -159,7 +159,7 @@ const createConvTranspose2DOpProgramShaderSource = } for (var i: u32 = 0; i < ${workPerThread}; i = i + 1) { - ${output.set('batch', 'r', 'c+i', 'd1', 'dotProd[i]')} + ${output.set('batch', 'r', 'c+i', 'd1', 'dotProd[i]')}; } }`; const codeSnippet = ` diff --git a/js/web/lib/wasm/jsep/webgpu/ops/concat.ts b/js/web/lib/wasm/jsep/webgpu/ops/concat.ts index 54d102b806af4..8b91b64a09200 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/concat.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/concat.ts @@ -118,7 +118,7 @@ const createConcatProgramInfo = ${shaderHelper.mainStart()} ${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)} - let indices = ${output.offsetToIndices('global_idx')}; + var indices = ${output.offsetToIndices('global_idx')}; let inputIndex = calculateInputIndex(${indicesAxis}); if (inputIndex != 0u) { diff --git a/js/web/lib/wasm/jsep/webgpu/ops/reduce.ts b/js/web/lib/wasm/jsep/webgpu/ops/reduce.ts index f9691000743de..b645510d8384b 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/reduce.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/reduce.ts @@ -190,7 +190,7 @@ export const reduceMax = (context: ComputeContext, attributes: ReduceAttributes) const idxZero = []; for (let k = 0; k < input.shape.length; k++) { if (axes.indexOf(k) >= 0 || axes.length === 0) { - idxZero.push(`inputIndices[${k}] = 0;`); // first element + idxZero.push(input.indicesSet('inputIndices', k, 0)); } } From 33ecde9af1cc38634f6431d2f1124502a46e20c9 Mon Sep 17 00:00:00 2001 From: xhcao Date: Wed, 16 Aug 2023 12:18:13 +0800 Subject: [PATCH 09/12] [js/webgpu] Fix reshape int32 test case (#17113) Co-authored-by: Xing Xu Co-authored-by: Xing Xu --- js/web/test/data/ops/reshape.jsonc | 97 +++++++++++++++++++++++++++++- 1 file changed, 96 insertions(+), 1 deletion(-) diff --git a/js/web/test/data/ops/reshape.jsonc b/js/web/test/data/ops/reshape.jsonc index a7639040f1c08..7f16d2691436e 100644 --- a/js/web/test/data/ops/reshape.jsonc +++ b/js/web/test/data/ops/reshape.jsonc @@ -1,6 +1,6 @@ [ { - "name": "Reshape with '0' and '-1' in the shape tensor input", + "name": "Reshape float32 with '0' and '-1' in the shape tensor input", "operator": "Reshape", "attributes": [], "cases": [ @@ -93,5 +93,100 @@ ] } ] + }, + { + "name": "Reshape int32 with '0' and '-1' in the shape tensor input", + "operator": "Reshape", + "attributes": [], + "cases": [ + { + "name": "T[0]", + "inputs": [ + { + "data": [1, 1, 1, 1], + "dims": [2, 2], + "type": "int32" + }, + { + "data": [-1, 0], + "dims": [2], + "type": "int64" + } + ], + "outputs": [ + { + "data": [1, 1, 1, 1], + "dims": [2, 2], + "type": "int32" + } + ] + }, + { + "name": "Scalar to 1D", + "inputs": [ + { + "data": [1], + "dims": [], + "type": "int32" + }, + { + "data": [1], + "dims": [1], + "type": "int64" + } + ], + "outputs": [ + { + "data": [1], + "dims": [1], + "type": "int32" + } + ] + }, + { + "name": "Scalar to 2D", + "inputs": [ + { + "data": [1], + "dims": [], + "type": "int32" + }, + { + "data": [1, 1], + "dims": [2], + "type": "int64" + } + ], + "outputs": [ + { + "data": [1], + "dims": [1, 1], + "type": "int32" + } + ] + }, + { + "name": "Scalar to 2D with -1 in shape hints", + "inputs": [ + { + "data": [1], + "dims": [], + "type": "int32" + }, + { + "data": [-1, 1], + "dims": [2], + "type": "int64" + } + ], + "outputs": [ + { + "data": [1], + "dims": [1, 1], + "type": "int32" + } + ] + } + ] } ] From 6b29837ed28bb550a8f4b09f888225eea446c0f6 Mon Sep 17 00:00:00 2001 From: Tianlei Wu Date: Tue, 15 Aug 2023 21:31:57 -0700 Subject: [PATCH 10/12] Move attention test data to file (#17158) (1) Move attention test data from code to file to avoid prefast crash (which blocks python packaging pipeline) (2) Enable some test cases that previously disabled in Windows (3) Fix an assertion error in `MultiHeadAttentionTest.CrossAttention_WithPastPassedInDirectly_NoMask` This test case is for Whisper cross attention. When Memory efficient attention was enabled, format is converted to BNSH, which trigger assertion error since memory efficient attention asserts BSNH format. Temporarily disable memory efficient attention for this case. I also disabled the test since Whisper does not use it anymore, and ROCm fails in the test. --- .../contrib_ops/cuda/bert/attention_impl.cu | 32 +- .../cuda/bert/multihead_attention.cc | 7 +- .../test/contrib_ops/attention_op_test.cc | 88 +- .../contrib_ops/attention_op_test_helper.cc | 6582 +---------------- .../contrib_ops/attention_op_test_helper.h | 12 +- .../multihead_attention_op_test.cc | 6 +- .../packed_multihead_attention_op_test.cc | 2 - .../attention/attention_test_data.txt | 4996 +++++++++++++ .../packed_multihead_attention_test_data.txt | 362 + .../test/util/include/tensors_from_file.h | 17 + onnxruntime/test/util/tensors_from_file.cc | 107 + 11 files changed, 5739 insertions(+), 6472 deletions(-) create mode 100644 onnxruntime/test/testdata/attention/attention_test_data.txt create mode 100644 onnxruntime/test/testdata/attention/packed_multihead_attention_test_data.txt create mode 100644 onnxruntime/test/util/include/tensors_from_file.h create mode 100644 onnxruntime/test/util/tensors_from_file.cc diff --git a/onnxruntime/contrib_ops/cuda/bert/attention_impl.cu b/onnxruntime/contrib_ops/cuda/bert/attention_impl.cu index 254d3aabb78c8..4d478ef158503 100644 --- a/onnxruntime/contrib_ops/cuda/bert/attention_impl.cu +++ b/onnxruntime/contrib_ops/cuda/bert/attention_impl.cu @@ -336,6 +336,7 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, } // attention with past/present state else if (data.past_key != nullptr || data.present_key != nullptr) { + // Below logic does not support memory efficient attention with past (like pass_past_in_kv) but without bias if (data.bias == nullptr) { // cross attention with past state if (data.past_key != nullptr && data.present_key == nullptr) { @@ -344,7 +345,7 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, assert(data.key == nullptr); assert(data.value == nullptr); ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.query, q)); + max_threads_per_block, false, data.query, q)); } // cross attention with present state or self attention with present state else if (data.past_key == nullptr && data.present_key != nullptr) { @@ -356,13 +357,13 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, // TODO: supporting packed qkv for self attention may benefit performance ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.query, q)); + max_threads_per_block, false, data.query, q)); // TODO: supporting packed kv for cross attention may benefit performance ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.key, data.present_key)); + max_threads_per_block, false, data.key, data.present_key)); ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, v_head_size, num_heads, - max_threads_per_block, false, data.value, data.present_value)); + max_threads_per_block, false, data.value, data.present_value)); } // self attention with past and present state else { @@ -375,11 +376,11 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, assert(data.value != nullptr); // TODO: supporting packed qkv for self attention may benefit performance ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.query, q)); + max_threads_per_block, false, data.query, q)); ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.key, k)); + max_threads_per_block, false, data.key, k)); ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, v_head_size, num_heads, - max_threads_per_block, false, data.value, v)); + max_threads_per_block, false, data.value, v)); } qkv_format = AttentionQkvFormat::Q_K_V_BNSH; } @@ -397,9 +398,9 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, // query => q, temp_k_workspace => k, temp_v_workspace => v LaunchAddBias(stream, max_threads_per_block, - batch_size, sequence_length, kv_sequence_length, - num_heads, qk_head_size, v_head_size, - data.bias, data.query, data.temp_k_workspace, data.temp_v_workspace, q, k, v); + batch_size, sequence_length, kv_sequence_length, + num_heads, qk_head_size, v_head_size, + data.bias, data.query, data.temp_k_workspace, data.temp_v_workspace, q, k, v); DUMP_TENSOR_D("q(BSNH)", q, batch_size * sequence_length, num_heads, qk_head_size); DUMP_TENSOR_D("k(BSNH)", k, batch_size * kv_sequence_length, num_heads, qk_head_size); @@ -419,11 +420,11 @@ Status PrepareQkv(contrib::AttentionParameters& parameters, // temp_k_workspace (BxSxNxH) => present_k (BxNxSxH) ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, qk_head_size, num_heads, - max_threads_per_block, false, data.temp_k_workspace, data.present_key)); + max_threads_per_block, false, data.temp_k_workspace, data.present_key)); // temp_v_workspace (BxSxNxH_v) => present_v (BxNxSxH_v) ORT_RETURN_IF_ERROR(LaunchTransQkv(stream, 1, kv_sequence_length, batch_size, v_head_size, num_heads, - max_threads_per_block, false, data.temp_v_workspace, data.present_value)); + max_threads_per_block, false, data.temp_v_workspace, data.present_value)); DUMP_TENSOR_D("q(BSNH)", q, batch_size * sequence_length, num_heads, qk_head_size); DUMP_TENSOR_D("k(BSNH)", data.temp_k_workspace, batch_size * kv_sequence_length, num_heads, qk_head_size); @@ -688,8 +689,7 @@ Status QkvToContext( if (qkv_format == AttentionQkvFormat::Q_K_V_BNSH) { k = data.present_key; v = data.present_value; - } - else { + } else { assert(qkv_format == AttentionQkvFormat::Q_K_V_BSNH); k = data.temp_k_workspace; v = data.temp_v_workspace; @@ -1111,12 +1111,12 @@ Status DecoderQkvToContext( constexpr int max_sequence_length = 0; ORT_RETURN_IF_ERROR(ComputeSoftmaxWithRawMask(ort_stream, kv_sequence_length, sequence_length, batch_size, num_heads, nullptr, key_padding_mask, add_before_softmax, - false/*broadcast rpb*/, scratch1, scratch2, is_unidirectional, + false /*broadcast rpb*/, scratch1, scratch2, is_unidirectional, 1.0f, mask_dimension, max_sequence_length, false, nullptr, mask_filter_value)); } else { ORT_RETURN_IF_ERROR(ComputeSoftmax(stream, kv_sequence_length, sequence_length, batch_size, num_heads, - add_before_softmax, false/*broadcast rpb*/, scratch1, scratch2, + add_before_softmax, false /*broadcast rpb*/, scratch1, scratch2, is_unidirectional)); } diff --git a/onnxruntime/contrib_ops/cuda/bert/multihead_attention.cc b/onnxruntime/contrib_ops/cuda/bert/multihead_attention.cc index 8bf29b8b2f453..15f0bc1a746d3 100644 --- a/onnxruntime/contrib_ops/cuda/bert/multihead_attention.cc +++ b/onnxruntime/contrib_ops/cuda/bert/multihead_attention.cc @@ -166,17 +166,23 @@ Status MultiHeadAttention::ComputeInternal(OpKernelContext* context) const { } } + const bool pass_key_value_as_past = (parameters.pass_past_in_kv && nullptr != key && nullptr != value); + #if USE_FLASH_ATTENTION bool is_long_sequence = sizeof(T) == 2 || // sequence length threshold is 0 for FP16 parameters.sequence_length >= attention::kMinSequenceLengthForMemoryEfficientAttentionFp32 || parameters.kv_sequence_length >= attention::kMinSequenceLengthForMemoryEfficientAttentionFp32; + // Exclude this case since PrepareQkv will convert the format to BNSH. + bool past_no_bias = (pass_key_value_as_past || past_key != nullptr || present_key != nullptr) && bias == nullptr; + bool is_good_for_rpb = relative_position_bias != nullptr && parameters.sequence_length % (4 * sizeof(T)) == 0; bool use_memory_efficient_attention = fused_runner == nullptr && fused_cross_attention_kernel == nullptr && !disable_memory_efficient_attention_ && is_long_sequence && + !past_no_bias && (relative_position_bias == nullptr || is_good_for_rpb) && (nullptr == key_padding_mask || is_mask_1d_key_seq_len_start) && has_memory_efficient_attention(sm, sizeof(T) == 2); @@ -226,7 +232,6 @@ Status MultiHeadAttention::ComputeInternal(OpKernelContext* context) const { data.mask_index = (nullptr == key_padding_mask) ? nullptr : key_padding_mask->Data(); data.mask_index_dims = (nullptr == key_padding_mask) ? gsl::span() : key_padding_mask->Shape().GetDims(); data.past = nullptr; - const bool pass_key_value_as_past = (parameters.pass_past_in_kv && nullptr != key && nullptr != value); data.past_key = pass_key_value_as_past ? reinterpret_cast(key->Data()) : (nullptr == past_key) ? nullptr : reinterpret_cast(past_key->Data()); diff --git a/onnxruntime/test/contrib_ops/attention_op_test.cc b/onnxruntime/test/contrib_ops/attention_op_test.cc index f17375e9366fd..0e66a22e59b9a 100644 --- a/onnxruntime/test/contrib_ops/attention_op_test.cc +++ b/onnxruntime/test/contrib_ops/attention_op_test.cc @@ -846,30 +846,12 @@ void RawAttentionEmptyPastState(bool past_present_share_buffer) { } } -// Disable Causal_EmptyPastState temporarily in Windows build since prefast crashes in python package pipelines -// TODO(tianleiwu): change the test to load test data from file. -#ifndef _MSC_VER TEST(AttentionTest, Causal_EmptyPastState) { int batch_size = 1; int sequence_length = 2; int hidden_size = 64; int number_of_heads = 2; - std::vector input_data = { - 0.00838f, 0.007523f, -0.00872f, 0.002882f, -0.003567f, 0.000859f, -0.002821f, 0.000563f, 0.007675f, -0.002758f, - 0.000947f, 0.001149f, -0.001534f, 0.0006075f, 0.002853f, 0.004517f, 0.00825f, 0.003687f, -0.002161f, 0.001167f, - 0.005913f, 0.00394f, -0.002136f, 0.00946f, 0.000461f, -0.003593f, -0.002377f, -0.001609f, -0.006363f, 0.0013485f, - -0.006706f, -0.005188f, 0.002165f, 0.006073f, 0.007717f, -0.007675f, 0.000827f, 0.004253f, 0.00697f, -0.0035f, - -0.00301f, 0.006565f, -0.0002068f, -0.004593f, 0.00198f, 0.00107f, -0.003082f, 0.002243f, 0.00983f, 0.00608f, - 0.001682f, 0.001701f, -0.006935f, 0.004765f, -0.002333f, 0.003805f, -0.00905f, 0.00599f, 0.00998f, -0.001602f, - 0.00744f, -0.008514f, 0.005424f, -0.002413f, 0.00862f, 0.00459f, -0.002516f, 0.00283f, -0.00272f, -0.005207f, - -0.00738f, -0.005386f, -0.00951f, 0.008415f, 0.002865f, -0.00726f, 0.00494f, 0.002226f, 0.0000424f, -0.007507f, - 0.002193f, -0.004482f, 0.002386f, 0.005997f, -0.001786f, 0.009f, 0.006435f, -0.0067f, -0.001984f, 0.001514f, - -0.004917f, 0.003468f, -0.0013685f, -0.007122f, 0.00788f, 0.000825f, 0.00621f, -0.00437f, 0.005653f, 0.009674f, - 0.003576f, 0.00956f, 0.0064f, 0.00283f, -0.00797f, 0.00867f, 0.004536f, -0.00985f, 0.004856f, -0.006878f, - 0.006012f, -0.0042f, -0.00328f, -0.00885f, -0.0079f, 0.004917f, -0.00594f, 0.003452f, -0.006355f, -0.003536f, - 0.0022f, 0.003494f, -0.008865f, 0.00461f, -0.00485f, 0.00889f, -0.002272f, 0.00596f}; - std::vector weight_data; std::vector bias_data; GetAttentionWeight(weight_data); @@ -878,74 +860,13 @@ TEST(AttentionTest, Causal_EmptyPastState) { // No mask_index std::vector mask_index_data = {}; - std::vector output_data = { - 0.0027942657f, 0.0067901611f, 0.0070953369f, -0.0020713806f, 0.0055351257f, 0.0030479431f, -0.0060462952f, - -0.0087127686f, 0.0030956268f, -0.00036644936f, 0.0014686584f, -0.0038146973f, 0.0072097778f, -0.0052490234f, - 0.0056114197f, 0.0050926208f, 0.0080947876f, 0.0074501038f, 0.0079498291f, 0.0098876953f, -0.0066146851f, - 0.0064735413f, 0.0093307495f, -0.00051593781f, -0.0047683716f, -0.0069198608f, 0.0094604492f, 0.0066146851f, - -0.0040054321f, 0.0017976761f, -0.0058059692f, -0.0087051392f, 0.0054740906f, 0.0022010803f, 0.0075340271f, - 0.0047035217f, 0.00340271f, 0.0096969604f, -0.0016756058f, 0.0020771027f, -0.0063018799f, 0.0073280334f, - -0.0056381226f, 0.004032135f, -0.0082473755f, 0.0045280457f, 0.0045814514f, -0.0026607513f, -0.0031585693f, - -0.003660202f, -0.0053253174f, -0.0089187622f, -0.0073509216f, 0.0048408508f, 0.0058364868f, 0.0069313049f, - -0.0071868896f, 0.008392334f, -0.0018663406f, -0.0092163086f, -0.00048780441f, -0.0054283142f, -0.0061683655f, - 0.0078048706f, 0.0025291443f, 0.0065917969f, 0.0072250366f, -0.0018520355f, 0.005531311f, 0.003118515f, - -0.0061264038f, -0.0090484619f, 0.003276825f, -0.00047063828f, 0.0015802383f, -0.0037345886f, 0.0069732666f, - -0.0054092407f, 0.0052947998f, 0.004940033f, 0.0085220337f, 0.007194519f, 0.0078659058f, 0.0095214844f, - -0.0065574646f, 0.0064315796f, 0.0093383789f, -0.00058555603f, -0.0046386719f, -0.0067710876f, 0.0096130371f, - 0.0064315796f, -0.0040740967f, 0.0017337799f, -0.0057067871f, -0.008682251f, 0.0054855347f, 0.0019645691f, - 0.0075149536f, 0.0047187805f, 0.0036354065f, 0.0096282959f, -0.0019168854f, 0.0021934509f, -0.0063018799f, - 0.0072937012f, -0.006187439f, 0.0039825439f, -0.0081253052f, 0.0046577454f, 0.0045700073f, -0.0028266907f, - -0.0028438568f, -0.0035438538f, -0.0053100586f, -0.0090332031f, -0.0071105957f, 0.004699707f, 0.0058021545f, - 0.0071411133f, -0.0071678162f, 0.0085449219f, -0.0018749237f, -0.0095825195f, -0.00049686432f, -0.0053634644f, - -0.0057945251f, 0.0078277588f}; + std::vector input_data; + std::vector output_data; + std::vector present_data; + GetCausal_EmptyPastState(input_data, output_data, present_data); std::vector past_data = {}; - std::vector present_data = { - 0.0070152283f, -0.0049858093f, -0.0029277802f, 0.0078277588f, -0.001991272f, -0.0010290146f, -0.0084457397f, - -0.0028400421f, 0.0048294067f, 0.0012731552f, 0.0047149658f, 0.0069084167f, 0.0027809143f, 0.0014457703f, - -0.0010128021f, -0.0011024475f, 8.4400177e-05f, -0.0049972534f, -0.0040206909f, 0.002073288f, -0.0034713745f, - -0.0087203979f, -0.0047302246f, -0.0023326874f, -0.0063209534f, -0.0031681061f, -0.006942749f, 0.0064888f, - 0.0014505386f, -0.0037765503f, 0.0067138672f, -0.0018196106f, - 0.0064506531f, -0.0049514771f, -0.0036487579f, 0.0081558228f, -0.0024414062f, -0.0014820099f, -0.0086212158f, - -0.0025672913f, 0.0047111511f, 0.0011997223f, 0.0042953491f, 0.0067138672f, 0.0028495789f, 0.0015869141f, - -0.00037360191f, -0.0012044907f, 0.00029373169f, -0.005065918f, -0.0038700104f, 0.0014038086f, -0.0030422211f, - -0.0084838867f, -0.004863739f, -0.0028686523f, -0.0063362122f, -0.0034809113f, -0.0075874329f, 0.0066947937f, - 0.0019130707f, -0.0036792755f, 0.0070266724f, -0.0016460419f, - - -0.003238678f, -0.0066452026f, 0.0043983459f, -0.0016002655f, 0.0045623779f, 0.0065002441f, -0.0072174072f, - -0.0050315857f, 0.0087356567f, 0.0061645508f, 0.0069580078f, -0.003320694f, -0.0087814331f, 0.0062255859f, - 0.0035037994f, 0.00064849854f, -0.0018444061f, 0.0043945312f, 0.01008606f, -0.0089874268f, -0.0087585449f, - 0.0020160675f, 0.00207901f, -0.0097732544f, -0.0042991638f, 0.0070266724f, -0.0028743744f, 0.0087051392f, - 0.0099868774f, 0.0076217651f, -0.0027103424f, -0.006439209f, - -0.0033836365f, -0.0063171387f, 0.0043144226f, -0.001707077f, 0.0044555664f, 0.0069885254f, -0.0072593689f, - -0.0050468445f, 0.008895874f, 0.0050582886f, 0.0064926147f, -0.0030384064f, -0.0083618164f, 0.0065307617f, - 0.0038928986f, 0.0005645752f, -0.0024528503f, 0.0043983459f, 0.0099029541f, -0.0088043213f, -0.0081558228f, - 0.0021705627f, 0.0018062592f, -0.0094985962f, -0.0045890808f, 0.0068702698f, -0.002532959f, 0.0081863403f, - 0.009765625f, 0.0077362061f, -0.0026664734f, -0.0060920715f, - - 0.0027942657f, 0.0067901611f, 0.0070953369f, -0.0020713806f, 0.0055351257f, 0.0030479431f, -0.0060462952f, - -0.0087127686f, 0.0030956268f, -0.00036644936f, 0.0014686584f, -0.0038146973f, 0.0072097778f, -0.0052490234f, - 0.0056114197f, 0.0050926208f, 0.0080947876f, 0.0074501038f, 0.0079498291f, 0.0098876953f, -0.0066146851f, - 0.0064735413f, 0.0093307495f, -0.00051593781f, -0.0047683716f, -0.0069198608f, 0.0094604492f, 0.0066146851f, - -0.0040054321f, 0.0017976761f, -0.0058059692f, -0.0087051392f, - 0.0022659302f, 0.0063896179f, 0.0073509216f, -0.0016336441f, 0.0055236816f, 0.0031890869f, -0.0062026978f, - -0.0093917847f, 0.0034580231f, -0.00057506561f, 0.0016918182f, -0.0036563873f, 0.0067405701f, -0.005569458f, - 0.0049743652f, 0.0047874451f, 0.0089492798f, 0.0069389343f, 0.0077819824f, 0.0091552734f, -0.0065002441f, - 0.0063934326f, 0.0093460083f, -0.00065517426f, -0.0045127869f, -0.0066223145f, 0.009765625f, 0.0062484741f, - -0.0041465759f, 0.0016708374f, -0.0056037903f, -0.0086669922f, - - 0.0054740906f, 0.0022010803f, 0.0075340271f, 0.0047035217f, 0.00340271f, 0.0096969604f, -0.0016756058f, - 0.0020771027f, -0.0063018799f, 0.0073280334f, -0.0056381226f, 0.004032135f, -0.0082473755f, 0.0045280457f, - 0.0045814514f, -0.0026607513f, -0.0031585693f, -0.003660202f, -0.0053253174f, -0.0089187622f, -0.0073509216f, - 0.0048408508f, 0.0058364868f, 0.0069313049f, -0.0071868896f, 0.008392334f, -0.0018663406f, -0.0092163086f, - -0.00048780441f, -0.0054283142f, -0.0061683655f, 0.0078048706f, - 0.0054931641f, 0.0017261505f, 0.0074958801f, 0.0047340393f, 0.003868103f, 0.0095596313f, -0.0021572113f, - 0.0023078918f, -0.0063018799f, 0.0072631836f, -0.0067367554f, 0.0039329529f, -0.0080032349f, 0.0047874451f, - 0.0045623779f, -0.0029945374f, -0.0025291443f, -0.0034275055f, -0.0052986145f, -0.0091400146f, -0.0068702698f, - 0.0045623779f, 0.0057678223f, 0.0073547363f, -0.0071487427f, 0.0087051392f, -0.0018835068f, -0.0099411011f, - -0.00050640106f, -0.0052947998f, -0.0054206848f, 0.0078430176f}; - bool is_unidirectional = true; bool use_past_state = true; int past_sequence_length = 0; @@ -987,7 +908,6 @@ TEST(AttentionTest, Causal_EmptyPastState) { use_past_state, past_sequence_length, &past_data, &present_data); } } -#endif TEST(AttentionTest, AttentionEmptyPastState) { RawAttentionEmptyPastState(false); diff --git a/onnxruntime/test/contrib_ops/attention_op_test_helper.cc b/onnxruntime/test/contrib_ops/attention_op_test_helper.cc index f70b7ecaf6863..fcd17e0d4ed71 100644 --- a/onnxruntime/test/contrib_ops/attention_op_test_helper.cc +++ b/onnxruntime/test/contrib_ops/attention_op_test_helper.cc @@ -1,1411 +1,44 @@ // Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. #include -#include "test/contrib_ops/attention_op_test_helper.h" +#include #include "gtest/gtest.h" +#include "core/common/common.h" +#include "test/contrib_ops/attention_op_test_helper.h" +#include "test/util/include/tensors_from_file.h" namespace onnxruntime { namespace test { -// Disable some tests in Windows since prefast build might crash with large test data. -#if !defined(_MSC_VER) +static void LoadTensor(const std::string& name, std::vector& values) { + static std::unordered_map> tensors; + static std::once_flag load_once_flag; + std::call_once(load_once_flag, []() { + const std::string test_data_path("testdata/attention/attention_test_data.txt"); + LoadTensorsFromFile(test_data_path, tensors); + + const std::string packed_mha_test_data_path("testdata/attention/packed_multihead_attention_test_data.txt"); + LoadTensorsFromFile(packed_mha_test_data_path, tensors); + }); + + auto it = tensors.find(name); + if (it == tensors.end()) { + ORT_THROW("Failed to find key:", name); + } + + values = it->second; +} + void GetWeight_64_3_64(std::vector& weight_data) { - weight_data = { - -0.004707f, -0.006775f, 0.0009236f, 0.003067f, -0.00806f, 0.00779f, 0.0004425f, 0.00846f, 0.00048f, - 0.00999f, 0.00115f, 0.00226f, -0.00705f, 0.004467f, 0.001455f, -0.006073f, 0.00465f, -0.00861f, - -0.002779f, 0.00883f, -0.002996f, 0.008354f, -0.003141f, -0.007374f, 0.001634f, -0.009544f, 0.00198f, - 0.005894f, 0.001434f, 0.001589f, 0.00921f, -0.00507f, 0.00448f, 0.0002687f, -0.003147f, 0.001627f, - -0.005608f, 0.006516f, 0.00935f, -0.004715f, 0.00833f, -0.00563f, 0.00281f, -0.005875f, 0.000629f, - 0.00993f, -0.002695f, 0.004486f, -0.00528f, -0.003807f, 0.00521f, 0.00010276f, 0.003307f, 0.000701f, - 0.0001151f, 0.00649f, 0.00934f, -0.001063f, 0.002327f, -0.0002892f, 0.003317f, -0.003506f, 0.004875f, - 0.0006566f, 0.000953f, -0.005898f, 0.00326f, 0.00877f, 0.00923f, -0.00622f, -0.006588f, 0.007748f, - -0.001789f, 0.00002104f, 0.002937f, 0.00816f, 0.005833f, -0.006634f, 0.006985f, 0.00951f, 0.002947f, - 0.001871f, -0.009445f, 0.0004554f, -0.006294f, -0.00649f, 0.00917f, -0.004158f, -0.00462f, -0.001531f, - 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0.004547f, 0.001851f, -0.005634f, 0.003641f, 0.007618f, -0.00985f, 0.009766f, -0.00459f, -0.002457f, - 0.00393f, -0.008224f, -0.003952f, -0.00813f, 0.007393f, 0.005188f, 0.007126f, 0.00639f, 0.001274f, - 0.002176f, -0.00894f, 0.002445f, -0.001414f, -0.00952f, 0.004444f, -0.001607f, -0.001501f, 0.00857f, - -0.005585f, -0.000724f, 0.003077f, 0.007797f, 0.007473f, 0.003546f, -0.00948f, -0.003933f, 0.004017f, - -0.003176f, 0.001448f, 0.002731f, 0.003504f, 0.00831f, 0.007763f, 0.002405f, -0.006264f, 0.00536f, - -0.0083f, 0.001413f, -0.0003624f, -0.001836f, 0.006027f, 0.005173f, -0.003073f, -0.008354f, 0.00164f, - -0.001941f, -0.002981f, 0.008156f, -0.004414f, -0.005413f, 0.002527f, -0.0004022f, 0.00625f, 0.008575f, - 0.00637f, 0.00765f, 0.0003421f, 0.00798f, -0.005287f, 0.00808f, -0.00646f, 0.000603f, 0.00955f, - 0.00889f, -0.002356f, -0.005306f, 0.002333f, 0.009514f, -0.003855f, 0.0054f, 0.005417f, 0.000675f, - -0.004402f, 0.00933f, -0.005234f, -0.00958f, 0.0089f, 0.009254f, -0.00757f, 0.0098f, -0.001879f, - 0.00789f, 0.002071f, 0.000677f, -0.007763f, -0.001941f, 0.001637f, -0.003653f, 0.00528f, 0.007465f, - -0.00557f, -0.006004f, -0.009476f, 0.000802f, 0.002075f, -0.007168f, 0.00398f, -0.006268f, 0.006287f, - -0.009575f, -0.001453f, 0.0092f, -0.00995f, -0.002644f, 0.005024f, 0.00966f, -0.006878f, 0.00995f, - -0.001319f, -0.002237f, 0.002209f, 0.00861f, -0.00883f, -0.003874f, -0.002903f, 0.00992f, -0.0016365f, - -0.00633f, 0.00823f, -0.00771f, -0.003204f, -0.00563f, 0.00563f, 0.00805f, -0.004936f, 0.003477f, - 0.00741f, 0.0043f, 0.006905f}; + LoadTensor("Weight_64_3_64.weight_data", weight_data); } void GetBias_3_64(std::vector& bias_data) { - bias_data = { - -0.003569f, -0.00789f, 0.002047f, -0.002829f, -0.000592f, -0.003313f, 0.00805f, -0.007397f, -0.006844f, - 0.00809f, -0.003479f, -0.0017395f, 0.007904f, -0.009056f, 0.005806f, 0.008896f, 0.004585f, -0.002356f, - -0.003815f, -0.00673f, 0.005787f, -0.001892f, 0.003233f, 0.005566f, -0.007626f, 0.00835f, 0.009415f, - -0.005707f, -0.0002623f, -0.007496f, -0.003569f, -0.00568f, -0.000693f, 0.00857f, 0.006607f, 0.005245f, - -0.0006056f, 0.008896f, 0.0000753f, -0.0001878f, -0.00957f, -0.003975f, 0.003006f, -0.006794f, -0.007935f, - 0.004246f, 0.004948f, 0.008896f, -0.0046f, -0.002516f, -0.000887f, -0.004555f, 0.002409f, 0.00364f, - -0.002491f, 0.004204f, 0.00010544f, 0.000783f, 0.00895f, 0.005367f, -0.004097f, -0.00592f, 0.009834f, - 0.001047f, 0.00677f, -0.004974f, -0.003212f, 0.00771f, -0.002256f, -0.001008f, -0.008484f, -0.002802f, - 0.00462f, 0.001329f, 0.004562f, 0.006687f, 0.002615f, 0.001449f, -0.0006714f, -0.001256f, 0.0003803f, - -0.005238f, -0.004112f, 0.001925f, -0.002827f, -0.00861f, -0.004723f, -0.002748f, -0.006134f, -0.00342f, - -0.007168f, 0.006626f, 0.001948f, -0.003838f, 0.006878f, -0.001717f, -0.003347f, -0.006287f, 0.00455f, - -0.00136f, 0.004364f, 0.006573f, -0.007545f, -0.004845f, 0.00883f, 0.00572f, 0.00675f, -0.003206f, - -0.00842f, 0.006428f, 0.00394f, 0.000642f, -0.002016f, 0.004486f, 0.009964f, -0.00918f, -0.0084f, - 0.001972f, 0.002031f, -0.00976f, -0.004494f, 0.006958f, -0.00262f, 0.00874f, 0.009865f, 0.0075f, - -0.00271f, -0.006386f, 0.002562f, 0.006397f, 0.00699f, -0.001731f, 0.005432f, 0.00271f, -0.006447f, - -0.00892f, 0.002897f, -0.0004315f, 0.001859f, -0.003462f, 0.007122f, -0.005135f, 0.005363f, 0.0051f, - 0.00806f, 0.00721f, 0.00799f, 0.00945f, -0.006943f, 0.006393f, 0.00935f, -0.0003269f, -0.004536f, - -0.006752f, 0.0095f, 0.00628f, -0.00418f, 0.001624f, -0.005577f, -0.008606f, 0.005486f, 0.002077f, - 0.007378f, 0.004734f, 0.0035f, 0.00991f, -0.001775f, 0.00247f, -0.00613f, 0.007202f, -0.00596f, - 0.003876f, -0.00789f, 0.004505f, 0.004795f, -0.002575f, -0.002932f, -0.003098f, -0.005463f, -0.00912f, - -0.00729f, 0.004486f, 0.006138f, 0.006924f, -0.00722f, 0.00841f, -0.001812f, -0.00959f, -0.000497f, - -0.00513f, -0.006042f, 0.007645f}; + LoadTensor("Bias_3_64.bias_data", bias_data); } -void SampleAttentionWeight(std::vector& data, std::vector& output, int elements, int start_offset, int step) { +void SampleAttentionWeight(std::vector& data, std::vector& output, + int elements, int start_offset, int step) { int data_length = static_cast(data.size()); output.resize(elements); @@ -1437,506 +70,19 @@ void GetCrossAttentionData_HeadSize40(AttentionTestData& data) { data.sequence_length = 3; data.kv_sequence_length = 5; data.mask_type = AttentionMaskType::MASK_NONE; - { - data.query_data = { - -1.22662961f, -0.35233688f, -2.51795793f, 3.08565354f, 4.24220848f, -2.51427174f, - 2.22180820f, -1.92292845f, -0.35114169f, 1.70695090f, 1.69466066f, 0.27359068f, - -0.64067757f, -0.63457423f, 1.04695463f, 4.04613352f, 0.97944307f, 0.15350986f, - 1.67937851f, -1.36576056f, 0.77318615f, -1.27569389f, 4.60397625f, -3.19242692f, - 0.48934177f, -3.07935381f, -0.11483648f, 1.47204328f, -0.63523442f, 0.67073810f, - 2.80178523f, 2.67149448f, -2.81271029f, 2.68525839f, 4.68173981f, 2.91258001f, - 3.57226992f, -3.05520511f, 2.54316950f, 2.00077820f, -0.95679653f, -0.32389647f, - 3.40642309f, -3.41444898f, 0.42168373f, 3.71653891f, 1.74413025f, -2.31608653f, - -1.05382800f, 2.33529496f, -0.03115923f, -2.09196687f, 2.51712871f, 0.32415283f, - 1.06346369f, -0.36822113f, 4.68930340f, 0.46780801f, -3.73769474f, 0.48317379f, - 0.39232603f, 0.27411360f, -3.42274952f, 3.13843346f, -1.47643280f, 1.33143926f, - -1.77027559f, 0.64681566f, -2.24492526f, 0.45514423f, 3.05239010f, -2.77623415f, - -0.01523268f, -1.31303573f, -3.99167180f, -1.17848396f, 2.49592471f, 2.05467582f, - -4.28567028f, -0.01797819f, - 4.67106724f, 1.53385055f, 3.39424896f, 3.93220329f, 1.68718219f, 2.44518471f, - -2.88907123f, -0.35424405f, 3.01430655f, 2.46258259f, 0.76977682f, -0.16410893f, - -0.17463332f, -3.87755418f, 1.83313918f, -2.97483563f, -4.08703470f, -0.08439432f, - 5.29304314f, 1.78443372f, -3.78656173f, -2.07051849f, 1.88238001f, -5.19135237f, - 3.88775992f, -2.59292984f, -4.11207771f, 3.96229005f, -0.83118176f, -3.83982468f, - 2.46327686f, -2.20555806f, 2.71137404f, 0.36317801f, 0.03267325f, 1.49253511f, - -1.07765102f, -0.87420821f, -1.38492739f, -3.10283113f, -6.48412514f, -3.24393439f, - -3.83601141f, -4.89051533f, 2.25563264f, 2.33896637f, 3.08240438f, 0.25861615f, - 5.35156775f, -4.30155373f, -0.39909154f, 0.51361942f, 1.70603693f, 0.56104976f, - -0.53627640f, -1.02876902f, -1.52522588f, 3.84260535f, 0.69256341f, 6.54086208f, - 1.46197557f, -0.43632865f, -0.60465157f, -1.64424038f, 1.38061714f, 0.57246995f, - 1.95028961f, 1.26038134f, 2.30116510f, -0.49234268f, -2.46396661f, -3.20620775f, - -3.26575089f, 1.24299562f, 2.17106104f, -2.19775343f, 3.60124683f, 0.57973087f, - 1.07749140f, 4.91360235f, - -0.21669322f, 0.33139130f, 1.75449383f, 9.52622700f, 2.17485499f, -1.66917014f, - 0.03545052f, 4.18067980f, 0.00023159f, 1.33923185f, -0.87918806f, -3.50237155f, - -1.46006012f, 0.60015154f, 5.83271360f, -0.22819775f, -0.31121445f, 5.66988373f, - 0.79325175f, 0.96488249f, -1.70520842f, -0.63099504f, -0.57731283f, -0.83466154f, - -1.16551876f, 3.83186436f, -1.45056069f, 0.50383788f, -1.44579923f, 0.65660918f, - 2.41228318f, -1.77592456f, -0.22811326f, -1.30705166f, 1.98969173f, -4.51494265f, - -1.47827673f, -3.64490080f, 2.93946624f, 1.29824829f, -3.46210217f, -3.89081907f, - -1.48601687f, -1.11542952f, -1.94489884f, -0.12696570f, -0.23979390f, 3.19791436f, - -0.63295209f, 1.12001634f, -5.84728909f, 1.05678606f, -1.42075634f, 0.05558330f, - 4.61813593f, 0.36126173f, -1.55681753f, 1.49261308f, 1.44369054f, -1.89044309f, - 0.72794700f, 0.88410646f, 1.78280950f, 0.46480489f, -1.13712585f, 1.98804855f, - -0.50860095f, -0.82247877f, -0.84092993f, 0.15579975f, -0.83490044f, 1.40706611f, - -0.62802029f, -1.00020695f, -0.42161250f, 4.65616417f, -0.14566854f, -5.21770144f, - -1.80859923f, -1.88397610f, - - 0.72858512f, 0.76285082f, -3.54603267f, -2.76666427f, -0.74586105f, 3.07966805f, - -1.23183393f, 2.65814924f, -0.48954675f, -0.01422951f, -0.80523360f, -0.05636902f, - 4.50960302f, 0.39967048f, 2.12411642f, -2.80581498f, -1.23623741f, -0.83596331f, - -1.59570324f, 0.31865728f, -2.93341351f, -0.91071963f, -5.62822533f, -0.31141007f, - 3.66986752f, 0.29200572f, 4.50133896f, -0.04906014f, 0.30284458f, 2.08347201f, - -0.26345047f, 2.89623761f, 1.47789168f, 0.25719327f, 0.59193242f, 3.06752014f, - 0.77815592f, 5.36399746f, -0.98917627f, 0.74345785f, 0.37825125f, 0.39711678f, - -0.51693177f, 0.70721328f, -1.65618515f, 0.39366072f, -0.48523498f, 0.26791164f, - 0.74384177f, -0.01070565f, 2.06832695f, 4.09473038f, -1.93577170f, 4.44833660f, - -3.57158875f, 1.13177609f, 0.04097128f, 0.97592485f, 0.32749751f, -0.63181406f, - 1.32568705f, 4.11899281f, -0.01445001f, -3.27274179f, -0.33302760f, 1.99459851f, - -0.71278077f, -2.11359572f, -0.49344134f, 2.91824555f, -0.30017141f, 3.06603670f, - 0.70625454f, -1.72438312f, 1.29221559f, 2.61260676f, -3.74348974f, -0.74985051f, - 3.06313038f, 0.40784115f, - 3.00617576f, 0.60401130f, -2.26022601f, 2.65955663f, 4.51086712f, 3.18778396f, - -2.03404522f, -1.75254703f, 1.52366590f, 2.97461796f, -1.71983969f, 1.67460120f, - -1.67232358f, -4.60054970f, 1.20151567f, -1.35206270f, -2.52547383f, -0.32723871f, - 0.20907879f, 3.33950758f, 1.31350076f, 4.40201521f, 4.84729719f, -2.02246284f, - 2.26325178f, -4.70484352f, 1.19820619f, -2.06560230f, 2.01903844f, 0.70123076f, - -2.18283868f, -1.58728933f, -1.76427519f, 1.73031628f, -1.02397823f, -0.82483894f, - 4.28719187f, 1.03131247f, -4.00242376f, 0.55060416f, 0.69296157f, -0.40307230f, - -1.57899165f, -0.64626098f, 0.38460332f, -2.79192090f, -0.99241018f, -6.47022247f, - 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- -1.9931641f, 2.8261719f, -0.57470703f, 2.5820312f, 3.6816406f, 1.78125f, 3.1953125f, -1.0664062f, 2.484375f, -2.265625f, 1.1123047f, 1.6445312f, -3.3222656f, 4.1601562f, -1.3828125f, -1.2744141f, -4.1875f, -2.5488281f, 0.1439209f, 0.36401367f, 1.2402344f, -1.9980469f, 2.9238281f, -0.83837891f, 0.23828125f, 2.7226562f, 3.8300781f, 0.30273438f, -1.8193359f, -1.0390625f, -0.15588379f, 0.17749023f, -2.1328125f, -0.40917969f, -0.30444336f, 0.31567383f, 0.43164062f, -1.1347656f, 0.37231445f, -1.3730469f, - - -2.203125f, -0.0080795288f, -0.62060547f, -0.057769775f, 3.2050781f, -1.9423828f, -0.44946289f, 3.3710938f, 1.6572266f, 0.31713867f, 2.6894531f, -2.0605469f, -1.546875f, -2.1328125f, 0.13586426f, 0.78369141f, -1.2148438f, -1.0078125f, 0.30273438f, 1.375f, 0.62548828f, -2.5820312f, -1.6708984f, -0.040985107f, -3.34375f, 1.7207031f, -6.5195312f, 0.10418701f, -0.58398438f, -0.98925781f, 0.72460938f, -2.1347656f, -1.4980469f, -2.0566406f, -0.33642578f, 3.9960938f, -1.7841797f, 0.94042969f, -2.71875f, 0.61865234f, - - -2.0078125f, 2.9941406f, -0.59277344f, 2.5761719f, 3.7832031f, 1.765625f, 3.3105469f, -1.078125f, 2.5195312f, -2.3027344f, 1.0693359f, 1.7207031f, -3.3554688f, 4.2421875f, -1.4033203f, -1.2929688f, -4.2070312f, -2.5683594f, 0.17724609f, 0.41577148f, 1.3242188f, -1.9326172f, 2.9101562f, -0.88330078f, 0.23376465f, 2.6992188f, 3.8300781f, 0.42358398f, -1.8964844f, -1.0371094f, -0.16442871f, 0.17700195f, -2.2109375f, -0.44287109f, -0.33642578f, 0.28515625f, 0.49194336f, -1.2324219f, 0.38037109f, -1.4160156f, - - -1.8134766f, 3.0058594f, -0.13061523f, 1.6318359f, 4.8476562f, -3.1074219f, 0.62841797f, 1.4414062f, 1.3876953f, 0.27319336f, 1.5742188f, -4.1679688f, 0.31518555f, -1.4072266f, 1.3613281f, 3.0175781f, -0.39794922f, -1.6777344f, 1.0517578f, 2.3359375f, 0.76806641f, -3.0585938f, 0.45483398f, -0.12078857f, -3.3105469f, -0.37841797f, -8.515625f, -0.11773682f, -0.23059082f, -1.6289062f, 0.27539062f, -2.3066406f, -2.1972656f, -2.8554688f, -3.1679688f, 2.7988281f, -3.1972656f, 1.3339844f, -4.359375f, 0.042053223f, - - 0.097961426f, 0.14807129f, -0.45410156f, 1.3339844f, -1.1279297f, 2.3261719f, 0.484375f, -0.72314453f, -1.1708984f, 0.81201172f, 3.3320312f, 1.7109375f, 1.453125f, 4.6484375f, -1.4169922f, -0.609375f, -1.1728516f, -1.0458984f, 2.5996094f, 0.47900391f, 2.984375f, -0.81835938f, 3.9121094f, -0.079711914f, -0.32177734f, 2.7636719f, 3.0507812f, -2.6953125f, -0.52294922f, -0.22570801f, 2.1582031f, 1.5126953f, -3.2558594f, -3.2695312f, -2.21875f, 2.7285156f, -2.0761719f, -0.89990234f, -2.3828125f, 0.044006348f, - - 1.2402344f, 2.2792969f, 0.33398438f, 2.2519531f, 0.67041016f, -0.55957031f, 0.20666504f, 1.3583984f, -1.9716797f, 2.6074219f, 2.2832031f, -2.0546875f, -2.4335938f, 0.53515625f, -0.15100098f, 1.9599609f, -0.51513672f, 0.31030273f, -0.49169922f, 1.4677734f, 2.234375f, 0.87451172f, 0.54736328f, -1.8681641f, -4.2265625f, -0.97509766f, -7.296875f, -1.3486328f, 1.3769531f, -1.8427734f, 3.1601562f, -2.4238281f, -0.82421875f, -2.7324219f, -0.52734375f, 2.2089844f, 0.66796875f, -0.42236328f, -3.03125f, -0.047302246f}; - } + LoadTensor("CrossAttentionData_HeadSize40.query_data", data.query_data); + LoadTensor("CrossAttentionData_HeadSize40.key_data", data.key_data); + LoadTensor("CrossAttentionData_HeadSize40.value_data", data.value_data); + LoadTensor("CrossAttentionData_HeadSize40.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_HeadSize40.fp32_output_data", data.fp32_output_data); + LoadTensor("CrossAttentionData_HeadSize40.fp16_output_data", data.fp16_output_data); } void GetCrossAttentionData_HeadSize40_NoBias(AttentionTestData& data) { GetCrossAttentionData_HeadSize40(data); data.bias_data.clear(); - { - data.fp32_output_data = { - -1.41742659f, 2.15152407f, 1.04562795f, -2.24374223f, -0.04717414f, 1.35415494f, -2.22757769f, 1.86239254f, 2.69114566f, -6.72842312f, 1.75712097f, -1.32716835f, -0.29526311f, 3.21845007f, 1.92469037f, 5.50302410f, -5.44591045f, 1.70150733f, -3.65152955f, 1.24731004f, -2.27949309f, 4.20098972f, 0.03186192f, -0.04943787f, 1.44350362f, 0.36441594f, 1.57309783f, 0.89751047f, 4.46334076f, -4.33237123f, 0.01717144f, -0.59184837f, 1.79316127f, 1.77931416f, 0.14474387f, -4.33217955f, -0.56225604f, -1.76532054f, -0.84570312f, -2.73260164f, - - 0.12478950f, -3.10866117f, -0.85841137f, 3.77194262f, -3.27266002f, 1.77506232f, -2.42189217f, 0.10825679f, 1.95918787f, 4.94663668f, 3.91713643f, 2.28616691f, -4.06595850f, 2.23235726f, -0.84805435f, -2.23345041f, -2.03120971f, -1.88641536f, -1.09826195f, 2.25707841f, 3.24559855f, 1.18912041f, -3.64727020f, -3.01371503f, 2.68850493f, -3.15157413f, -6.36788988f, -2.39488506f, 1.87837374f, 4.98469496f, 0.22985148f, -1.02970588f, -1.16538036f, -5.13183355f, -0.41686863f, 0.54360533f, 1.16716135f, 6.17682886f, 3.04362583f, 4.04813623f, - - -1.42417967f, 2.15435815f, 1.03971374f, -2.24015427f, -0.05345200f, 1.34537208f, -2.22884774f, 1.85825360f, 2.67446709f, -6.72772360f, 1.76715374f, -1.32337081f, -0.29505086f, 3.19914651f, 1.90399659f, 5.49347830f, -5.44424438f, 1.69376886f, -3.63920736f, 1.25351167f, -2.27403808f, 4.17100430f, 0.03175361f, -0.08079768f, 1.43696070f, 0.34488928f, 1.58517742f, 0.90214115f, 4.45445490f, -4.32695866f, -0.00118921f, -0.58452755f, 1.80395257f, 1.75610685f, 0.16048698f, -4.32064056f, -0.56982690f, -1.73989952f, -0.84093040f, -2.72663569f, - - 0.13186364f, -3.11423659f, -0.86316907f, 3.78399539f, -3.27828074f, 1.77901089f, -2.42992020f, 0.11804537f, 1.96141636f, 4.95947886f, 3.92235184f, 2.29242468f, -4.07375813f, 2.23869610f, -0.84603471f, -2.24866748f, -2.03565598f, -1.88956857f, -1.10135245f, 2.26302266f, 3.24525905f, 1.19217336f, -3.65679145f, -3.01720095f, 2.69548559f, -3.16282535f, -6.37307644f, -2.40397477f, 1.88918531f, 4.99577379f, 0.22660360f, -1.02878523f, -1.16615939f, -5.14430475f, -0.41941044f, 0.55101258f, 1.17067981f, 6.18814802f, 3.05311632f, 4.05843735f, - - 1.58491349f, 2.18418908f, -2.61316419f, -1.19461167f, 0.31131122f, 1.03194487f, -2.90404654f, -0.35682300f, 4.50262070f, 2.21961379f, 2.08062601f, -3.72921634f, 4.65971994f, 3.46044660f, 2.59209037f, 1.75916731f, -1.66252756f, 4.33679771f, 1.23986435f, -1.99405932f, -3.64911294f, -1.74503422f, 1.80885434f, 2.43805814f, -5.62830687f, 4.75278616f, -1.34041858f, 4.48804235f, 0.95380831f, -0.32654628f, -4.96857643f, -2.78253746f, 2.43861747f, 2.25903702f, -2.10894275f, -0.99328351f, 0.95549250f, -4.72304869f, -1.00289059f, -1.15769684f, - - -5.10913038f, -1.38361323f, 3.78980398f, -0.27995712f, 0.07776496f, 1.53318942f, -1.45798743f, 0.06345022f, 0.32985163f, -1.20825279f, 3.32992506f, -3.16107416f, 3.14213490f, -1.75764465f, -1.81823230f, 6.00926352f, 1.83184552f, 0.88772279f, 1.13544476f, -0.16091508f, 0.73152179f, 2.89268398f, 2.53888154f, -0.62667179f, -1.92644227f, 5.24402714f, -3.04914069f, 0.73081797f, -4.36438751f, -0.01024710f, 2.05606008f, -1.59136617f, -2.93256354f, 0.90090895f, 0.44130960f, -3.17225385f, -2.68491602f, 1.39586127f, -2.62767482f, -1.42729461f, - - -1.82169747f, 2.12078428f, -0.43695056f, 2.27537584f, 3.42691755f, 1.65860319f, 2.57705307f, -1.17967665f, 2.09597683f, -2.18013787f, 1.50621653f, 1.55477905f, -3.70713329f, 3.45152068f, -1.70394862f, -1.33734357f, -4.18969202f, -2.11793780f, 0.37242663f, -0.20806181f, 0.96408093f, -2.22627115f, 3.10095739f, -0.97176194f, 0.22555678f, 2.99631286f, 4.30567598f, -0.29444879f, -1.22917330f, -1.39327240f, -0.15407819f, 0.46064961f, -2.00380874f, -0.62698770f, 0.04687182f, 0.81974965f, 0.54190254f, -0.56075597f, 0.43117812f, -1.70553112f, - - -1.88462663f, -0.18665671f, -1.06960690f, 0.64497805f, 2.83166552f, -2.34236050f, -0.68599927f, 2.52589321f, 1.09144545f, 0.48552963f, 3.03313494f, -1.95211184f, -1.85385156f, -1.15996051f, 0.42496145f, 0.14187109f, -1.67549849f, -0.85382032f, 0.31291258f, 1.16500401f, 0.48290920f, -1.64285612f, -1.35711002f, 1.14920509f, -2.76547956f, 0.50387645f, -6.65734005f, 0.06499285f, -0.26013616f, -0.19627771f, 0.56354129f, -1.26614785f, -0.94395208f, -1.86354482f, 0.00720191f, 3.69053054f, -1.17969584f, 2.35666990f, -3.26046968f, 0.78327948f, - - -1.86769938f, 2.71813035f, -0.50948530f, 2.24504375f, 3.71597552f, 1.60988891f, 2.97607589f, -1.22726071f, 2.16237378f, -2.29194784f, 1.40557051f, 1.83395016f, -3.73706627f, 3.78015113f, -1.80717337f, -1.43455577f, -4.23915625f, -2.15067673f, 0.56629229f, -0.00130248f, 1.32205904f, -1.98912859f, 3.07867503f, -1.11066699f, 0.18896791f, 2.90356636f, 4.28740644f, 0.08492497f, -1.52221036f, -1.38736534f, -0.12700811f, 0.50624669f, -2.32619810f, -0.79596692f, -0.10685119f, 0.74229264f, 0.71136874f, -0.93978000f, 0.38004258f, -1.84059870f, - - -2.26918745f, 2.92838788f, -0.45714897f, 2.18296647f, 4.10041952f, -2.25037718f, 0.51260191f, 0.39325786f, 0.90468413f, -0.66815877f, 1.22376275f, -3.15594530f, 0.84955496f, -1.06137490f, 1.20908797f, 1.87171698f, -0.91993034f, -1.29943442f, 1.31052589f, 1.59136820f, 0.83899784f, -3.01598954f, 0.73303372f, 0.39389658f, -2.76502943f, -0.90127987f, -6.78780794f, -0.19403477f, 0.46670800f, -2.34413576f, 0.33809948f, -1.62583923f, -2.65135598f, -2.10512233f, -2.88674784f, 1.88245845f, -2.78318572f, 1.28361940f, -3.72045994f, -0.64210486f, - - -0.40192991f, 0.42336106f, -0.37019759f, 1.41447365f, 0.19176102f, 2.02308369f, 0.81132519f, -0.95749462f, -0.39838922f, -0.09587491f, 3.00953579f, 1.66607380f, -0.43405950f, 3.86591244f, -1.75709438f, -0.90621388f, -2.13548446f, -1.09224761f, 2.10858512f, -0.07912997f, 2.24841881f, -1.36435628f, 3.77529001f, -0.48102456f, -0.16689897f, 3.00326085f, 3.76847577f, -2.26835036f, -0.41139305f, -0.83580929f, 1.44518113f, 1.39267445f, -2.85280180f, -2.63157845f, -1.30405295f, 2.46063781f, -1.14184821f, -0.49150658f, -1.47628820f, -0.76379204f, - - 1.59237325f, 1.84326255f, 0.11042996f, 2.89765906f, -0.49430391f, 0.39030308f, 0.02746993f, 0.65821123f, -3.10381436f, 2.78205943f, 2.55404949f, -0.96529919f, -2.98005986f, 1.13010681f, -0.68560266f, 1.04888844f, -0.81784761f, 1.16720343f, -0.80749500f, 0.82892329f, 2.64979362f, 1.93710601f, 0.61530274f, -1.93501818f, -4.14114285f, -1.56158972f, -6.18459988f, -1.75687492f, 2.28010345f, -1.99459755f, 3.83940291f, -1.92955184f, -0.56180751f, -2.16278362f, 0.29707330f, 1.89639890f, 1.92093897f, -0.57678437f, -2.60749125f, -0.42066064f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_HeadSize40_NoBias.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_Batch2_HeadSize32_RightSidePadding(AttentionTestData& data, bool is_mask_1d) { @@ -1960,277 +106,20 @@ void GetCrossAttentionData_Batch2_HeadSize32_RightSidePadding(AttentionTestData& AttentionKernelType::AttentionKernel_TrtFusedAttention, AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention}; - { - data.query_data = { - 0.66417468f, -2.82039404f, 1.66603971f, 4.84341049f, -1.63285708f, 3.61133432f, - -1.07151258f, -0.41698062f, -1.38491797f, -3.79137778f, 1.34514475f, -2.97253704f, - 2.12579250f, -0.02954102f, 2.30081463f, 0.21410012f, 1.84038579f, 0.46486610f, - -4.49463224f, 0.69027799f, 1.01090157f, 0.04715919f, -1.60957003f, 0.10730582f, - -5.77672052f, 0.37593889f, 2.04825425f, -1.00890708f, -3.88195300f, -2.69047785f, - 1.15699422f, -1.13536406f, -0.42816854f, 3.12039518f, 3.21898699f, -0.51998949f, - -4.72336435f, -0.78055519f, -0.72722042f, 3.17147565f, -1.31066322f, -3.09425855f, - -3.54743338f, -0.07284085f, 1.10525322f, 1.82087338f, -2.03681397f, -4.27978802f, - 0.26408362f, 0.58637118f, -2.07128787f, -3.48036027f, -0.03049034f, -1.99293542f, - -0.67289937f, 1.17342246f, -4.84998703f, -2.43558168f, 1.16422236f, 0.26511097f, - -1.98199308f, -1.86423326f, 1.61366916f, -0.35201707f, - -1.43554640f, -1.37493825f, 2.32563400f, -1.31762123f, -1.46716797f, 0.18536982f, - 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2.14098549f, 0.65744257f, 2.12003636f, -0.21332240f, -0.35039914f, -1.79318547f, 1.08148456f, 0.83520722f, - -0.37325758f, 0.44315636f, -0.50703102f, -0.19921407f, 1.08093989f, -1.52517128f, -1.01477206f, -2.08499599f, - 0.05307493f, 0.56386751f, 0.16719794f, 0.99758488f, 0.35134155f, -2.70159864f, 0.49787593f, -6.01998806f, - - 1.88393891f, 1.20359635f, -1.11693203f, -1.24092197f, -2.47922421f, 2.11120105f, 5.19413376f, 2.67079711f, - 1.07527149f, 0.64369327f, 2.57635832f, 1.27686763f, 0.69491446f, -3.13548803f, -2.04371452f, 4.62090492f, - 2.18864536f, -2.10483122f, -0.04580984f, 1.08532572f, -3.46754074f, -0.53330994f, -1.35113037f, -1.51521778f, - -0.46994060f, -2.27551699f, -0.53152251f, 0.47133854f, 0.07705012f, 0.48279381f, -1.28113365f, 0.48468336f, - -1.54411674f, 0.06915778f, 0.64939111f, -1.33318806f, 0.63385141f, 1.72500539f, -1.27450287f, 2.53234506f, - 2.78955889f, 0.10935718f, 1.24130249f, -2.24100065f, -1.41059852f, -1.18030620f, 1.50915027f, 1.37942517f, - -1.41709673f, -0.74830860f, 0.30404601f, -0.99458563f, 0.22929534f, -1.72507358f, -0.68753922f, -2.64537501f, - 0.58683372f, 0.88788664f, 0.54932535f, 1.45773280f, 0.96530700f, -3.57728553f, -0.41517627f, -4.86154747f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding.query_data", data.query_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding.key_data", data.key_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding.value_data", data.value_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_Batch2_HeadSize32_RightSidePadding_NoBias(AttentionTestData& data, bool is_mask_1d) { GetCrossAttentionData_Batch2_HeadSize32_RightSidePadding(data, is_mask_1d); data.bias_data.clear(); - { - data.fp32_output_data = { - 2.52855659f, 1.00436294f, 0.83871710f, 0.97005701f, 1.33615291f, -2.07353282f, 0.14190522f, -1.42923164f, - 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-0.21569058f, 0.65559602f, 3.58669281f, 0.40837619f, 2.40912223f, 1.31780922f, -4.45945454f, 0.64903581f, - -1.10752177f, -1.79390311f, 0.89312351f, -1.84512544f, -1.13948750f, 3.87221098f, -2.74163318f, 2.90849519f, - -0.31782085f, 3.12108278f, 0.80056298f, 1.02164125f, -0.07995117f, -0.96148860f, 3.49803638f, -4.48321056f, - -1.50024915f, -2.58987570f, 0.61711067f, 4.13532829f, -4.38111591f, -2.48988461f, -0.43977243f, -3.93134618f, - -2.67314148f, 2.64455128f, 0.11041284f, 1.26786041f, -0.24446392f, -0.86178148f, 2.35680771f, -1.69236851f, - - 4.57896709f, -1.96923840f, -3.86827397f, 3.18770218f, -5.16361237f, 1.42594552f, -1.43489969f, 1.62748241f, - 0.91413617f, -0.27147719f, 0.89311284f, 0.39315033f, 1.18184888f, 4.30171919f, -2.32771778f, 1.61144078f, - 1.31702852f, 1.47999835f, -0.20565441f, 0.75846130f, -0.13237341f, -2.10059047f, 0.12025870f, -0.58277667f, - 1.93927360f, -3.11170268f, 0.84666550f, 0.08490579f, -0.36315942f, -3.13071775f, 0.12070279f, -0.10385174f, - -2.09942603f, 1.27883554f, 0.42277446f, -1.00997567f, -0.84779590f, 2.87665153f, 0.18837044f, 2.81797147f, - 1.85540521f, 0.30605689f, 1.86793220f, 0.43789154f, -0.20980379f, -1.73483229f, 0.97748178f, 0.32941481f, - -0.63111353f, 0.56805360f, -0.17779620f, 0.25940496f, 0.92033458f, -1.44722617f, -1.27452552f, -2.43680239f, - -0.11858715f, 0.98449469f, 0.01566132f, 0.69114012f, 0.41016975f, -2.33734345f, 0.48214769f, -5.91884756f, - 2.11303473f, 0.79722011f, -1.16258705f, -1.32830858f, -2.66458011f, 1.94228184f, 4.57733870f, 2.46697760f, - 0.73631936f, 0.59500724f, 2.83104920f, 1.34561014f, 0.34483883f, -3.20511031f, -2.47195292f, 4.32895803f, - 2.08832264f, -1.53225064f, 0.33865568f, 0.67958182f, -3.29418707f, -0.68394697f, -1.10808134f, -1.67574179f, - -0.39239436f, -2.11620450f, -0.01758179f, 0.11357109f, 0.39056650f, -0.03823794f, -1.16129172f, 0.79321450f, - -1.71389270f, -0.13380881f, 0.83875018f, -0.88353348f, 0.68820363f, 2.08583164f, -1.14706731f, 2.17536139f, - 2.48886776f, -0.22925906f, 1.00967121f, -1.54254520f, -1.24530232f, -1.13623202f, 1.39518356f, 0.86095339f, - -1.65063286f, -0.59565234f, 0.61438411f, -0.51743579f, 0.08853177f, -1.64247108f, -0.95491660f, -2.98412538f, - 0.40273598f, 1.30096471f, 0.38888580f, 1.14056730f, 1.00983083f, -3.19262862f, -0.40963191f, -4.78739595f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_Batch2_HeadSize32_RightSidePadding_NoBias.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_Batch1_HeadSize32_LeftSidePadding(AttentionTestData& data) { @@ -2249,157 +138,19 @@ void GetCrossAttentionData_Batch1_HeadSize32_LeftSidePadding(AttentionTestData& AttentionKernelType::AttentionKernel_TrtFusedAttention, AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention}; - { - data.query_data = { - 2.88765883f, 1.27536213f, -0.57580215f, 2.73696542f, 2.19016314f, 0.42629790f, 1.55081677f, -2.01307678f, - -0.80203497f, -1.23206115f, 1.78565156f, -2.09875321f, -2.22730732f, -0.98120236f, -0.25774139f, 0.75868356f, - -2.87585187f, -0.41810805f, -2.11528730f, 0.50642025f, -0.29446256f, -3.69675803f, -2.73721838f, -1.51089072f, - 0.74300194f, 0.27352047f, -0.88251829f, 2.82622814f, 0.73837662f, -2.14588642f, 0.37608737f, -0.06190044f, - -1.97659302f, -2.22348428f, 2.25573063f, -2.24459195f, -2.28073978f, -0.52412349f, -0.57297325f, 3.29259396f, - 1.35617173f, -0.83082151f, 0.03767079f, 1.82568312f, 0.88193995f, 1.15579486f, 1.87845564f, -0.15923920f, - 2.37435389f, 1.49093378f, 1.95134592f, -1.67609048f, -0.45959851f, 1.63960719f, 3.44909906f, -0.23531833f, - -0.57074630f, 1.38279045f, 0.58870834f, 0.85297751f, -1.44973445f, 1.56243801f, -0.67229253f, -0.16198707f, - - -0.23966503f, -0.15329531f, -3.22765136f, 0.60538405f, -0.33244422f, -1.34865439f, -0.24373266f, -1.78808010f, - -1.53090763f, 1.75037694f, -0.71890754f, 0.12527336f, 1.26654553f, -0.86477917f, -1.49822962f, 1.67973542f, - 0.99763191f, -0.07183220f, 1.55289185f, 1.62626481f, -0.04283767f, -2.55072594f, -1.95238030f, 0.60994428f, - -2.53714681f, 1.54605150f, 0.05900350f, 1.42194426f, 0.33801061f, 1.25557244f, 0.67291188f, -1.36867523f, - 1.86936152f, -1.19588101f, 0.75778806f, 1.85271311f, 0.02081686f, 2.65807819f, 0.78890860f, -1.07388866f, - 4.18109226f, 0.06373940f, 2.86840463f, 0.90427721f, -0.09531648f, -0.40835506f, 1.60812938f, -1.61683714f, - -0.45421624f, -2.25537109f, -1.35910070f, -0.25111723f, -0.71782172f, 0.62597942f, -0.42838976f, 0.23198499f, - 1.29250073f, -2.01550317f, 0.14619158f, -0.03868395f, -0.74211842f, -3.17291188f, -1.90475547f, 2.02544284f}; - } - { - data.key_data = { - 1.14242256f, 1.08148384f, -0.00962424f, -1.62719429f, 0.86478198f, 0.16862091f, 1.01692820f, -1.15278327f, - -1.13622630f, 1.78038371f, 0.58222097f, 0.39166588f, 1.75063372f, -1.20408881f, 0.75154918f, 0.58156419f, - -0.98975772f, -0.82555556f, -0.72656512f, -2.42399549f, 2.19217968f, 2.18518472f, -1.72216129f, 1.35098433f, - -0.34989786f, -0.69064844f, -0.98365444f, 3.10148478f, 0.64813483f, 1.78129303f, -0.47006512f, 2.53122735f, - 0.09757380f, 0.04077591f, -0.81791472f, -0.19737752f, 1.13775492f, -1.51351953f, 0.59109330f, 2.86624002f, - -0.09282493f, -1.69204521f, 1.27087700f, 3.53944731f, 0.59776509f, -0.90838081f, -0.15813766f, -1.86199224f, - 0.18734205f, -0.76110429f, -0.02243887f, -0.94068182f, 1.32443166f, 0.03512055f, -0.13194422f, -1.50401211f, - 0.92001319f, 0.20918207f, -1.34839189f, 1.56431675f, -0.61030018f, 2.39562368f, -1.56722510f, -0.96874726f, - -0.48726845f, -1.41476154f, -1.45116997f, 0.53907454f, -2.14415288f, 1.14340270f, -0.21846619f, -2.72349358f, - 2.99664998f, -2.38684058f, 0.95269018f, 0.04208702f, -1.75080788f, 1.24652982f, -1.76879966f, 3.10814905f, - 2.48754454f, -0.62601894f, 1.41356945f, 0.10340121f, 1.09059846f, -0.78241473f, -0.61477584f, -0.19339988f, - -0.48253334f, -2.41782594f, 1.04690075f, 0.14725411f, -0.20820639f, -1.95920563f, 0.96303236f, -1.20068836f, - - -1.71051037f, -1.90946770f, -2.07985783f, 2.35042953f, 0.35059446f, -0.44228595f, 4.08558750f, -0.60121447f, - 0.78836018f, 0.35280651f, 0.23129070f, -0.21523762f, 0.12277550f, 0.12348226f, -1.62759030f, -2.78246498f, - 4.04853964f, 0.29263157f, -0.38621908f, -1.07599223f, -1.99170423f, 1.41409016f, 2.19121861f, -3.53451037f, - 3.63692737f, 0.68270516f, 2.51469731f, 2.57543731f, -2.39040112f, -3.97164130f, 1.28371549f, 1.64144099f, - -0.70385075f, 2.55361128f, 1.60707259f, 0.84735453f, -2.07756495f, -1.99240303f, -3.60991144f, 2.87136865f, - 2.31296396f, 2.30251813f, -1.05624914f, -2.43777156f, -0.27048296f, 2.39037871f, -2.04504776f, 1.65183067f, - -0.38970214f, 0.16808379f, -1.30286717f, 1.90201700f, -2.71696734f, -0.66445369f, 1.27085483f, -0.60816145f, - 1.81054437f, -1.55584621f, -2.19360781f, -4.52794456f, -0.90534067f, 0.94724411f, 2.40401077f, -2.94815230f, - -3.19650269f, 2.50638890f, 1.02038431f, 1.50519919f, 0.47196171f, -1.89026380f, -1.86559379f, 0.82210326f, - 0.10818237f, 1.45290673f, 1.62321615f, -0.61283481f, -1.42501950f, 2.10349464f, -1.65715265f, 0.30090189f, - -3.81919909f, -2.44903922f, -1.20557833f, -0.69951278f, -1.31475580f, -3.73842764f, 1.49299407f, -0.70933276f, - -1.49021530f, 0.71776378f, -1.23052382f, -2.13119912f, -1.20718014f, 2.30572701f, 1.78386402f, -1.57122159f}; - } - - { - data.value_data = { - 1.79297853f, 0.96909231f, 1.23087275f, -0.61933923f, -0.56477690f, 1.47813499f, 0.51474279f, -3.44743419f, - 0.95816678f, -0.20553169f, -0.76906109f, -4.60927439f, 0.40629998f, 0.91934747f, -1.09594405f, -1.45653892f, - -0.59282207f, 0.05621797f, -2.26634383f, -1.30799258f, 1.22072279f, -3.60811162f, 1.70111597f, 0.47336632f, - -1.43857694f, -0.13917151f, -1.34617388f, 1.07960105f, -1.77342618f, 0.31946269f, 1.19137061f, 2.59346104f, - -1.82395399f, 0.73557752f, 2.32600021f, -0.22650969f, -0.48526058f, 1.40349376f, -0.33553454f, 0.45531431f, - 0.73859257f, 0.37798560f, 0.85344458f, -1.30447221f, 1.23349071f, -0.26439479f, 1.18636096f, -0.33328748f, - -0.50939041f, 0.53500950f, 1.33486223f, -1.54447496f, -2.88690519f, -0.06809106f, -0.00597921f, -1.07510388f, - 0.62182164f, 0.50033569f, -0.88293070f, 2.56142712f, 0.37708595f, 1.59349704f, -1.17139614f, 0.89580274f, - 0.69456708f, 2.91441655f, -0.25431669f, -1.20305562f, 2.06701255f, -0.86700624f, -2.23615170f, 0.13303493f, - -2.97540593f, 0.08654684f, 1.40381706f, 3.54294443f, -2.07661867f, -1.33181918f, 2.24228764f, 1.79975545f, - 2.14695477f, 1.40222490f, -0.29813689f, 1.94485068f, 1.99623775f, 1.53450203f, 0.28755581f, -0.67934704f, - -0.92102510f, -1.52764773f, 1.11267352f, -3.90122724f, 0.22128634f, 0.14945325f, -4.38529491f, -1.58423281f, - - -2.45574522f, -1.91599977f, 5.05240345f, 2.24617362f, 3.99182248f, 0.92924285f, -0.39660916f, -0.08696688f, - 0.24855530f, 0.71378094f, 0.92413902f, 1.73599064f, 1.03852975f, 2.44676781f, 0.35013664f, 0.98107171f, - 1.62946916f, 0.41239718f, -1.41385484f, 2.49293518f, 2.32976985f, 2.89612579f, 2.66875219f, 1.47379971f, - 1.31164551f, -1.82183075f, -5.15272474f, 0.28575048f, 0.16861364f, -0.47264135f, 0.22565089f, -0.37727535f, - -1.13935280f, 0.38051969f, -2.38735437f, -2.80645251f, 0.18637873f, 2.13938355f, 2.92260599f, -0.38653925f, - 0.58366799f, -1.67636371f, -2.29396892f, -1.31527638f, 2.39795637f, 0.39815575f, -0.98530269f, -1.29227996f, - 0.14452982f, -0.38186538f, -1.71267688f, 0.18121701f, -2.26441002f, -0.94511753f, 0.27371156f, -2.44858527f, - -0.21510160f, -2.65228534f, -2.16755104f, 0.86151361f, 0.77589297f, -1.06628847f, 0.73745233f, 1.15778029f, - -0.73659700f, 0.74325305f, -1.97666430f, -1.07301974f, 0.17534591f, -1.66584718f, 1.21820331f, 0.67675018f, - -1.08938253f, 1.78010321f, 0.39817584f, -0.02914053f, 1.13571596f, -0.44081455f, 1.70561552f, -2.12085509f, - -0.69322622f, -1.87331009f, -2.15000772f, 2.08436966f, 1.70494926f, -3.69169927f, -1.22119129f, -1.60190558f, - -2.09093666f, -1.02816033f, -1.78743768f, 2.34501553f, 2.79939008f, 1.82245076f, 1.47408092f, 1.10063124f}; - } - - { - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, -0.34948170f, -0.19608477f, 0.19725692f, 0.39987487f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, -0.23178342f, -0.13692456f, -0.04889601f, 0.48739988f, - -0.25891554f, 0.13431972f, 0.22861153f, 0.06360734f, 0.48096961f, -0.47906545f, 0.43613154f, -0.23511401f, - -0.10595283f, -0.42839217f, 0.28931111f, -0.13180739f, -0.45826656f, 0.23286396f, -0.43407962f, 0.40754890f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, 0.27376485f, -0.38174152f, -0.43700469f, 0.38040614f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f, 0.07120579f, -0.08055863f, 0.12095112f, -0.27988660f, - 0.06004709f, -0.05600315f, -0.25510073f, 0.41887105f, -0.19016314f, 0.47241372f, 0.12890404f, -0.24272856f, - 0.21106839f, -0.40523255f, 0.10336459f, -0.11084765f, 0.42408967f, -0.15285304f, -0.28945464f, -0.25714916f, - -0.10567203f, 0.26791072f, -0.08976898f, 0.31341976f, 0.06027532f, 0.14307594f, 0.31587386f, 0.16180152f, - 0.34785229f, 0.00531715f, -0.35168743f, -0.11641458f, 0.39196932f, 0.44535065f, 0.43545735f, 0.15593112f, - 0.06171834f, -0.42181283f, -0.41170910f, 0.40969193f, -0.01510030f, 0.07973170f, -0.18156880f, 0.21522856f, - 0.03915739f, -0.20913908f, -0.47068381f, 0.35633272f, -0.35124153f, 0.36624825f, -0.05567622f, -0.35343069f}; - } - - { - data.fp32_output_data = { - 0.23503941f, 2.87619758f, 0.01845241f, -0.75242990f, 1.76869011f, -0.40492195f, -1.65323853f, 0.34011719f, - -2.10573196f, 0.13281155f, 0.97480160f, 2.74546146f, -1.21957457f, -0.73649400f, 2.52938581f, 1.65599120f, - 1.83545303f, 0.85856718f, -0.48040742f, 1.86428785f, 1.29504943f, 1.38906729f, 0.06474495f, -0.51972288f, - -0.66509569f, -1.45185244f, 0.36160457f, -2.63688278f, -0.10806514f, 0.71859169f, -3.98941422f, -1.58921516f, - - -1.89806330f, 1.03079379f, 2.20389438f, 0.07467184f, -0.39299977f, 1.51811528f, -0.04347950f, 0.61307698f, - 1.03990030f, 0.37965038f, 0.50865448f, -1.36013806f, 1.58397710f, 0.16757873f, 1.63505113f, -0.15062472f, - -0.41438234f, 0.12406474f, 0.90268815f, -1.09105420f, -2.84080887f, 0.03172458f, -0.18386938f, -0.85491556f, - 0.64164376f, 0.26578158f, -1.32860518f, 2.83676863f, 0.02389192f, 1.94164813f, -1.26734924f, 0.51129180f, - - -0.84226906f, 1.01116371f, -2.06643319f, -0.75959998f, 0.23562123f, -1.52277124f, 1.53407717f, 0.83855170f, - -0.74153024f, 1.78542042f, 0.04648840f, -0.14555511f, 1.52768528f, 0.00453609f, 2.14107275f, -1.96492398f, - -0.63150787f, -2.29512286f, -2.56171679f, 2.49406147f, 1.68984890f, -3.61196756f, -1.40276003f, -1.38667703f, - -2.05177927f, -1.23729944f, -2.25812149f, 2.70134830f, 2.44814849f, 2.18869901f, 1.41840470f, 0.74720055f, - - -0.84226906f, 1.01116371f, -2.06643319f, -0.75959998f, 0.23562123f, -1.52277124f, 1.53407717f, 0.83855170f, - -0.74153024f, 1.78542042f, 0.04648840f, -0.14555511f, 1.52768528f, 0.00453609f, 2.14107275f, -1.96492398f, - -0.63150787f, -2.29512286f, -2.56171679f, 2.49406147f, 1.68984890f, -3.61196756f, -1.40276003f, -1.38667703f, - -2.05177927f, -1.23729944f, -2.25812149f, 2.70134830f, 2.44814849f, 2.18869901f, 1.41840470f, 0.74720055f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding.query_data", data.query_data); + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding.key_data", data.key_data); + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding.value_data", data.value_data); + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_Batch1_HeadSize32_LeftSidePadding_NoBias(AttentionTestData& data) { GetCrossAttentionData_Batch1_HeadSize32_LeftSidePadding(data); data.bias_data.clear(); - { - data.fp32_output_data = { - 0.38947105f, 2.65047002f, 0.05826539f, -1.08475602f, 1.75782788f, -0.59195572f, -2.00590920f, 0.17207618f, - -2.52548885f, 0.12185203f, 1.33714449f, 2.95572400f, -1.67562902f, -1.20251048f, 2.11437178f, 1.54135668f, - 1.82516265f, 1.29716969f, -0.10031381f, 1.52215052f, 1.40468919f, 1.34036255f, 0.25199673f, -0.72728944f, - -0.73412323f, -1.28197598f, 0.87092417f, -3.11833549f, 0.24016008f, 0.32438612f, -3.99596047f, -1.28379905f, - - -1.78660965f, 0.76788503f, 2.28773952f, -0.24098979f, -0.44741583f, 1.36982703f, -0.36371663f, 0.45053560f, - 0.68352193f, 0.37366420f, 0.86160547f, -1.23259544f, 1.18440890f, -0.28022242f, 1.20201802f, -0.30165902f, - -0.47000250f, 0.54786849f, 1.31064832f, -1.49273574f, -2.81449866f, -0.04432804f, -0.00162671f, -1.06923568f, - 0.59894449f, 0.47026503f, -0.85334015f, 2.46559978f, 0.37477580f, 1.57208502f, -1.21905136f, 0.85902911f, - - -0.73659700f, 0.74325305f, -1.97666430f, -1.07301974f, 0.17534591f, -1.66584718f, 1.21820331f, 0.67675018f, - -1.08938253f, 1.78010321f, 0.39817584f, -0.02914053f, 1.13571596f, -0.44081455f, 1.70561552f, -2.12085509f, - -0.69322622f, -1.87331009f, -2.15000772f, 2.08436966f, 1.70494926f, -3.69169927f, -1.22119129f, -1.60190558f, - -2.09093666f, -1.02816033f, -1.78743768f, 2.34501553f, 2.79939008f, 1.82245076f, 1.47408092f, 1.10063124f, - - -0.73659700f, 0.74325305f, -1.97666430f, -1.07301974f, 0.17534591f, -1.66584718f, 1.21820331f, 0.67675018f, - -1.08938253f, 1.78010321f, 0.39817584f, -0.02914053f, 1.13571596f, -0.44081455f, 1.70561552f, -2.12085509f, - -0.69322622f, -1.87331009f, -2.15000772f, 2.08436966f, 1.70494926f, -3.69169927f, -1.22119129f, -1.60190558f, - -2.09093666f, -1.02816033f, -1.78743768f, 2.34501553f, 2.79939008f, 1.82245076f, 1.47408092f, 1.10063124f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_Batch1_HeadSize32_LeftSidePadding_NoBias.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV(AttentionTestData& data) { @@ -2414,222 +165,14 @@ void GetCrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV(AttentionTes data.skip_kernel_types = { AttentionKernelType::AttentionKernel_Unfused, AttentionKernelType::AttentionKernel_TrtFusedAttention}; - { - data.query_data = { - -0.35420692f, 1.31206024f, -2.80201197f, 2.42258096f, -0.86031514f, -1.44535458f, -0.10832444f, -2.00132895f, - 1.62475216f, 0.10978927f, 1.84596729f, 0.48908550f, 1.44369888f, 0.87542874f, -1.16434252f, 0.52133209f, - 1.54848897f, -2.21174526f, -0.28574878f, 0.70815033f, 1.18327498f, 3.14097571f, -0.25795099f, 1.89341247f, - -0.11603792f, 0.38110194f, 0.40873206f, -1.14149106f, 0.79770875f, -0.98069525f, -1.53588808f, 0.50821728f, - -2.21641898f, 0.55090773f, 0.80901796f, -0.56089771f, 0.03574468f, -1.27940118f, -0.02213959f, -0.80698186f, - -0.82701880f, 1.72937381f, 1.56083691f, -0.30311784f, -0.25183848f, 0.24280515f, 0.29569417f, -0.31162494f, - 0.48996922f, 0.22795241f, 2.07125854f, 1.45823467f, 3.03750706f, 1.53734803f, 0.48668906f, -1.63703632f, - -0.14114749f, 1.85963213f, 1.20729232f, -0.28972962f, -0.80783498f, -1.16619551f, -0.60004634f, 0.02498829f, - - 3.50846076f, -2.50027657f, -2.59866142f, 1.58495271f, 2.21110034f, -2.74877763f, -1.00267041f, 0.62646407f, - 2.50227380f, -0.27291518f, -0.33037442f, 0.75840306f, 0.45437157f, -0.79876304f, 0.83509272f, 2.53716302f, - 0.01348384f, -2.16307616f, 2.01661849f, 2.10746121f, -1.70485222f, 1.35548759f, 1.39401650f, -0.99451691f, - -4.13484812f, 0.56262714f, -0.92725742f, -0.16389316f, -1.31260049f, 2.32357836f, -3.05251694f, -1.12570131f, - 1.87849474f, -1.80381167f, 0.52235699f, 2.38887334f, -1.58878529f, 0.69571090f, 1.65044296f, -0.27024290f, - 3.59580970f, -1.97888982f, 1.17034674f, 0.26716161f, -1.16770899f, 0.74609619f, 0.78886843f, 0.15717520f, - -0.93303132f, -0.84753871f, -4.32799959f, -1.94716609f, -1.16980326f, 1.62631667f, 2.41053247f, 3.78186774f, - 0.26432252f, -0.40396988f, 2.04414082f, 0.65150046f, 0.47777444f, -2.57569051f, 0.99004912f, 2.47947693f}; - } - { - data.key_data = { - 2.66554713f, 0.04116637f, -1.14599442f, -1.99071956f, 0.42523879f, 0.94212061f, 1.15597987f, -1.76809072f, - -1.89803648f, -0.74707657f, -0.71960962f, 0.67453432f, 3.31946969f, 1.06201041f, 2.29824829f, 0.23788756f, - 1.69329333f, 0.06745748f, -1.34720469f, 1.81031406f, -0.33143526f, -2.46566057f, -0.32179555f, 1.69001770f, - -0.39678648f, -0.91400242f, 1.56746745f, 0.36029303f, -1.01637018f, -1.84069777f, 0.15860040f, 1.35965717f, - 0.16654867f, 3.63810396f, 2.03763342f, 0.64186901f, -1.02682137f, 2.18480039f, -2.17365599f, -0.56225222f, - -2.48764873f, 1.94031644f, -1.13630998f, -2.51891637f, -1.29985571f, 0.23808026f, 2.95523596f, 1.06378591f, - -0.20339361f, -0.56349581f, 1.46587682f, 4.12142849f, 0.78908098f, -0.24000889f, -1.15510166f, 0.42653239f, - -1.98345447f, 1.06918168f, 2.98073006f, -2.94872737f, -0.67443597f, -0.96227646f, -1.94805872f, -0.96003568f, - 1.06492281f, 0.32333452f, -0.52869648f, -1.25258100f, 0.75479198f, -1.04409528f, -1.81722605f, 0.99018478f, - 1.83352923f, 1.02711058f, 0.31064227f, 2.44383168f, -1.80332434f, 1.57207584f, -0.41058558f, 0.20494992f, - -0.78399467f, -0.35703743f, -0.67568171f, -1.30091023f, -0.17390330f, 0.22340816f, -0.44613233f, 1.23870432f, - -0.16092014f, -1.22258115f, 0.60575533f, -0.17969827f, 1.87851882f, 1.13991237f, -0.81591004f, -1.68899822f, - - -1.72543812f, 0.63848293f, 0.87042624f, 0.39726460f, 0.62647510f, 1.73326159f, -0.55110240f, -1.26900804f, - 1.94843686f, -1.73077893f, 2.53475809f, 2.79892564f, -1.91852188f, 0.99826050f, -3.04680610f, 1.38900220f, - -1.17920876f, -2.07508063f, -0.34274688f, -0.24780962f, 1.75715542f, 1.27657294f, -1.15560341f, -2.69310951f, - 0.93523502f, 0.58213681f, -2.57009196f, 2.56376076f, 0.06911665f, 1.73962176f, 0.43307841f, -1.18240118f, - 1.52338290f, 1.02856898f, 0.40946901f, 1.57649779f, 1.22447217f, 0.85961932f, 0.30765539f, -2.66427660f, - -1.55998194f, -0.31161505f, -1.63090813f, -1.62476087f, 1.28381526f, -0.77024549f, 1.46711981f, -0.71657622f, - -0.51606011f, 0.87953311f, 0.26169056f, 1.03068113f, 0.41064253f, -1.56344402f, -1.53443003f, -0.03009570f, - -0.02123317f, -1.74375248f, 1.60988081f, 1.74488568f, 0.59155780f, -0.62032932f, 0.03105794f, 4.54175377f, - -2.08403850f, 0.22352570f, -0.17924348f, 0.65815634f, -0.59089363f, -1.66189861f, 0.75618476f, 0.03879535f, - 1.50222909f, -0.29873836f, -1.76075482f, -2.97067928f, 0.28112072f, 0.72105575f, 0.06761266f, -1.61681306f, - -0.80693424f, 2.40102959f, -2.91352296f, -1.21352315f, -1.62430143f, -1.60909438f, 0.53140688f, -0.28235722f, - 0.63271880f, 1.33791542f, -1.37593675f, -1.60502291f, 1.27470064f, -0.96280038f, 0.79614848f, 0.31894624f}; - } - - { - data.value_data = { - 0.67641568f, -1.44437671f, 0.57255918f, 0.11087912f, 0.73787844f, -1.36586773f, - 1.45507979f, -3.70331645f, -0.85970032f, -2.14545083f, 2.11107802f, -0.16663373f, - 1.47033095f, 0.49124131f, 1.99316287f, -2.68613410f, 0.23831765f, 0.90826637f, - 0.72628385f, 1.29567933f, -0.07918698f, 0.13999116f, 1.22531521f, 0.06399018f, - -2.24613571f, -1.08365369f, -0.68457615f, -0.25960952f, -0.88386559f, 0.46391147f, - 1.24469304f, 1.13121903f, - -0.21484625f, 3.49263334f, -1.35283577f, 0.38428289f, -4.29686069f, -4.34778786f, - -0.49574745f, -0.08637778f, -0.50855160f, -1.12334609f, -1.44851387f, 3.36797357f, - -0.91776383f, -0.98647243f, 1.45408130f, 0.29062888f, 0.24470398f, -1.28129590f, - 0.47530234f, 2.19562674f, 0.62674099f, -2.56222868f, -1.42671025f, 1.51795268f, - -1.92045701f, 1.20271325f, 2.53190184f, -0.37211552f, 0.92569226f, -1.11019444f, - 1.15402830f, -1.98479640f, - -0.49658760f, 1.62168694f, -1.71412969f, -1.26646388f, -1.37257946f, 1.53828073f, - -0.35583261f, 0.03810386f, 0.43514529f, 0.97525519f, -2.22109556f, 1.17547810f, - -0.28825673f, 0.91509271f, -1.19243717f, 1.09280133f, -0.51078367f, 0.63577116f, - -0.62186599f, -2.80234575f, -1.58007598f, 1.06965756f, -0.89327252f, -0.84735525f, - -0.46283475f, 0.77867299f, -0.07434830f, 1.44711912f, 1.07089376f, 0.78913736f, - 0.59053934f, -0.32160193f, - - 0.51273453f, 1.12628150f, 1.96404183f, 0.26380035f, 3.41526699f, 1.08249199f, - -1.70347631f, 0.42854923f, -1.98269284f, 1.97382474f, -0.12164606f, -1.41219604f, - 0.01819625f, 0.73082930f, -2.60845804f, 1.47046185f, 0.26324001f, 1.54259276f, - -1.18744254f, -1.77539694f, 1.76547086f, -1.57072937f, -1.83995926f, -0.05529352f, - 1.83544660f, 0.69575423f, -0.03345531f, -1.69629955f, 0.04713173f, 1.39800107f, - 0.24362923f, 0.12432972f, - -2.92895460f, -0.46070760f, 0.20383459f, 1.93618548f, -1.08026588f, 1.08253515f, - -0.48318014f, -2.34334373f, -2.69622159f, 0.00661799f, -1.10738027f, 0.03181311f, - 0.32897863f, 1.89451993f, -0.01152946f, 0.17766151f, 2.46450090f, -0.64409554f, - 2.56058550f, 1.29339278f, 2.72114944f, 0.87801707f, -1.58970404f, 2.88365316f, - 0.46464550f, -1.71912467f, -1.90960062f, -3.13572145f, 0.19871379f, -0.28741950f, - -0.38167781f, -2.30705547f, - 0.64399612f, 0.32866889f, -3.49091625f, -0.02294427f, 1.60225844f, 1.83659923f, - 1.55193460f, -0.06712314f, 0.76592684f, 0.83479869f, 0.49627584f, 0.75736403f, - 0.75179487f, -0.32156041f, 1.36537170f, 0.57024354f, 0.36152276f, 0.93625057f, - -1.69728792f, -0.28833422f, 0.43304375f, 1.62640548f, -0.00187188f, 0.80429250f, - -0.77993584f, 1.37333393f, -1.16019452f, -0.91983509f, 0.20466281f, 1.09339333f, - -0.99191529f, 3.42685890f}; - } - - { - data.bias_data = { - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f - }; - } - - { - data.kv_data = { - 2.66554713f, 0.04116637f, -1.14599442f, -1.99071956f, 0.42523879f, 0.94212061f, - 1.15597987f, -1.76809072f, -1.89803648f, -0.74707657f, -0.71960962f, 0.67453432f, - 3.31946969f, 1.06201041f, 2.29824829f, 0.23788756f, 1.69329333f, 0.06745748f, - -1.34720469f, 1.81031406f, -0.33143526f, -2.46566057f, -0.32179555f, 1.69001770f, - -0.39678648f, -0.91400242f, 1.56746745f, 0.36029303f, -1.01637018f, -1.84069777f, - 0.15860040f, 1.35965717f, - 0.67641568f, -1.44437671f, 0.57255918f, 0.11087912f, 0.73787844f, -1.36586773f, - 1.45507979f, -3.70331645f, -0.85970032f, -2.14545083f, 2.11107802f, -0.16663373f, - 1.47033095f, 0.49124131f, 1.99316287f, -2.68613410f, 0.23831765f, 0.90826637f, - 0.72628385f, 1.29567933f, -0.07918698f, 0.13999116f, 1.22531521f, 0.06399018f, - -2.24613571f, -1.08365369f, -0.68457615f, -0.25960952f, -0.88386559f, 0.46391147f, - 1.24469304f, 1.13121903f, - - 0.16654867f, 3.63810396f, 2.03763342f, 0.64186901f, -1.02682137f, 2.18480039f, - -2.17365599f, -0.56225222f, -2.48764873f, 1.94031644f, -1.13630998f, -2.51891637f, - -1.29985571f, 0.23808026f, 2.95523596f, 1.06378591f, -0.20339361f, -0.56349581f, - 1.46587682f, 4.12142849f, 0.78908098f, -0.24000889f, -1.15510166f, 0.42653239f, - -1.98345447f, 1.06918168f, 2.98073006f, -2.94872737f, -0.67443597f, -0.96227646f, - -1.94805872f, -0.96003568f, - -0.21484625f, 3.49263334f, -1.35283577f, 0.38428289f, -4.29686069f, -4.34778786f, - -0.49574745f, -0.08637778f, -0.50855160f, -1.12334609f, -1.44851387f, 3.36797357f, - -0.91776383f, -0.98647243f, 1.45408130f, 0.29062888f, 0.24470398f, -1.28129590f, - 0.47530234f, 2.19562674f, 0.62674099f, -2.56222868f, -1.42671025f, 1.51795268f, - -1.92045701f, 1.20271325f, 2.53190184f, -0.37211552f, 0.92569226f, -1.11019444f, - 1.15402830f, -1.98479640f, - - 1.06492281f, 0.32333452f, -0.52869648f, -1.25258100f, 0.75479198f, -1.04409528f, - -1.81722605f, 0.99018478f, 1.83352923f, 1.02711058f, 0.31064227f, 2.44383168f, - -1.80332434f, 1.57207584f, -0.41058558f, 0.20494992f, -0.78399467f, -0.35703743f, - -0.67568171f, -1.30091023f, -0.17390330f, 0.22340816f, -0.44613233f, 1.23870432f, - -0.16092014f, -1.22258115f, 0.60575533f, -0.17969827f, 1.87851882f, 1.13991237f, - -0.81591004f, -1.68899822f, - -0.49658760f, 1.62168694f, -1.71412969f, -1.26646388f, -1.37257946f, 1.53828073f, - -0.35583261f, 0.03810386f, 0.43514529f, 0.97525519f, -2.22109556f, 1.17547810f, - -0.28825673f, 0.91509271f, -1.19243717f, 1.09280133f, -0.51078367f, 0.63577116f, - -0.62186599f, -2.80234575f, -1.58007598f, 1.06965756f, -0.89327252f, -0.84735525f, - -0.46283475f, 0.77867299f, -0.07434830f, 1.44711912f, 1.07089376f, 0.78913736f, - 0.59053934f, -0.32160193f, - - -1.72543812f, 0.63848293f, 0.87042624f, 0.39726460f, 0.62647510f, 1.73326159f, - -0.55110240f, -1.26900804f, 1.94843686f, -1.73077893f, 2.53475809f, 2.79892564f, - -1.91852188f, 0.99826050f, -3.04680610f, 1.38900220f, -1.17920876f, -2.07508063f, - -0.34274688f, -0.24780962f, 1.75715542f, 1.27657294f, -1.15560341f, -2.69310951f, - 0.93523502f, 0.58213681f, -2.57009196f, 2.56376076f, 0.06911665f, 1.73962176f, - 0.43307841f, -1.18240118f, - 0.51273453f, 1.12628150f, 1.96404183f, 0.26380035f, 3.41526699f, 1.08249199f, - -1.70347631f, 0.42854923f, -1.98269284f, 1.97382474f, -0.12164606f, -1.41219604f, - 0.01819625f, 0.73082930f, -2.60845804f, 1.47046185f, 0.26324001f, 1.54259276f, - -1.18744254f, -1.77539694f, 1.76547086f, -1.57072937f, -1.83995926f, -0.05529352f, - 1.83544660f, 0.69575423f, -0.03345531f, -1.69629955f, 0.04713173f, 1.39800107f, - 0.24362923f, 0.12432972f, - - 1.52338290f, 1.02856898f, 0.40946901f, 1.57649779f, 1.22447217f, 0.85961932f, - 0.30765539f, -2.66427660f, -1.55998194f, -0.31161505f, -1.63090813f, -1.62476087f, - 1.28381526f, -0.77024549f, 1.46711981f, -0.71657622f, -0.51606011f, 0.87953311f, - 0.26169056f, 1.03068113f, 0.41064253f, -1.56344402f, -1.53443003f, -0.03009570f, - -0.02123317f, -1.74375248f, 1.60988081f, 1.74488568f, 0.59155780f, -0.62032932f, - 0.03105794f, 4.54175377f, - -2.92895460f, -0.46070760f, 0.20383459f, 1.93618548f, -1.08026588f, 1.08253515f, - -0.48318014f, -2.34334373f, -2.69622159f, 0.00661799f, -1.10738027f, 0.03181311f, - 0.32897863f, 1.89451993f, -0.01152946f, 0.17766151f, 2.46450090f, -0.64409554f, - 2.56058550f, 1.29339278f, 2.72114944f, 0.87801707f, -1.58970404f, 2.88365316f, - 0.46464550f, -1.71912467f, -1.90960062f, -3.13572145f, 0.19871379f, -0.28741950f, - -0.38167781f, -2.30705547f, - - -2.08403850f, 0.22352570f, -0.17924348f, 0.65815634f, -0.59089363f, -1.66189861f, - 0.75618476f, 0.03879535f, 1.50222909f, -0.29873836f, -1.76075482f, -2.97067928f, - 0.28112072f, 0.72105575f, 0.06761266f, -1.61681306f, -0.80693424f, 2.40102959f, - -2.91352296f, -1.21352315f, -1.62430143f, -1.60909438f, 0.53140688f, -0.28235722f, - 0.63271880f, 1.33791542f, -1.37593675f, -1.60502291f, 1.27470064f, -0.96280038f, - 0.79614848f, 0.31894624f, - 0.64399612f, 0.32866889f, -3.49091625f, -0.02294427f, 1.60225844f, 1.83659923f, - 1.55193460f, -0.06712314f, 0.76592684f, 0.83479869f, 0.49627584f, 0.75736403f, - 0.75179487f, -0.32156041f, 1.36537170f, 0.57024354f, 0.36152276f, 0.93625057f, - -1.69728792f, -0.28833422f, 0.43304375f, 1.62640548f, -0.00187188f, 0.80429250f, - -0.77993584f, 1.37333393f, -1.16019452f, -0.91983509f, 0.20466281f, 1.09339333f, - -0.99191529f, 3.42685890f}; - } - - { - // Do not test fp32 - data.fp32_output_data = {}; - } - - { - data.fp16_output_data = { - -0.18665725f, 1.53655565f, -1.16219902f, -0.53553712f, -1.76899862f, -0.67172408f, - -0.03719823f, -0.73519617f, -0.08289805f, -0.22439885f, -1.15095568f, 1.52012229f, - -0.11608444f, 0.30267856f, 0.17237782f, 0.12366229f, -0.15282108f, 0.15652999f, - -0.05062571f, -0.60356319f, -0.67014134f, -0.12373877f, -0.62331146f, -0.00974876f, - -1.22021353f, 0.52888882f, 0.52984023f, 0.60431194f, 0.64458221f, 0.19681633f, - 0.87637067f, -0.49721599f, - - -0.21368809f, 3.48006248f, -1.34989023f, 0.38081154f, -4.28221798f, -4.33166409f, - -0.49185523f, -0.09290559f, -0.50751436f, -1.12148952f, -1.44325578f, 3.35744357f, - -0.91217732f, -0.98030341f, 1.45034039f, 0.28651160f, 0.24333692f, -1.27377033f, - 0.47380278f, 2.18498206f, 0.62146491f, -2.55067039f, -1.42080343f, 1.51099622f, - -1.91845036f, 1.19768524f, 2.52122355f, -0.36864227f, 0.92257524f, -1.10384953f, - 1.15318692f, -1.97599709f, - - 0.25325853f, 0.99478984f, 1.75511229f, 0.38680723f, 3.04894686f, 1.09290445f, - -1.56589723f, 0.21126932f, -1.99892235f, 1.80875492f, -0.18795207f, -1.27262163f, - 0.05191655f, 0.80464834f, -2.35645056f, 1.35988820f, 0.43171301f, 1.36821294f, - -0.90993541f, -1.52189243f, 1.81963241f, -1.34069264f, -1.79558825f, 0.17969209f, - 1.69527614f, 0.52177316f, -0.19144230f, -1.79486036f, 0.06081408f, 1.26584184f, - 0.17910211f, -0.01467115f, - - 0.15915775f, 0.23589413f, -2.89726520f, 0.24662971f, 1.27141249f, 1.72167253f, - 1.22059381f, -0.36594886f, 0.25064397f, 0.74270636f, 0.26896626f, 0.62173104f, - 0.68196213f, -0.00399938f, 1.11046481f, 0.53283978f, 0.64384484f, 0.73332942f, - -1.11337614f, -0.10050645f, 0.76519096f, 1.46986043f, -0.24821334f, 1.07021677f, - -0.56646812f, 0.94391233f, -1.24186087f, -1.23258281f, 0.20112629f, 0.91218621f, - -0.88806105f, 2.59514260f}; - } + LoadTensor("CrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV.query_data", data.query_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV.key_data", data.key_data); + LoadTensor("CrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV.value_data", data.value_data); + data.bias_data = {}; + LoadTensor("CrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV.kv_data", data.kv_data); + // Do not test fp32 + data.fp32_output_data = {}; + LoadTensor("CrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV.fp16_output_data", data.fp16_output_data); } void GetSelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV(AttentionTestData& data) { @@ -2645,313 +188,15 @@ void GetSelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV(AttentionTes AttentionKernelType::AttentionKernel_Unfused, AttentionKernelType::AttentionKernel_TrtFusedCrossAttention}; - { - data.query_data = { - -0.35420692f, 1.31206024f, -2.80201197f, 2.42258096f, -0.86031514f, -1.44535458f, -0.10832444f, -2.00132895f, - 1.62475216f, 0.10978927f, 1.84596729f, 0.48908550f, 1.44369888f, 0.87542874f, -1.16434252f, 0.52133209f, - 1.54848897f, -2.21174526f, -0.28574878f, 0.70815033f, 1.18327498f, 3.14097571f, -0.25795099f, 1.89341247f, - -0.11603792f, 0.38110194f, 0.40873206f, -1.14149106f, 0.79770875f, -0.98069525f, -1.53588808f, 0.50821728f, - - -2.21641898f, 0.55090773f, 0.80901796f, -0.56089771f, 0.03574468f, -1.27940118f, -0.02213959f, -0.80698186f, - -0.82701880f, 1.72937381f, 1.56083691f, -0.30311784f, -0.25183848f, 0.24280515f, 0.29569417f, -0.31162494f, - 0.48996922f, 0.22795241f, 2.07125854f, 1.45823467f, 3.03750706f, 1.53734803f, 0.48668906f, -1.63703632f, - -0.14114749f, 1.85963213f, 1.20729232f, -0.28972962f, -0.80783498f, -1.16619551f, -0.60004634f, 0.02498829f, - - 3.50846076f, -2.50027657f, -2.59866142f, 1.58495271f, 2.21110034f, -2.74877763f, -1.00267041f, 0.62646407f, - 2.50227380f, -0.27291518f, -0.33037442f, 0.75840306f, 0.45437157f, -0.79876304f, 0.83509272f, 2.53716302f, - 0.01348384f, -2.16307616f, 2.01661849f, 2.10746121f, -1.70485222f, 1.35548759f, 1.39401650f, -0.99451691f, - -4.13484812f, 0.56262714f, -0.92725742f, -0.16389316f, -1.31260049f, 2.32357836f, -3.05251694f, -1.12570131f, - - 1.87849474f, -1.80381167f, 0.52235699f, 2.38887334f, -1.58878529f, 0.69571090f, 1.65044296f, -0.27024290f, - 3.59580970f, -1.97888982f, 1.17034674f, 0.26716161f, -1.16770899f, 0.74609619f, 0.78886843f, 0.15717520f, - -0.93303132f, -0.84753871f, -4.32799959f, -1.94716609f, -1.16980326f, 1.62631667f, 2.41053247f, 3.78186774f, - 0.26432252f, -0.40396988f, 2.04414082f, 0.65150046f, 0.47777444f, -2.57569051f, 0.99004912f, 2.47947693f}; - } - { - data.key_data = { - -0.04407793f, 1.29459429f, 1.05810797f, 1.92067695f, -0.65047157f, 0.99029726f, -1.69796586f, 1.15320420f, - -1.66444266f, 1.78305888f, 1.20582056f, 1.69975281f, 0.34572244f, -0.60833001f, 2.59864879f, -1.05330181f, - -1.16554165f, -0.03781542f, -1.13475525f, 0.71595150f, -0.91169560f, 1.26686060f, 1.60492957f, -0.53510487f, - -1.40180850f, 1.83253956f, 2.70238972f, -1.48750985f, 0.47105616f, -0.79477602f, -1.93152475f, 1.04042351f, - - 1.21863425f, 1.20610654f, 0.69031805f, 2.60092020f, 1.43040228f, 0.60616529f, 0.47948456f, -1.15139377f, - 0.15641990f, -0.46933329f, 0.64774191f, 0.35970241f, -1.00424135f, 0.01247875f, 1.00281739f, -1.10514688f, - 0.30922988f, -0.82255656f, -1.23242986f, 0.90557313f, -0.38946581f, -0.21124774f, -2.37903309f, -1.42169905f, - -0.05935127f, 0.47488672f, -0.37083727f, 1.31585515f, -0.21577421f, -0.97746384f, -0.13380399f, 1.77390409f, - - -2.65206385f, 1.26134932f, -1.01682174f, 0.64366758f, 0.95474619f, 2.06720352f, 0.51750720f, -0.07041813f, - 0.53124994f, -3.26612782f, 1.37013340f, 0.13939659f, -0.57418114f, 0.80680281f, -3.40751696f, -0.15847699f, - 0.97837782f, -0.09121911f, 1.18452120f, 0.52711177f, -1.86135840f, -0.11258313f, 0.85863215f, -2.60261130f, - 0.72695309f, 1.44092011f, 0.43785980f, -1.63415265f, -1.05772328f, 0.12997569f, 0.07356137f, -0.62493324f, - - -0.43267637f, -1.80009198f, 0.92961007f, 2.05127883f, -2.85521173f, -0.21652693f, -0.89153922f, 0.15524670f, - -2.16850328f, 1.46751809f, 2.51663852f, -0.49499366f, 0.19886012f, 0.77093124f, -1.14819765f, 1.47111738f, - 2.42824388f, 1.56369960f, 1.69934130f, -0.42460468f, -2.25951004f, -1.18074155f, 3.51091242f, -0.30183151f, - -1.83517075f, -0.56233191f, 2.35561657f, -3.63751698f, -3.20001125f, -1.66120780f, 3.23455381f, -1.86251283f}; - } - - { - data.value_data = { - -0.89167893f, 0.02633595f, -0.84866279f, 1.43489110f, -2.91941142f, -0.20650116f, 1.85965109f, 0.45669034f, - 0.07678832f, 0.04492294f, 0.67326981f, 0.97103029f, 1.53470886f, -1.10242307f, 0.86584085f, -0.34770033f, - -1.24311507f, -1.80293822f, -1.01317739f, -0.71518499f, 0.77814674f, -0.59236068f, -2.00310278f, 3.13277125f, - -1.20754123f, 2.01506066f, 0.82650810f, 2.06084490f, -0.46267471f, 1.56365979f, 4.31514502f, -1.03099275f, - - -1.85462761f, 2.10100341f, 1.79686451f, 0.23871201f, 1.23598254f, -0.31959364f, 0.50101948f, -0.09527110f, - -1.02331078f, 0.16319990f, -0.54766160f, 0.41597658f, -0.52141404f, 1.71663237f, -0.00776333f, -0.68160462f, - 1.76272714f, -0.04465733f, 0.28247434f, 1.69360149f, 0.14144623f, 0.75038731f, -1.33337545f, 2.23457718f, - -0.07649468f, 1.97064841f, -1.85374629f, -1.59334683f, 0.32698441f, -0.16024286f, 2.02828407f, -0.96440399f, - - -2.11639142f, -1.50897706f, 1.63863683f, 2.32786226f, 1.32746494f, 0.75751448f, 0.57184196f, 0.86446053f, - -0.62406683f, 0.78861046f, 0.01044065f, 3.51772785f, -1.33701336f, 0.27977663f, -0.35464612f, 0.74973166f, - 0.03352100f, 1.55007398f, 0.69849420f, -2.47725606f, -1.89363778f, -1.79874682f, -0.56210291f, -1.75556040f, - 1.07565808f, -0.18023658f, 1.63777173f, 1.28198206f, 2.19431949f, 0.67998970f, -0.52531999f, -1.89906740f, - - 1.35158050f, -2.21481490f, -0.11812399f, -1.74263430f, -0.57895988f, -0.04181165f, 0.78120053f, -2.22377038f, - -0.53264999f, -2.03721714f, 0.21023634f, 2.55751204f, -1.04522800f, 0.85386503f, 0.41594937f, -2.98181081f, - 1.14034331f, -1.41539204f, 0.13379651f, 3.47018123f, 1.53924727f, 1.50004411f, 2.87318921f, 1.62624204f, - 0.64942807f, -4.54302311f, -1.50294220f, -1.75212634f, 0.27900690f, -3.05124855f, 3.30960631f, -0.07991691f}; - } - - { - data.bias_data = { - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, - // 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f - }; - } - - { - data.qkv_data = { - -0.35420692f, 1.31206024f, -2.80201197f, 2.42258096f, -0.86031514f, -1.44535458f, -0.10832444f, -2.00132895f, - 1.62475216f, 0.10978927f, 1.84596729f, 0.48908550f, 1.44369888f, 0.87542874f, -1.16434252f, 0.52133209f, - 1.54848897f, -2.21174526f, -0.28574878f, 0.70815033f, 1.18327498f, 3.14097571f, -0.25795099f, 1.89341247f, - -0.11603792f, 0.38110194f, 0.40873206f, -1.14149106f, 0.79770875f, -0.98069525f, -1.53588808f, 0.50821728f, - -0.04407793f, 1.29459429f, 1.05810797f, 1.92067695f, -0.65047157f, 0.99029726f, -1.69796586f, 1.15320420f, - -1.66444266f, 1.78305888f, 1.20582056f, 1.69975281f, 0.34572244f, -0.60833001f, 2.59864879f, -1.05330181f, - -1.16554165f, -0.03781542f, -1.13475525f, 0.71595150f, -0.91169560f, 1.26686060f, 1.60492957f, -0.53510487f, - -1.40180850f, 1.83253956f, 2.70238972f, -1.48750985f, 0.47105616f, -0.79477602f, -1.93152475f, 1.04042351f, - -0.89167893f, 0.02633595f, -0.84866279f, 1.43489110f, -2.91941142f, -0.20650116f, 1.85965109f, 0.45669034f, - 0.07678832f, 0.04492294f, 0.67326981f, 0.97103029f, 1.53470886f, -1.10242307f, 0.86584085f, -0.34770033f, - -1.24311507f, -1.80293822f, -1.01317739f, -0.71518499f, 0.77814674f, -0.59236068f, -2.00310278f, 3.13277125f, - -1.20754123f, 2.01506066f, 0.82650810f, 2.06084490f, -0.46267471f, 1.56365979f, 4.31514502f, -1.03099275f, - - -2.21641898f, 0.55090773f, 0.80901796f, -0.56089771f, 0.03574468f, -1.27940118f, -0.02213959f, -0.80698186f, - -0.82701880f, 1.72937381f, 1.56083691f, -0.30311784f, -0.25183848f, 0.24280515f, 0.29569417f, -0.31162494f, - 0.48996922f, 0.22795241f, 2.07125854f, 1.45823467f, 3.03750706f, 1.53734803f, 0.48668906f, -1.63703632f, - -0.14114749f, 1.85963213f, 1.20729232f, -0.28972962f, -0.80783498f, -1.16619551f, -0.60004634f, 0.02498829f, - 1.21863425f, 1.20610654f, 0.69031805f, 2.60092020f, 1.43040228f, 0.60616529f, 0.47948456f, -1.15139377f, - 0.15641990f, -0.46933329f, 0.64774191f, 0.35970241f, -1.00424135f, 0.01247875f, 1.00281739f, -1.10514688f, - 0.30922988f, -0.82255656f, -1.23242986f, 0.90557313f, -0.38946581f, -0.21124774f, -2.37903309f, -1.42169905f, - -0.05935127f, 0.47488672f, -0.37083727f, 1.31585515f, -0.21577421f, -0.97746384f, -0.13380399f, 1.77390409f, - -1.85462761f, 2.10100341f, 1.79686451f, 0.23871201f, 1.23598254f, -0.31959364f, 0.50101948f, -0.09527110f, - -1.02331078f, 0.16319990f, -0.54766160f, 0.41597658f, -0.52141404f, 1.71663237f, -0.00776333f, -0.68160462f, - 1.76272714f, -0.04465733f, 0.28247434f, 1.69360149f, 0.14144623f, 0.75038731f, -1.33337545f, 2.23457718f, - -0.07649468f, 1.97064841f, -1.85374629f, -1.59334683f, 0.32698441f, -0.16024286f, 2.02828407f, -0.96440399f, - - 3.50846076f, -2.50027657f, -2.59866142f, 1.58495271f, 2.21110034f, -2.74877763f, -1.00267041f, 0.62646407f, - 2.50227380f, -0.27291518f, -0.33037442f, 0.75840306f, 0.45437157f, -0.79876304f, 0.83509272f, 2.53716302f, - 0.01348384f, -2.16307616f, 2.01661849f, 2.10746121f, -1.70485222f, 1.35548759f, 1.39401650f, -0.99451691f, - -4.13484812f, 0.56262714f, -0.92725742f, -0.16389316f, -1.31260049f, 2.32357836f, -3.05251694f, -1.12570131f, - -2.65206385f, 1.26134932f, -1.01682174f, 0.64366758f, 0.95474619f, 2.06720352f, 0.51750720f, -0.07041813f, - 0.53124994f, -3.26612782f, 1.37013340f, 0.13939659f, -0.57418114f, 0.80680281f, -3.40751696f, -0.15847699f, - 0.97837782f, -0.09121911f, 1.18452120f, 0.52711177f, -1.86135840f, -0.11258313f, 0.85863215f, -2.60261130f, - 0.72695309f, 1.44092011f, 0.43785980f, -1.63415265f, -1.05772328f, 0.12997569f, 0.07356137f, -0.62493324f, - -2.11639142f, -1.50897706f, 1.63863683f, 2.32786226f, 1.32746494f, 0.75751448f, 0.57184196f, 0.86446053f, - -0.62406683f, 0.78861046f, 0.01044065f, 3.51772785f, -1.33701336f, 0.27977663f, -0.35464612f, 0.74973166f, - 0.03352100f, 1.55007398f, 0.69849420f, -2.47725606f, -1.89363778f, -1.79874682f, -0.56210291f, -1.75556040f, - 1.07565808f, -0.18023658f, 1.63777173f, 1.28198206f, 2.19431949f, 0.67998970f, -0.52531999f, -1.89906740f, - - 1.87849474f, -1.80381167f, 0.52235699f, 2.38887334f, -1.58878529f, 0.69571090f, 1.65044296f, -0.27024290f, - 3.59580970f, -1.97888982f, 1.17034674f, 0.26716161f, -1.16770899f, 0.74609619f, 0.78886843f, 0.15717520f, - -0.93303132f, -0.84753871f, -4.32799959f, -1.94716609f, -1.16980326f, 1.62631667f, 2.41053247f, 3.78186774f, - 0.26432252f, -0.40396988f, 2.04414082f, 0.65150046f, 0.47777444f, -2.57569051f, 0.99004912f, 2.47947693f, - -0.43267637f, -1.80009198f, 0.92961007f, 2.05127883f, -2.85521173f, -0.21652693f, -0.89153922f, 0.15524670f, - -2.16850328f, 1.46751809f, 2.51663852f, -0.49499366f, 0.19886012f, 0.77093124f, -1.14819765f, 1.47111738f, - 2.42824388f, 1.56369960f, 1.69934130f, -0.42460468f, -2.25951004f, -1.18074155f, 3.51091242f, -0.30183151f, - -1.83517075f, -0.56233191f, 2.35561657f, -3.63751698f, -3.20001125f, -1.66120780f, 3.23455381f, -1.86251283f, - 1.35158050f, -2.21481490f, -0.11812399f, -1.74263430f, -0.57895988f, -0.04181165f, 0.78120053f, -2.22377038f, - -0.53264999f, -2.03721714f, 0.21023634f, 2.55751204f, -1.04522800f, 0.85386503f, 0.41594937f, -2.98181081f, - 1.14034331f, -1.41539204f, 0.13379651f, 3.47018123f, 1.53924727f, 1.50004411f, 2.87318921f, 1.62624204f, - 0.64942807f, -4.54302311f, -1.50294220f, -1.75212634f, 0.27900690f, -3.05124855f, 3.30960631f, -0.07991691f}; - } - - { - // Do not test fp32 - data.fp32_output_data = {}; - } - - { - data.fp16_output_data = { - -1.30247164f, 0.91138631f, 0.27991560f, 0.92460269f, -1.14672589f, -0.25474626f, - 1.28006065f, 0.22122431f, -0.39251250f, 0.09537974f, 0.15242209f, 0.73424512f, - 0.65756959f, 0.10018224f, 0.49316248f, -0.49014348f, 0.03917319f, -1.05285788f, - -0.46045411f, 0.31240013f, 0.50653118f, -0.01954618f, -1.71739793f, 2.74960279f, - -0.72503829f, 1.99611449f, -0.31688485f, 0.50197154f, -0.12580720f, 0.82824522f, - 3.33957314f, -1.00258613f, - - -0.95444643f, 0.16156809f, -0.67622054f, 1.35692120f, -2.64855242f, -0.21387282f, - 1.77109206f, 0.42071211f, 0.00508105f, 0.05263254f, 0.59368640f, 0.93485051f, - 1.40068567f, -0.91866994f, 0.80889714f, -0.36946508f, -1.04718661f, -1.68832910f, - -0.92872351f, -0.55817413f, 0.73664504f, -0.50483698f, -1.95944834f, 3.07422471f, - -1.13381684f, 2.01216578f, 0.65180230f, 1.82265544f, -0.41120273f, 1.45129156f, - 4.16608191f, -1.02665234f, - - 0.21158576f, -1.98279130f, 0.45935997f, -0.40457720f, 0.04772174f, 0.22094353f, - 0.71238005f, -1.20860445f, -0.56270063f, -1.10830855f, 0.14455934f, 2.87315512f, - -1.14114404f, 0.66515017f, 0.16263856f, -1.75517499f, 0.77650774f, -0.44058144f, - 0.31942442f, 1.51513433f, 0.41078627f, 0.41566271f, 1.74393702f, 0.51457298f, - 0.78953874f, -3.10888410f, -0.47052401f, -0.75475156f, 0.90861011f, -1.82471263f, - 2.04898596f, -0.67790967f, - - 1.17194295f, -2.17825341f, -0.02712549f, -1.53178656f, -0.48020893f, -0.00040733f, - 0.77035600f, -2.06380320f, -0.53738528f, -1.89084208f, 0.19988713f, 2.60725045f, - -1.06034219f, 0.82412785f, 0.37603328f, -2.78852081f, 1.08301103f, -1.26178384f, - 0.16304730f, 3.16210985f, 1.36142719f, 1.32916999f, 2.69524455f, 1.45106804f, - 0.67150640f, -4.31703520f, -1.34025633f, -1.59496248f, 0.37821823f, -2.85797405f, - 3.11096096f, -0.17414713f}; - } -} - -void GetPackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias(PackedAttentionTestData& data) { - data.hidden_size = 32; - data.v_hidden_size = 32; - data.num_heads = 1; - data.batch_size = 2; - data.sequence_length = 2; - data.kv_sequence_length = 2; - - data.token_offset = {0, 2, 3, 1}; - data.cumulative_sequence_length = {0, 1, 3}; - data.token_count = 3; - - data.skip_kernel_types = { - AttentionKernelType::AttentionKernel_TrtFusedCrossAttention}; - - { - data.query_data = { - -0.35420692f, 1.31206024f, -2.80201197f, 2.42258096f, -0.86031514f, -1.44535458f, -0.10832444f, -2.00132895f, - 1.62475216f, 0.10978927f, 1.84596729f, 0.48908550f, 1.44369888f, 0.87542874f, -1.16434252f, 0.52133209f, - 1.54848897f, -2.21174526f, -0.28574878f, 0.70815033f, 1.18327498f, 3.14097571f, -0.25795099f, 1.89341247f, - -0.11603792f, 0.38110194f, 0.40873206f, -1.14149106f, 0.79770875f, -0.98069525f, -1.53588808f, 0.50821728f, - - 3.50846076f, -2.50027657f, -2.59866142f, 1.58495271f, 2.21110034f, -2.74877763f, -1.00267041f, 0.62646407f, - 2.50227380f, -0.27291518f, -0.33037442f, 0.75840306f, 0.45437157f, -0.79876304f, 0.83509272f, 2.53716302f, - 0.01348384f, -2.16307616f, 2.01661849f, 2.10746121f, -1.70485222f, 1.35548759f, 1.39401650f, -0.99451691f, - -4.13484812f, 0.56262714f, -0.92725742f, -0.16389316f, -1.31260049f, 2.32357836f, -3.05251694f, -1.12570131f, - - 1.87849474f, -1.80381167f, 0.52235699f, 2.38887334f, -1.58878529f, 0.69571090f, 1.65044296f, -0.27024290f, - 3.59580970f, -1.97888982f, 1.17034674f, 0.26716161f, -1.16770899f, 0.74609619f, 0.78886843f, 0.15717520f, - -0.93303132f, -0.84753871f, -4.32799959f, -1.94716609f, -1.16980326f, 1.62631667f, 2.41053247f, 3.78186774f, - 0.26432252f, -0.40396988f, 2.04414082f, 0.65150046f, 0.47777444f, -2.57569051f, 0.99004912f, 2.47947693f}; - } - { - data.key_data = { - -0.04407793f, 1.29459429f, 1.05810797f, 1.92067695f, -0.65047157f, 0.99029726f, -1.69796586f, 1.15320420f, - -1.66444266f, 1.78305888f, 1.20582056f, 1.69975281f, 0.34572244f, -0.60833001f, 2.59864879f, -1.05330181f, - -1.16554165f, -0.03781542f, -1.13475525f, 0.71595150f, -0.91169560f, 1.26686060f, 1.60492957f, -0.53510487f, - -1.40180850f, 1.83253956f, 2.70238972f, -1.48750985f, 0.47105616f, -0.79477602f, -1.93152475f, 1.04042351f, - - -2.65206385f, 1.26134932f, -1.01682174f, 0.64366758f, 0.95474619f, 2.06720352f, 0.51750720f, -0.07041813f, - 0.53124994f, -3.26612782f, 1.37013340f, 0.13939659f, -0.57418114f, 0.80680281f, -3.40751696f, -0.15847699f, - 0.97837782f, -0.09121911f, 1.18452120f, 0.52711177f, -1.86135840f, -0.11258313f, 0.85863215f, -2.60261130f, - 0.72695309f, 1.44092011f, 0.43785980f, -1.63415265f, -1.05772328f, 0.12997569f, 0.07356137f, -0.62493324f, - - -0.43267637f, -1.80009198f, 0.92961007f, 2.05127883f, -2.85521173f, -0.21652693f, -0.89153922f, 0.15524670f, - -2.16850328f, 1.46751809f, 2.51663852f, -0.49499366f, 0.19886012f, 0.77093124f, -1.14819765f, 1.47111738f, - 2.42824388f, 1.56369960f, 1.69934130f, -0.42460468f, -2.25951004f, -1.18074155f, 3.51091242f, -0.30183151f, - -1.83517075f, -0.56233191f, 2.35561657f, -3.63751698f, -3.20001125f, -1.66120780f, 3.23455381f, -1.86251283f}; - } - - { - data.value_data = { - -0.89167893f, 0.02633595f, -0.84866279f, 1.43489110f, -2.91941142f, -0.20650116f, 1.85965109f, 0.45669034f, - 0.07678832f, 0.04492294f, 0.67326981f, 0.97103029f, 1.53470886f, -1.10242307f, 0.86584085f, -0.34770033f, - -1.24311507f, -1.80293822f, -1.01317739f, -0.71518499f, 0.77814674f, -0.59236068f, -2.00310278f, 3.13277125f, - -1.20754123f, 2.01506066f, 0.82650810f, 2.06084490f, -0.46267471f, 1.56365979f, 4.31514502f, -1.03099275f, - - -2.11639142f, -1.50897706f, 1.63863683f, 2.32786226f, 1.32746494f, 0.75751448f, 0.57184196f, 0.86446053f, - -0.62406683f, 0.78861046f, 0.01044065f, 3.51772785f, -1.33701336f, 0.27977663f, -0.35464612f, 0.74973166f, - 0.03352100f, 1.55007398f, 0.69849420f, -2.47725606f, -1.89363778f, -1.79874682f, -0.56210291f, -1.75556040f, - 1.07565808f, -0.18023658f, 1.63777173f, 1.28198206f, 2.19431949f, 0.67998970f, -0.52531999f, -1.89906740f, - - 1.35158050f, -2.21481490f, -0.11812399f, -1.74263430f, -0.57895988f, -0.04181165f, 0.78120053f, -2.22377038f, - -0.53264999f, -2.03721714f, 0.21023634f, 2.55751204f, -1.04522800f, 0.85386503f, 0.41594937f, -2.98181081f, - 1.14034331f, -1.41539204f, 0.13379651f, 3.47018123f, 1.53924727f, 1.50004411f, 2.87318921f, 1.62624204f, - 0.64942807f, -4.54302311f, -1.50294220f, -1.75212634f, 0.27900690f, -3.05124855f, 3.30960631f, -0.07991691f}; - } - - { - data.bias_data = {}; - } - - { - data.qkv_data = { - -0.35420692f, 1.31206024f, -2.80201197f, 2.42258096f, -0.86031514f, -1.44535458f, -0.10832444f, -2.00132895f, - 1.62475216f, 0.10978927f, 1.84596729f, 0.48908550f, 1.44369888f, 0.87542874f, -1.16434252f, 0.52133209f, - 1.54848897f, -2.21174526f, -0.28574878f, 0.70815033f, 1.18327498f, 3.14097571f, -0.25795099f, 1.89341247f, - -0.11603792f, 0.38110194f, 0.40873206f, -1.14149106f, 0.79770875f, -0.98069525f, -1.53588808f, 0.50821728f, - -0.04407793f, 1.29459429f, 1.05810797f, 1.92067695f, -0.65047157f, 0.99029726f, -1.69796586f, 1.15320420f, - -1.66444266f, 1.78305888f, 1.20582056f, 1.69975281f, 0.34572244f, -0.60833001f, 2.59864879f, -1.05330181f, - -1.16554165f, -0.03781542f, -1.13475525f, 0.71595150f, -0.91169560f, 1.26686060f, 1.60492957f, -0.53510487f, - -1.40180850f, 1.83253956f, 2.70238972f, -1.48750985f, 0.47105616f, -0.79477602f, -1.93152475f, 1.04042351f, - -0.89167893f, 0.02633595f, -0.84866279f, 1.43489110f, -2.91941142f, -0.20650116f, 1.85965109f, 0.45669034f, - 0.07678832f, 0.04492294f, 0.67326981f, 0.97103029f, 1.53470886f, -1.10242307f, 0.86584085f, -0.34770033f, - -1.24311507f, -1.80293822f, -1.01317739f, -0.71518499f, 0.77814674f, -0.59236068f, -2.00310278f, 3.13277125f, - -1.20754123f, 2.01506066f, 0.82650810f, 2.06084490f, -0.46267471f, 1.56365979f, 4.31514502f, -1.03099275f, - - 3.50846076f, -2.50027657f, -2.59866142f, 1.58495271f, 2.21110034f, -2.74877763f, -1.00267041f, 0.62646407f, - 2.50227380f, -0.27291518f, -0.33037442f, 0.75840306f, 0.45437157f, -0.79876304f, 0.83509272f, 2.53716302f, - 0.01348384f, -2.16307616f, 2.01661849f, 2.10746121f, -1.70485222f, 1.35548759f, 1.39401650f, -0.99451691f, - -4.13484812f, 0.56262714f, -0.92725742f, -0.16389316f, -1.31260049f, 2.32357836f, -3.05251694f, -1.12570131f, - -2.65206385f, 1.26134932f, -1.01682174f, 0.64366758f, 0.95474619f, 2.06720352f, 0.51750720f, -0.07041813f, - 0.53124994f, -3.26612782f, 1.37013340f, 0.13939659f, -0.57418114f, 0.80680281f, -3.40751696f, -0.15847699f, - 0.97837782f, -0.09121911f, 1.18452120f, 0.52711177f, -1.86135840f, -0.11258313f, 0.85863215f, -2.60261130f, - 0.72695309f, 1.44092011f, 0.43785980f, -1.63415265f, -1.05772328f, 0.12997569f, 0.07356137f, -0.62493324f, - -2.11639142f, -1.50897706f, 1.63863683f, 2.32786226f, 1.32746494f, 0.75751448f, 0.57184196f, 0.86446053f, - -0.62406683f, 0.78861046f, 0.01044065f, 3.51772785f, -1.33701336f, 0.27977663f, -0.35464612f, 0.74973166f, - 0.03352100f, 1.55007398f, 0.69849420f, -2.47725606f, -1.89363778f, -1.79874682f, -0.56210291f, -1.75556040f, - 1.07565808f, -0.18023658f, 1.63777173f, 1.28198206f, 2.19431949f, 0.67998970f, -0.52531999f, -1.89906740f, - - 1.87849474f, -1.80381167f, 0.52235699f, 2.38887334f, -1.58878529f, 0.69571090f, 1.65044296f, -0.27024290f, - 3.59580970f, -1.97888982f, 1.17034674f, 0.26716161f, -1.16770899f, 0.74609619f, 0.78886843f, 0.15717520f, - -0.93303132f, -0.84753871f, -4.32799959f, -1.94716609f, -1.16980326f, 1.62631667f, 2.41053247f, 3.78186774f, - 0.26432252f, -0.40396988f, 2.04414082f, 0.65150046f, 0.47777444f, -2.57569051f, 0.99004912f, 2.47947693f, - -0.43267637f, -1.80009198f, 0.92961007f, 2.05127883f, -2.85521173f, -0.21652693f, -0.89153922f, 0.15524670f, - -2.16850328f, 1.46751809f, 2.51663852f, -0.49499366f, 0.19886012f, 0.77093124f, -1.14819765f, 1.47111738f, - 2.42824388f, 1.56369960f, 1.69934130f, -0.42460468f, -2.25951004f, -1.18074155f, 3.51091242f, -0.30183151f, - -1.83517075f, -0.56233191f, 2.35561657f, -3.63751698f, -3.20001125f, -1.66120780f, 3.23455381f, -1.86251283f, - 1.35158050f, -2.21481490f, -0.11812399f, -1.74263430f, -0.57895988f, -0.04181165f, 0.78120053f, -2.22377038f, - -0.53264999f, -2.03721714f, 0.21023634f, 2.55751204f, -1.04522800f, 0.85386503f, 0.41594937f, -2.98181081f, - 1.14034331f, -1.41539204f, 0.13379651f, 3.47018123f, 1.53924727f, 1.50004411f, 2.87318921f, 1.62624204f, - 0.64942807f, -4.54302311f, -1.50294220f, -1.75212634f, 0.27900690f, -3.05124855f, 3.30960631f, -0.07991691f}; - } - - { - data.fp32_output_data = {}; - } - - { - data.fp16_output_data = { - -0.89160156f, 0.02633667f, -0.84863281f, 1.4345703f, -2.9199219f, -0.20654297f, 1.859375f, 0.45678711f, - 0.076782227f, 0.044921875f, 0.67333984f, 0.97119141f, 1.5351562f, -1.1025391f, 0.86572266f, -0.34765625f, - -1.2431641f, -1.8027344f, -1.0126953f, -0.71533203f, 0.77832031f, -0.59228516f, -2.0039062f, 3.1328125f, - -1.2080078f, 2.015625f, 0.82666016f, 2.0605469f, -0.46264648f, 1.5634766f, 4.3164062f, -1.03125f, - - 0.21158576f, -1.98279130f, 0.45935997f, -0.40457720f, 0.04772174f, 0.22094353f, 0.71238005f, -1.20860445f, - -0.56270063f, -1.10830855f, 0.14455934f, 2.87315512f, -1.14114404f, 0.66515017f, 0.16263856f, -1.75517499f, - 0.77650774f, -0.44058144f, 0.31942442f, 1.51513433f, 0.41078627f, 0.41566271f, 1.74393702f, 0.51457298f, - 0.78953874f, -3.10888410f, -0.47052401f, -0.75475156f, 0.90861011f, -1.82471263f, 2.04898596f, -0.67790967f, - - 1.17194295f, -2.17825341f, -0.02712549f, -1.53178656f, -0.48020893f, -0.00040733f, 0.77035600f, -2.06380320f, - -0.53738528f, -1.89084208f, 0.19988713f, 2.60725045f, -1.06034219f, 0.82412785f, 0.37603328f, -2.78852081f, - 1.08301103f, -1.26178384f, 0.16304730f, 3.16210985f, 1.36142719f, 1.32916999f, 2.69524455f, 1.45106804f, - 0.67150640f, -4.31703520f, -1.34025633f, -1.59496248f, 0.37821823f, -2.85797405f, 3.11096096f, -0.17414713f}; - } + LoadTensor("SelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV.query_data", data.query_data); + LoadTensor("SelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV.key_data", data.key_data); + LoadTensor("SelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV.value_data", data.value_data); + data.bias_data = {}; + LoadTensor("SelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV.qkv_data", data.qkv_data); + // Do not test fp32 + data.fp32_output_data = {}; + LoadTensor("SelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV.fp16_output_data", data.fp16_output_data); } -#endif void GetCrossAttentionData_HeadSize16_8(AttentionTestData& data) { data.hidden_size = 48; @@ -2965,138 +210,19 @@ void GetCrossAttentionData_HeadSize16_8(AttentionTestData& data) { AttentionKernelType::AttentionKernel_TrtFusedCrossAttention, AttentionKernelType::AttentionKernel_TrtFusedAttention}; - { - data.query_data = { - 2.88765883f, 1.27536213f, -0.57580215f, 2.73696542f, 2.19016314f, 0.42629790f, 1.55081677f, -2.01307678f, - -0.80203497f, -1.23206115f, 1.78565156f, -2.09875321f, -2.22730732f, -0.98120236f, -0.25774139f, 0.75868356f, - -2.87585187f, -0.41810805f, -2.11528730f, 0.50642025f, -0.29446256f, -3.69675803f, -2.73721838f, -1.51089072f, - 0.74300194f, 0.27352047f, -0.88251829f, 2.82622814f, 0.73837662f, -2.14588642f, 0.37608737f, -0.06190044f, - 1.83028936f, -0.02953561f, 1.94609165f, 1.03678417f, -3.07869005f, 1.13037205f, 2.14215207f, 1.29724145f, - 0.06229818f, -2.93803453f, -1.12074065f, -1.75312924f, -2.51804519f, -0.20714152f, 0.94910270f, 0.31394321f, - - -1.97659302f, -2.22348428f, 2.25573063f, -2.24459195f, -2.28073978f, -0.52412349f, -0.57297325f, 3.29259396f, - 1.35617173f, -0.83082151f, 0.03767079f, 1.82568312f, 0.88193995f, 1.15579486f, 1.87845564f, -0.15923920f, - 2.37435389f, 1.49093378f, 1.95134592f, -1.67609048f, -0.45959851f, 1.63960719f, 3.44909906f, -0.23531833f, - -0.57074630f, 1.38279045f, 0.58870834f, 0.85297751f, -1.44973445f, 1.56243801f, -0.67229253f, -0.16198707f, - 2.24443579f, 0.01009618f, -2.02270651f, -1.48122561f, -0.71337879f, -1.41594160f, 0.67262292f, -1.45187402f, - 2.45791745f, 0.94860327f, 1.22767174f, 1.16789973f, -0.69281816f, 0.90847492f, 1.16295385f, -0.84179711f}; - } - { - data.key_data = { - 1.14242256f, 1.08148384f, -0.00962424f, -1.62719429f, 0.86478198f, 0.16862091f, 1.01692820f, -1.15278327f, - -1.13622630f, 1.78038371f, 0.58222097f, 0.39166588f, 1.75063372f, -1.20408881f, 0.75154918f, 0.58156419f, - -0.98975772f, -0.82555556f, -0.72656512f, -2.42399549f, 2.19217968f, 2.18518472f, -1.72216129f, 1.35098433f, - -0.34989786f, -0.69064844f, -0.98365444f, 3.10148478f, 0.64813483f, 1.78129303f, -0.47006512f, 2.53122735f, - -4.06511545f, 0.22256386f, 2.46787810f, -1.64387906f, -0.72458595f, 0.03613299f, -2.20491385f, 1.25488305f, - -1.49934030f, 0.09558886f, 0.21092418f, -0.04370949f, -0.54754108f, 0.89117372f, -1.44286251f, -0.89374435f, - 0.09757380f, 0.04077591f, -0.81791472f, -0.19737752f, 1.13775492f, -1.51351953f, 0.59109330f, 2.86624002f, - -0.09282493f, -1.69204521f, 1.27087700f, 3.53944731f, 0.59776509f, -0.90838081f, -0.15813766f, -1.86199224f, - 0.18734205f, -0.76110429f, -0.02243887f, -0.94068182f, 1.32443166f, 0.03512055f, -0.13194422f, -1.50401211f, - 0.92001319f, 0.20918207f, -1.34839189f, 1.56431675f, -0.61030018f, 2.39562368f, -1.56722510f, -0.96874726f, - 0.36663681f, 1.67216635f, 1.97995794f, -1.43150198f, 1.61904466f, -0.26285610f, -0.63515049f, 3.34068251f, - 0.54150528f, 1.26057637f, -0.99386609f, 0.06303076f, -1.30578506f, 0.03304024f, -0.22100723f, -0.79328370f, - -0.48726845f, -1.41476154f, -1.45116997f, 0.53907454f, -2.14415288f, 1.14340270f, -0.21846619f, -2.72349358f, - 2.99664998f, -2.38684058f, 0.95269018f, 0.04208702f, -1.75080788f, 1.24652982f, -1.76879966f, 3.10814905f, - 2.48754454f, -0.62601894f, 1.41356945f, 0.10340121f, 1.09059846f, -0.78241473f, -0.61477584f, -0.19339988f, - -0.48253334f, -2.41782594f, 1.04690075f, 0.14725411f, -0.20820639f, -1.95920563f, 0.96303236f, -1.20068836f, - 1.01268184f, 4.29013920f, 0.77999580f, 1.46932411f, 0.87674600f, -1.25074506f, 2.45850706f, 0.09870356f, - -0.14051074f, 1.17763662f, -1.21477187f, 1.60379291f, -0.01956993f, 0.43266663f, -0.45684600f, -1.02696598f, - - -1.71051037f, -1.90946770f, -2.07985783f, 2.35042953f, 0.35059446f, -0.44228595f, 4.08558750f, -0.60121447f, - 0.78836018f, 0.35280651f, 0.23129070f, -0.21523762f, 0.12277550f, 0.12348226f, -1.62759030f, -2.78246498f, - 4.04853964f, 0.29263157f, -0.38621908f, -1.07599223f, -1.99170423f, 1.41409016f, 2.19121861f, -3.53451037f, - 3.63692737f, 0.68270516f, 2.51469731f, 2.57543731f, -2.39040112f, -3.97164130f, 1.28371549f, 1.64144099f, - 0.18788165f, 1.15558743f, 2.74443531f, 0.92457932f, -0.34628516f, 0.15525299f, 1.43510377f, 0.20861864f, - 2.88269520f, 0.64859426f, 1.78730142f, -2.25655675f, -1.83863652f, -2.58051491f, -4.23162079f, 1.49537027f, - -0.70385075f, 2.55361128f, 1.60707259f, 0.84735453f, -2.07756495f, -1.99240303f, -3.60991144f, 2.87136865f, - 2.31296396f, 2.30251813f, -1.05624914f, -2.43777156f, -0.27048296f, 2.39037871f, -2.04504776f, 1.65183067f, - -0.38970214f, 0.16808379f, -1.30286717f, 1.90201700f, -2.71696734f, -0.66445369f, 1.27085483f, -0.60816145f, - 1.81054437f, -1.55584621f, -2.19360781f, -4.52794456f, -0.90534067f, 0.94724411f, 2.40401077f, -2.94815230f, - 1.56385708f, -0.63737142f, -0.72946531f, -0.79579020f, -0.18071416f, 0.66005665f, -3.16687059f, -0.97323495f, - 0.49748731f, -3.54246902f, -2.14790606f, 0.09179869f, -0.56292027f, -2.96827269f, 1.74778676f, 0.12816763f, - -3.19650269f, 2.50638890f, 1.02038431f, 1.50519919f, 0.47196171f, -1.89026380f, -1.86559379f, 0.82210326f, - 0.10818237f, 1.45290673f, 1.62321615f, -0.61283481f, -1.42501950f, 2.10349464f, -1.65715265f, 0.30090189f, - -3.81919909f, -2.44903922f, -1.20557833f, -0.69951278f, -1.31475580f, -3.73842764f, 1.49299407f, -0.70933276f, - -1.49021530f, 0.71776378f, -1.23052382f, -2.13119912f, -1.20718014f, 2.30572701f, 1.78386402f, -1.57122159f, - -1.08014178f, -1.40319920f, -1.40852046f, 0.59488881f, -3.51004219f, 2.35288191f, -2.06260157f, -1.11531663f, - 2.51375723f, 0.25726259f, -0.99232292f, 1.47292709f, 2.81933832f, -0.39054599f, 0.18200648f, 1.54844952f}; - } - - { - data.value_data = { - 1.79297853f, 0.96909231f, 1.23087275f, -0.61933923f, -0.56477690f, 1.47813499f, 0.51474279f, -3.44743419f, - 0.95816678f, -0.20553169f, -0.76906109f, -4.60927439f, 0.40629998f, 0.91934747f, -1.09594405f, -1.45653892f, - -0.59282207f, 0.05621797f, -2.26634383f, -1.30799258f, 1.22072279f, -3.60811162f, 1.70111597f, 0.47336632f, - -1.82395399f, 0.73557752f, 2.32600021f, -0.22650969f, -0.48526058f, 1.40349376f, -0.33553454f, 0.45531431f, - 0.73859257f, 0.37798560f, 0.85344458f, -1.30447221f, 1.23349071f, -0.26439479f, 1.18636096f, -0.33328748f, - -0.50939041f, 0.53500950f, 1.33486223f, -1.54447496f, -2.88690519f, -0.06809106f, -0.00597921f, -1.07510388f, - 0.69456708f, 2.91441655f, -0.25431669f, -1.20305562f, 2.06701255f, -0.86700624f, -2.23615170f, 0.13303493f, - -2.97540593f, 0.08654684f, 1.40381706f, 3.54294443f, -2.07661867f, -1.33181918f, 2.24228764f, 1.79975545f, - 2.14695477f, 1.40222490f, -0.29813689f, 1.94485068f, 1.99623775f, 1.53450203f, 0.28755581f, -0.67934704f, - - -2.45574522f, -1.91599977f, 5.05240345f, 2.24617362f, 3.99182248f, 0.92924285f, -0.39660916f, -0.08696688f, - 0.24855530f, 0.71378094f, 0.92413902f, 1.73599064f, 1.03852975f, 2.44676781f, 0.35013664f, 0.98107171f, - 1.62946916f, 0.41239718f, -1.41385484f, 2.49293518f, 2.32976985f, 2.89612579f, 2.66875219f, 1.47379971f, - -1.13935280f, 0.38051969f, -2.38735437f, -2.80645251f, 0.18637873f, 2.13938355f, 2.92260599f, -0.38653925f, - 0.58366799f, -1.67636371f, -2.29396892f, -1.31527638f, 2.39795637f, 0.39815575f, -0.98530269f, -1.29227996f, - 0.14452982f, -0.38186538f, -1.71267688f, 0.18121701f, -2.26441002f, -0.94511753f, 0.27371156f, -2.44858527f, - -0.73659700f, 0.74325305f, -1.97666430f, -1.07301974f, 0.17534591f, -1.66584718f, 1.21820331f, 0.67675018f, - -1.08938253f, 1.78010321f, 0.39817584f, -0.02914053f, 1.13571596f, -0.44081455f, 1.70561552f, -2.12085509f, - -0.69322622f, -1.87331009f, -2.15000772f, 2.08436966f, 1.70494926f, -3.69169927f, -1.22119129f, -1.60190558f}; - } - - { - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, -0.34948170f, -0.19608477f, 0.19725692f, 0.39987487f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, -0.23178342f, -0.13692456f, -0.04889601f, 0.48739988f, - -0.25891554f, 0.13431972f, 0.22861153f, 0.06360734f, 0.48096961f, -0.47906545f, 0.43613154f, -0.23511401f, - -0.10595283f, -0.42839217f, 0.28931111f, -0.13180739f, -0.45826656f, 0.23286396f, -0.43407962f, 0.40754890f, - 0.23778325f, 0.34850210f, -0.01385659f, 0.32141626f, -0.27738628f, 0.27683002f, 0.31886810f, -0.24781504f, - -0.25476855f, -0.46742713f, -0.12478521f, 0.39731556f, -0.12087554f, 0.40822440f, 0.13202906f, -0.23747686f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, 0.27376485f, -0.38174152f, -0.43700469f, 0.38040614f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f, 0.07120579f, -0.08055863f, 0.12095112f, -0.27988660f, - 0.06004709f, -0.05600315f, -0.25510073f, 0.41887105f, -0.19016314f, 0.47241372f, 0.12890404f, -0.24272856f, - 0.21106839f, -0.40523255f, 0.10336459f, -0.11084765f, 0.42408967f, -0.15285304f, -0.28945464f, -0.25714916f, - 0.40978593f, -0.09138483f, -0.02013114f, -0.39042589f, -0.19557095f, 0.07540411f, 0.33955890f, 0.41873980f, - -0.27744853f, -0.33097768f, -0.44587523f, -0.01648277f, 0.34952271f, -0.48838940f, -0.17273578f, 0.37286615f, - -0.10567203f, 0.26791072f, -0.08976898f, 0.31341976f, 0.06027532f, 0.14307594f, 0.31587386f, 0.16180152f, - 0.34785229f, 0.00531715f, -0.35168743f, -0.11641458f, 0.39196932f, 0.44535065f, 0.43545735f, 0.15593112f, - 0.06171834f, -0.42181283f, -0.41170910f, 0.40969193f, -0.01510030f, 0.07973170f, -0.18156880f, 0.21522856f}; - } - - { - data.fp32_output_data = { - 0.70553654f, 2.84393549f, -0.06753168f, -0.78168947f, 1.67733526f, -0.32306066f, -1.46519339f, -0.24197246f, - 0.68103230f, 0.09225838f, -0.12426007f, -2.19415975f, 0.82274425f, 0.54800904f, 0.77917045f, -0.37480056f, - 1.41798937f, 0.70201361f, -0.38768357f, 1.33144617f, 0.71884990f, 0.98060107f, 0.09563713f, -0.51187015f, - - -1.23079133f, 0.65636921f, -2.42403007f, -2.38468814f, 0.26282290f, 2.08802962f, 3.13919282f, -0.17057800f, - 0.59563273f, 0.71862715f, 0.57042938f, 1.61676264f, 1.43126500f, 2.88902473f, 0.78586847f, 1.13364232f, - -0.24963731f, -1.69403267f, -2.38265419f, 1.86863625f, 0.37573546f, -2.40374231f, -0.73219091f, -1.54168916f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_HeadSize16_8.query_data", data.query_data); + LoadTensor("CrossAttentionData_HeadSize16_8.key_data", data.key_data); + LoadTensor("CrossAttentionData_HeadSize16_8.value_data", data.value_data); + LoadTensor("CrossAttentionData_HeadSize16_8.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_HeadSize16_8.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_HeadSize16_8_NoBias(AttentionTestData& data) { GetCrossAttentionData_HeadSize16_8(data); data.bias_data.clear(); - { - data.fp32_output_data = { - 0.88660234f, 2.46094799f, 0.10754689f, -1.06147599f, 1.46027637f, -0.32641891f, -1.61505651f, -0.62761730f, - 0.35181305f, 0.04672670f, 0.11436265f, -2.31145239f, 0.37641913f, 0.18575731f, 0.18441223f, -0.61060971f, - 0.62300563f, 0.86652821f, 0.32993844f, -0.02772357f, -0.44500753f, 0.32007718f, 0.26425001f, -0.77443624f, - - -1.12354600f, 0.38605267f, -2.30243778f, -2.65445495f, 0.21547484f, 1.88312864f, 2.78607035f, -0.31523654f, - 0.24827829f, 0.71276933f, 0.92208558f, 1.73359740f, 1.03935337f, 2.44456077f, 0.34983918f, 0.97865880f, - -0.25726128f, -1.24286532f, -1.95995116f, 1.54186428f, 0.55555028f, -2.34330893f, -0.46331605f, -1.61526406f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_HeadSize16_8_NoBias.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_HeadSize16(AttentionTestData& data) { @@ -3107,102 +233,20 @@ void GetCrossAttentionData_HeadSize16(AttentionTestData& data) { data.sequence_length = 2; data.kv_sequence_length = 3; data.mask_type = AttentionMaskType::MASK_NONE; - { - data.query_data = { - 2.88765883f, 1.27536213f, -0.57580215f, 2.73696542f, 2.19016314f, 0.42629790f, 1.55081677f, -2.01307678f, - -0.80203497f, -1.23206115f, 1.78565156f, -2.09875321f, -2.22730732f, -0.98120236f, -0.25774139f, 0.75868356f, - -2.87585187f, -0.41810805f, -2.11528730f, 0.50642025f, -0.29446256f, -3.69675803f, -2.73721838f, -1.51089072f, - 0.74300194f, 0.27352047f, -0.88251829f, 2.82622814f, 0.73837662f, -2.14588642f, 0.37608737f, -0.06190044f, - -1.97659302f, -2.22348428f, 2.25573063f, -2.24459195f, -2.28073978f, -0.52412349f, -0.57297325f, 3.29259396f, - 1.35617173f, -0.83082151f, 0.03767079f, 1.82568312f, 0.88193995f, 1.15579486f, 1.87845564f, -0.15923920f, - 2.37435389f, 1.49093378f, 1.95134592f, -1.67609048f, -0.45959851f, 1.63960719f, 3.44909906f, -0.23531833f, - -0.57074630f, 1.38279045f, 0.58870834f, 0.85297751f, -1.44973445f, 1.56243801f, -0.67229253f, -0.16198707f}; - } - { - data.key_data = { - 1.14242256f, 1.08148384f, -0.00962424f, -1.62719429f, 0.86478198f, 0.16862091f, 1.01692820f, -1.15278327f, - -1.13622630f, 1.78038371f, 0.58222097f, 0.39166588f, 1.75063372f, -1.20408881f, 0.75154918f, 0.58156419f, - -0.98975772f, -0.82555556f, -0.72656512f, -2.42399549f, 2.19217968f, 2.18518472f, -1.72216129f, 1.35098433f, - -0.34989786f, -0.69064844f, -0.98365444f, 3.10148478f, 0.64813483f, 1.78129303f, -0.47006512f, 2.53122735f, - 0.09757380f, 0.04077591f, -0.81791472f, -0.19737752f, 1.13775492f, -1.51351953f, 0.59109330f, 2.86624002f, - -0.09282493f, -1.69204521f, 1.27087700f, 3.53944731f, 0.59776509f, -0.90838081f, -0.15813766f, -1.86199224f, - 0.18734205f, -0.76110429f, -0.02243887f, -0.94068182f, 1.32443166f, 0.03512055f, -0.13194422f, -1.50401211f, - 0.92001319f, 0.20918207f, -1.34839189f, 1.56431675f, -0.61030018f, 2.39562368f, -1.56722510f, -0.96874726f, - -0.48726845f, -1.41476154f, -1.45116997f, 0.53907454f, -2.14415288f, 1.14340270f, -0.21846619f, -2.72349358f, - 2.99664998f, -2.38684058f, 0.95269018f, 0.04208702f, -1.75080788f, 1.24652982f, -1.76879966f, 3.10814905f, - 2.48754454f, -0.62601894f, 1.41356945f, 0.10340121f, 1.09059846f, -0.78241473f, -0.61477584f, -0.19339988f, - -0.48253334f, -2.41782594f, 1.04690075f, 0.14725411f, -0.20820639f, -1.95920563f, 0.96303236f, -1.20068836f}; - } - - { - data.value_data = { - 1.79297853f, 0.96909231f, 1.23087275f, -0.61933923f, -0.56477690f, 1.47813499f, 0.51474279f, -3.44743419f, - 0.95816678f, -0.20553169f, -0.76906109f, -4.60927439f, 0.40629998f, 0.91934747f, -1.09594405f, -1.45653892f, - -0.59282207f, 0.05621797f, -2.26634383f, -1.30799258f, 1.22072279f, -3.60811162f, 1.70111597f, 0.47336632f, - -1.43857694f, -0.13917151f, -1.34617388f, 1.07960105f, -1.77342618f, 0.31946269f, 1.19137061f, 2.59346104f, - -1.82395399f, 0.73557752f, 2.32600021f, -0.22650969f, -0.48526058f, 1.40349376f, -0.33553454f, 0.45531431f, - 0.73859257f, 0.37798560f, 0.85344458f, -1.30447221f, 1.23349071f, -0.26439479f, 1.18636096f, -0.33328748f, - -0.50939041f, 0.53500950f, 1.33486223f, -1.54447496f, -2.88690519f, -0.06809106f, -0.00597921f, -1.07510388f, - 0.62182164f, 0.50033569f, -0.88293070f, 2.56142712f, 0.37708595f, 1.59349704f, -1.17139614f, 0.89580274f, - 0.69456708f, 2.91441655f, -0.25431669f, -1.20305562f, 2.06701255f, -0.86700624f, -2.23615170f, 0.13303493f, - -2.97540593f, 0.08654684f, 1.40381706f, 3.54294443f, -2.07661867f, -1.33181918f, 2.24228764f, 1.79975545f, - 2.14695477f, 1.40222490f, -0.29813689f, 1.94485068f, 1.99623775f, 1.53450203f, 0.28755581f, -0.67934704f, - -0.92102510f, -1.52764773f, 1.11267352f, -3.90122724f, 0.22128634f, 0.14945325f, -4.38529491f, -1.58423281f}; - } - { - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, -0.34948170f, -0.19608477f, 0.19725692f, 0.39987487f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, -0.23178342f, -0.13692456f, -0.04889601f, 0.48739988f, - -0.25891554f, 0.13431972f, 0.22861153f, 0.06360734f, 0.48096961f, -0.47906545f, 0.43613154f, -0.23511401f, - -0.10595283f, -0.42839217f, 0.28931111f, -0.13180739f, -0.45826656f, 0.23286396f, -0.43407962f, 0.40754890f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, 0.27376485f, -0.38174152f, -0.43700469f, 0.38040614f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f, 0.07120579f, -0.08055863f, 0.12095112f, -0.27988660f, - 0.06004709f, -0.05600315f, -0.25510073f, 0.41887105f, -0.19016314f, 0.47241372f, 0.12890404f, -0.24272856f, - 0.21106839f, -0.40523255f, 0.10336459f, -0.11084765f, 0.42408967f, -0.15285304f, -0.28945464f, -0.25714916f, - -0.10567203f, 0.26791072f, -0.08976898f, 0.31341976f, 0.06027532f, 0.14307594f, 0.31587386f, 0.16180152f, - 0.34785229f, 0.00531715f, -0.35168743f, -0.11641458f, 0.39196932f, 0.44535065f, 0.43545735f, 0.15593112f, - 0.06171834f, -0.42181283f, -0.41170910f, 0.40969193f, -0.01510030f, 0.07973170f, -0.18156880f, 0.21522856f, - 0.03915739f, -0.20913908f, -0.47068381f, 0.35633272f, -0.35124153f, 0.36624825f, -0.05567622f, -0.35343069f}; - } - - { - data.fp32_output_data = { - 0.70553654f, 2.84393549f, -0.06753166f, -0.78168941f, 1.67733538f, -0.32306066f, -1.46519351f, -0.24197248f, - -1.95703733f, 0.05333783f, 0.71154630f, 2.09348249f, -1.24223638f, -0.52374214f, 2.15032387f, 1.41931129f, - -0.12594563f, 0.02337830f, -0.85073662f, -0.56283176f, -0.47189179f, -1.30011129f, 0.58861959f, -0.13839069f, - -0.43588838f, -0.25786775f, -1.28476405f, 1.40800762f, -0.92311549f, 1.21551156f, -0.64031672f, 0.94095230f, - - -1.87212098f, 1.04452848f, 2.18516684f, 0.06764929f, -0.37797281f, 1.50475919f, -0.05229051f, 0.59941143f, - 1.01834595f, 0.37615222f, 0.50706661f, -1.34108353f, 1.56169033f, 0.16475427f, 1.63450289f, -0.14124450f, - -0.21351013f, 0.15201563f, 0.47484040f, -0.79835385f, -2.11648011f, -0.13788147f, -0.01865268f, -0.69491959f, - 0.34924412f, 0.05382843f, -1.21107709f, 2.20767021f, -0.16749848f, 1.72250605f, -1.32190716f, 0.45872629f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_HeadSize16.query_data", data.query_data); + LoadTensor("CrossAttentionData_HeadSize16.key_data", data.key_data); + LoadTensor("CrossAttentionData_HeadSize16.value_data", data.value_data); + LoadTensor("CrossAttentionData_HeadSize16.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_HeadSize16.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionData_HeadSize16_NoBias(AttentionTestData& data) { GetCrossAttentionData_HeadSize16(data); data.bias_data.clear(); - { - data.fp32_output_data = { - 0.88660234f, 2.46094799f, 0.10754693f, -1.06147599f, 1.46027637f, -0.32641891f, -1.61505640f, -0.62761730f, - -2.07027483f, 0.02902380f, 0.92946291f, 1.71574616f, -1.48879766f, -0.83188367f, 1.50993633f, 1.06654513f, - -0.19588387f, 0.41118127f, -0.68736500f, -0.95931244f, -0.17629701f, -1.62689805f, 0.88834876f, -0.24655706f, - -0.61657274f, -0.09123766f, -0.84804469f, 0.95479041f, -0.72092235f, 0.76219988f, -0.41778216f, 1.41442800f, - - -1.75602365f, 0.78011239f, 2.26923561f, -0.24788655f, -0.43482834f, 1.35864854f, -0.36920172f, 0.42971241f, - 0.66571552f, 0.36931390f, 0.85642850f, -1.22419143f, 1.16351080f, -0.27983150f, 1.19616866f, -0.29633391f, - -0.24715914f, 0.57112449f, 0.77329880f, -1.16207874f, -1.93779230f, -0.29239467f, 0.21112607f, -0.86494255f, - 0.23835859f, 0.22305638f, -0.72983342f, 1.73876703f, 0.12544832f, 1.30632234f, -1.24074650f, 0.82852137f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionData_HeadSize16_NoBias.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetCrossAttentionDataWithPast(AttentionTestData& data) { @@ -3221,45 +265,12 @@ void GetCrossAttentionDataWithPast(AttentionTestData& data) { AttentionKernelType::AttentionKernel_TrtFusedAttention, AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention}; - { - data.query_data = { - -0.10939738f, -0.11916742f, -0.23157823f, -0.12894472f, - -0.02661306f, 0.26251313f, 0.30725253f, -0.34759378f, - -0.11695808f, -0.13129434f, -0.17031054f, -0.14986445f, - -0.02826184f, 0.2797631f, 0.27337456f, -0.44312602f}; - } + LoadTensor("CrossAttentionDataWithPast.query_data", data.query_data); // The past key and value data will be passed to the kernel as input 'key' and 'value'. - { - data.past_key_data = { - 0.5967375f, 0.5966938f, 0.48602432f, 0.5341031f, - 0.55797786f, 0.5663399f, 0.57087725f, 0.6240304f, - 0.5352563f, 0.5648297f, 0.4972945f, 0.56637144f, - - 0.44123724f, 0.35872823f, 0.32176313f, 0.4490301f, - 0.3643952f, 0.51968557f, 0.50137347f, 0.5743993f, - 0.3905106f, 0.4741712f, 0.40881708f, 0.47243845f}; - } - - { - data.past_value_data = { - 0.40251260f, 0.55487730f, 0.49565578f, 0.42683450f, - 0.44379145f, 0.58945787f, 0.54852820f, 0.43376005f, - 0.44116694f, 0.44007313f, 0.40293324f, 0.53202707f, - - 0.35520583f, 0.47293650f, 0.45417705f, 0.33723440f, - 0.50175804f, 0.37620395f, 0.24103148f, 0.50958070f, - 0.56803876f, 0.37866923f, 0.32273075f, 0.44389135f}; - } - - { - data.fp32_output_data = { - 0.4291f, 0.5275f, 0.4818f, 0.4645f, 0.4770f, 0.4082f, 0.3372f, 0.4319f, - 0.4291f, 0.5276f, 0.4818f, 0.4645f, 0.4768f, 0.4083f, 0.3377f, 0.4315f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } + LoadTensor("CrossAttentionDataWithPast.past_key_data", data.past_key_data); + LoadTensor("CrossAttentionDataWithPast.past_value_data", data.past_value_data); + LoadTensor("CrossAttentionDataWithPast.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; } void GetSelfAttentionData_WithPast_WithRelPosBias_ForT5(AttentionTestData& data) { @@ -3278,102 +289,17 @@ void GetSelfAttentionData_WithPast_WithRelPosBias_ForT5(AttentionTestData& data) AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - { - data.query_data = { - 0.00403503f, 0.08716156f, -0.0358175f, -0.08171791f, - 0.48912194f, -0.22679007f, -0.09093101f, -0.5939322f, - 0.00878838f, 0.03355761f, -0.08080226f, -0.06677517f, - 0.55038965f, -0.2720567f, -0.12977877f, -0.634123f}; - } - { - data.key_data = { - 0.2808786f, 0.10041683f, 0.15880886f, 0.45283064f, - 0.39884242f, 0.12596075f, 0.4198916f, -0.0651141f, - 0.31678027f, 0.11010794f, 0.21594375f, 0.4975329f, - 0.436772f, 0.20940652f, 0.44072092f, -0.05601776f}; - } - - { - data.value_data = { - 0.26421773f, -0.16541699f, -0.0599675f, 0.27200517f, - -0.1074627f, -0.4493224f, -0.03694462f, 0.17997989f, - 0.27960598f, -0.16643806f, -0.07019104f, 0.29006317f, - -0.11640988f, -0.47876123f, -0.01979145f, 0.11468418f}; - } - - { - data.rel_pos_bias_data = { - 0.4781123f, 0.82420444f, 0.654424f, 0.3995186f, 0.5482078f, - 0.55570245f, 0.4216576f, 0.46001542f, 0.67183703f, 0.41973996f, - - 0.28494194f, 0.60367906f, 0.3453173f, 0.44483483f, 0.6770777f, - 0.5460559f, 0.31994605f, 0.5470492f, 0.5433419f, 0.60349935f}; - - data.broadcast_rel_pos_bias = false; - } - - { - data.past_key_data = { - 0.34734827f, 0.5592256f, 0.5333037f, 0.5122027f, - 0.5940516f, 0.44744077f, 0.43128848f, 0.55360645f, - 0.57874715f, 0.29512063f, 0.2780432f, 0.4693917f, - - 0.4450266f, 0.530704f, 0.3124955f, 0.4273598f, - 0.44368753f, 0.5890438f, 0.5054336f, 0.46042535f, - 0.5352153f, 0.5157861f, 0.39744973f, 0.5441864f}; - } - - { - data.past_value_data = { - 0.48998538f, 0.5493853f, 0.556647f, 0.7011929f, - 0.543909f, 0.5630743f, 0.5087797f, 0.3901024f, - 0.53116417f, 0.4086225f, 0.5320247f, 0.5145377f, - - 0.4086198f, 0.6913348f, 0.50045484f, 0.5338214f, - 0.52980417f, 0.5243695f, 0.6046111f, 0.53555113f, - 0.44936907f, 0.6010697f, 0.38031512f, 0.427301f}; - } - - { - data.fp32_output_data = { - 0.4358f, 0.2708f, 0.3201f, 0.4347f, 0.1886f, 0.0845f, 0.2479f, 0.3289f, - 0.4157f, 0.2247f, 0.2826f, 0.4321f, 0.1874f, 0.1021f, 0.2427f, 0.3305f}; - } - - { - data.fp16_output_data = data.fp32_output_data; - } - - { - data.present_key_data = { - 0.3473f, 0.5592f, 0.5333f, 0.5122f, - 0.5941f, 0.4474f, 0.4313f, 0.5536f, - 0.5787f, 0.2951f, 0.2780f, 0.4694f, - 0.2809f, 0.1004f, 0.1588f, 0.4528f, - 0.3168f, 0.1101f, 0.2159f, 0.4975f, - - 0.4450f, 0.5307f, 0.3125f, 0.4274f, - 0.4437f, 0.5890f, 0.5054f, 0.4604f, - 0.5352f, 0.5158f, 0.3974f, 0.5442f, - 0.3988f, 0.1260f, 0.4199f, -0.0651f, - 0.4368f, 0.2094f, 0.4407f, -0.0560f}; - } - - { - data.present_value_data = { - 0.4900f, 0.5494f, 0.5566f, 0.7012f, - 0.5439f, 0.5631f, 0.5088f, 0.3901f, - 0.5312f, 0.4086f, 0.5320f, 0.5145f, - 0.2642f, -0.1654f, -0.0600f, 0.2720f, - 0.2796f, -0.1664f, -0.0702f, 0.2901f, - - 0.4086f, 0.6913f, 0.5005f, 0.5338f, - 0.5298f, 0.5244f, 0.6046f, 0.5356f, - 0.4494f, 0.6011f, 0.3803f, 0.4273f, - -0.1075f, -0.4493f, -0.0369f, 0.1800f, - -0.1164f, -0.4788f, -0.0198f, 0.1147f}; - } - + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.query_data", data.query_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.key_data", data.key_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.value_data", data.value_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.rel_pos_bias_data", data.rel_pos_bias_data); + data.broadcast_rel_pos_bias = false; + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.past_key_data", data.past_key_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.past_value_data", data.past_value_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.present_key_data", data.present_key_data); + LoadTensor("SelfAttentionData_WithPast_WithRelPosBias_ForT5.present_value_data", data.present_value_data); data.is_static_kv = false; } @@ -3393,465 +319,14 @@ void GetAttentionDataCutlassRelPosBias(AttentionTestData& data) { AttentionKernelType::AttentionKernel_TrtFusedCrossAttention, AttentionKernelType::AttentionKernel_TrtFusedAttention}; - { - data.query_data = { - -0.029273793f, - 0.079709493f, - 0.064531095f, - 0.24270254f, - -0.28326464f, - 0.20984903f, - -0.10173888f, - 0.18373983f, - - 0.089472905f, - -0.0063416883f, - -0.049477674f, - 0.36512995f, - -0.23620239f, - 0.1464397f, - 0.068258412f, - 0.31627196f, - - 0.12436871f, - -0.0075563118f, - -0.11576633f, - 0.41008925f, - -0.19456652f, - 0.20145792f, - 0.11790096f, - 0.39789933f, - - 0.002485469f, - 0.029660821f, - -0.043821491f, - 0.3892332f, - -0.26994205f, - 0.14530671f, - 0.12950704f, - 0.36185294f, - - -0.029273793f, - 0.079709493f, - 0.064531095f, - 0.24270254f, - -0.28326464f, - 0.20984903f, - -0.10173888f, - 0.18373983f, - - 0.089472905f, - -0.0063416883f, - -0.049477674f, - 0.36512995f, - -0.23620239f, - 0.1464397f, - 0.068258412f, - 0.31627196f, - - 0.12436871f, - -0.0075563118f, - -0.11576633f, - 0.41008925f, - -0.19456652f, - 0.20145792f, - 0.11790096f, - 0.39789933f, - - 0.002485469f, - 0.029660821f, - -0.043821491f, - 0.3892332f, - -0.26994205f, - 0.14530671f, - 0.12950704f, - 0.36185294f, - }; - } - { - data.key_data = { - -0.32538497f, - 0.34121913f, - -0.18170178f, - -0.015152611f, - 0.20429322f, - 0.25979176f, - 0.21269324f, - 0.0025638193f, - - -0.24246037f, - 0.21112341f, - -0.36959589f, - -0.16091451f, - 0.24183474f, - 0.18856162f, - 0.094487116f, - -0.3053959f, - - -0.35736683f, - 0.29276621f, - -0.4217523f, - -0.20031664f, - 0.33148992f, - 0.26928401f, - 0.19360018f, - -0.39494509f, - - -0.28043351f, - 0.24279942f, - -0.29154932f, - -0.13657911f, - 0.31932494f, - 0.3500579f, - 0.027172565f, - -0.19327414f, - - -0.32538497f, - 0.34121913f, - -0.18170178f, - -0.015152611f, - 0.20429322f, - 0.25979176f, - 0.21269324f, - 0.0025638193f, - - -0.24246037f, - 0.21112341f, - -0.36959589f, - -0.16091451f, - 0.24183474f, - 0.18856162f, - 0.094487116f, - -0.3053959f, - - -0.35736683f, - 0.29276621f, - -0.4217523f, - -0.20031664f, - 0.33148992f, - 0.26928401f, - 0.19360018f, - -0.39494509f, - - -0.28043351f, - 0.24279942f, - -0.29154932f, - -0.13657911f, - 0.31932494f, - 0.3500579f, - 0.027172565f, - -0.19327414f, - }; - } - - { - data.value_data = { - 0.56916672f, - -0.2443777f, - 0.47111356f, - -0.52134115f, - 0.010381341f, - 0.0696759f, - -0.071910433f, - -0.35201436f, - - 0.70809275f, - -0.24479815f, - 0.41633749f, - -0.34744334f, - -0.0044222325f, - 0.25929695f, - -0.087832771f, - -0.281232f, - - 0.90039468f, - -0.28931504f, - 0.56394172f, - -0.43948689f, - -0.05856207f, - 0.33713666f, - -0.10320446f, - -0.38833332f, - - 0.76054728f, - -0.29080144f, - 0.50414616f, - -0.42371163f, - -0.047198489f, - 0.31959397f, - -0.22683662f, - -0.30321664f, - - 0.56916672f, - -0.2443777f, - 0.47111356f, - -0.52134115f, - 0.010381341f, - 0.0696759f, - -0.071910433f, - -0.35201436f, - - 0.70809275f, - -0.24479815f, - 0.41633749f, - -0.34744334f, - -0.0044222325f, - 0.25929695f, - -0.087832771f, - -0.281232f, - - 0.90039468f, - -0.28931504f, - 0.56394172f, - -0.43948689f, - -0.05856207f, - 0.33713666f, - -0.10320446f, - -0.38833332f, - - 0.76054728f, - -0.29080144f, - 0.50414616f, - -0.42371163f, - -0.047198489f, - 0.31959397f, - -0.22683662f, - -0.30321664f, - }; - } - - { - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, - -0.25891554f, 0.13431972f, 0.22861153f, 0.06360734f, - -0.10595283f, -0.42839217f, 0.28931111f, -0.13180739f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f}; - } - - { - data.rel_pos_bias_data = { - -10.808288f, - -10.887209f, - 7.8799553f, - -4.6565766f, - -1.6700006f, - -0.033962168f, - 7.4929152f, - 10.944146f, - 8.640254f, - -18.862164f, - -3.1202927f, - -6.3049207f, - 3.4508536f, - 11.722519f, - 3.3550568f, - -5.4888172f, - - -2.0828252f, - -13.241742f, - 2.9868939f, - 1.4455698f, - -15.262972f, - -10.457437f, - -8.4519463f, - -4.4281874f, - 10.212368f, - -0.28622282f, - 12.087646f, - 6.5218501f, - 8.1785011f, - 13.985523f, - -8.2068987f, - 5.4260745f, - - -10.808288f, - -10.887209f, - 7.8799553f, - -4.6565766f, - -1.6700006f, - -0.033962168f, - 7.4929152f, - 10.944146f, - 8.640254f, - -18.862164f, - -3.1202927f, - -6.3049207f, - 3.4508536f, - 11.722519f, - 3.3550568f, - -5.4888172f, - - -2.0828252f, - -13.241742f, - 2.9868939f, - 1.4455698f, - -15.262972f, - -10.457437f, - -8.4519463f, - -4.4281874f, - 10.212368f, - -0.28622282f, - 12.087646f, - 6.5218501f, - 8.1785011f, - 13.985523f, - -8.2068987f, - 5.4260745f, - - -10.808288f, - -10.887209f, - 7.8799553f, - -4.6565766f, - -1.6700006f, - -0.033962168f, - 7.4929152f, - 10.944146f, - 8.640254f, - -18.862164f, - -3.1202927f, - -6.3049207f, - 3.4508536f, - 11.722519f, - 3.3550568f, - -5.4888172f, - - -2.0828252f, - -13.241742f, - 2.9868939f, - 1.4455698f, - -15.262972f, - -10.457437f, - -8.4519463f, - -4.4281874f, - 10.212368f, - -0.28622282f, - 12.087646f, - 6.5218501f, - 8.1785011f, - 13.985523f, - -8.2068987f, - 5.4260745f, - - -10.808288f, - -10.887209f, - 7.8799553f, - -4.6565766f, - -1.6700006f, - -0.033962168f, - 7.4929152f, - 10.944146f, - 8.640254f, - -18.862164f, - -3.1202927f, - -6.3049207f, - 3.4508536f, - 11.722519f, - 3.3550568f, - -5.4888172f, - - -2.0828252f, - -13.241742f, - 2.9868939f, - 1.4455698f, - -15.262972f, - -10.457437f, - -8.4519463f, - -4.4281874f, - 10.212368f, - -0.28622282f, - 12.087646f, - 6.5218501f, - 8.1785011f, - 13.985523f, - -8.2068987f, - 5.4260745f, - }; - - data.broadcast_rel_pos_bias = false; - } - - { - data.fp16_output_data = { - 1.0419922f, - 0.13000488f, - 0.10528564f, - -0.86230469f, - -0.45336914f, - 0.39013672f, - -0.048858643f, - 0.10571289f, - - 0.97265625f, - 0.17590332f, - 0.015625f, - -0.79248047f, - -0.40917969f, - 0.31933594f, - 0.082763672f, - 0.12976074f, - - 1.1455078f, - 0.13134766f, - 0.15014648f, - -0.87451172f, - -0.46142578f, - 0.40161133f, - 0.04309082f, - 0.042663574f, - - 1.0009766f, - 0.17004395f, - 0.033752441f, - -0.80078125f, - -0.41625977f, - 0.33349609f, - 0.080383301f, - 0.11846924f, - - 1.0419922f, - 0.13000488f, - 0.10528564f, - -0.86230469f, - -0.45336914f, - 0.39013672f, - -0.048858643f, - 0.10571289f, - - 0.97265625f, - 0.17590332f, - 0.015625f, - -0.79248047f, - -0.40917969f, - 0.31933594f, - 0.082763672f, - 0.12976074f, - - 1.1455078f, - 0.13134766f, - 0.15014648f, - -0.87451172f, - -0.46142578f, - 0.40161133f, - 0.04309082f, - 0.042663574f, - - 1.0009766f, - 0.17004395f, - 0.033752441f, - -0.80078125f, - -0.41625977f, - 0.33349609f, - 0.080383301f, - 0.11846924f, - }; - } - - { - data.fp32_output_data = {}; - } - + LoadTensor("AttentionDataCutlassRelPosBias.query_data", data.query_data); + LoadTensor("AttentionDataCutlassRelPosBias.key_data", data.key_data); + LoadTensor("AttentionDataCutlassRelPosBias.value_data", data.value_data); + LoadTensor("AttentionDataCutlassRelPosBias.bias_data", data.bias_data); + LoadTensor("AttentionDataCutlassRelPosBias.rel_pos_bias_data", data.rel_pos_bias_data); + data.broadcast_rel_pos_bias = false; + LoadTensor("AttentionDataCutlassRelPosBias.fp16_output_data", data.fp16_output_data); + data.fp32_output_data = {}; data.is_static_kv = false; } @@ -3871,381 +346,13 @@ void GetCrossAttentionData_DiffSequenceLengths(AttentionTestData& data) { AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - data.query_data = { - 0.19646919f, - -0.21386067f, - -0.27314855f, - 0.05131477f, - 0.21946897f, - -0.07689354f, - 0.4807642f, - 0.18482974f, - -0.0190681f, - -0.10788248f, - -0.15682198f, - 0.22904971f, - -0.06142776f, - -0.4403221f, - -0.10195574f, - 0.23799541f, - - -0.31750827f, - -0.32454824f, - 0.03155137f, - 0.03182759f, - 0.13440096f, - 0.34943179f, - 0.22445532f, - 0.11102351f, - 0.22244338f, - -0.17704109f, - -0.13821134f, - -0.27173677f, - -0.20628595f, - 0.13097612f, - -0.40789506f, - -0.06629883f, - }; - data.key_data = { - -0.06913724f, - -0.0063149f, - -0.07416971f, - -0.18773878f, - -0.07364869f, - 0.39338916f, - 0.44416002f, - 0.00183668f, - 0.12395295f, - -0.3843816f, - -0.18271452f, - -0.08517379f, - 0.36630916f, - -0.24954463f, - -0.01696574f, - 0.48555979f, - - 0.01948512f, - 0.11289453f, - -0.37937133f, - 0.3263408f, - 0.10306013f, - 0.04506801f, - -0.15723617f, - -0.19587921f, - -0.08297779f, - 0.18130077f, - 0.37545684f, - 0.01042234f, - 0.16931378f, - 0.08593655f, - 0.1249035f, - 0.17468905f, - - 0.34234244f, - -0.41680501f, - 0.26368284f, - -0.25633363f, - -0.30577704f, - 0.07245696f, - -0.40428748f, - 0.38532683f, - 0.12724897f, - 0.22341636f, - -0.48387079f, - 0.09443188f, - 0.05678519f, - -0.34104036f, - -0.34692948f, - 0.19552953f, - - -0.18123357f, - 0.1919703f, - 0.05438325f, - -0.11104943f, - 0.42513249f, - 0.34167f, - -0.14260243f, - -0.45640854f, - -0.19523193f, - -0.10181432f, - 0.20495883f, - 0.49535848f, - -0.14408513f, - 0.26254781f, - 0.09317692f, - 0.1917018f, - }; - data.value_data = { - -0.34887255f, - -0.10112371f, - -0.2591441f, - -0.15654399f, - 0.01312815f, - 0.16662455f, - -0.39409151f, - -0.36910505f, - -0.17801939f, - 0.16156434f, - 0.34650623f, - 0.05325734f, - 0.35445249f, - -0.11516219f, - -0.1832121f, - -0.14573532f, - - -0.32891817f, - 0.32911263f, - -0.16132915f, - 0.05237008f, - 0.07855147f, - 0.02153306f, - -0.49731194f, - 0.48834542f, - 0.40534158f, - -0.29236414f, - -0.20751059f, - 0.02001015f, - 0.40191137f, - 0.48363088f, - -0.24245794f, - 0.06435904f, - - 0.30696868f, - -0.10562995f, - 0.23107304f, - -0.33893099f, - 0.10069857f, - 0.36586446f, - 0.48352161f, - -0.42063421f, - -0.07165273f, - -0.29545714f, - -0.04936351f, - 0.04776357f, - -0.40667329f, - -0.20313922f, - 0.42758424f, - 0.06900373f, - - -0.042588f, - 0.25352599f, - 0.24186215f, - -0.45142097f, - 0.2086974f, - 0.33924335f, - -0.33406212f, - 0.28099794f, - -0.21346338f, - -0.19353025f, - 0.16526147f, - -0.38860783f, - 0.16487245f, - 0.38785679f, - 0.19631127f, - -0.05967212f, - }; - data.bias_data = { - -0.06178562f, - 0.2650961f, - 0.065642f, - -0.41509584f, - 0.08267109f, - 0.3148437f, - -0.16293362f, - 0.42757658f, - 0.250717f, - 0.07406383f, - 0.25164399f, - -0.42085104f, - 0.35938908f, - 0.32150411f, - 0.40987166f, - -0.3713688f, - -0.41821991f, - -0.36158443f, - -0.10062129f, - -0.07569314f, - 0.06221838f, - -0.37775645f, - -0.2986005f, - 0.31164435f, - }; - - data.fp32_output_data = { - -0.53803939f, - -0.33528122f, - -0.16753256f, - -0.084826469f, - 0.28213754f, - -0.23802593f, - -0.61857146f, - 0.29926175f, - -0.53170669f, - -0.33900675f, - -0.17392565f, - -0.084655531f, - 0.28832543f, - -0.24704586f, - -0.61680299f, - 0.31617802f, - - -0.41967732f, - -0.43735462f, - 0.051356006f, - -0.36559904f, - 0.093453586f, - -0.13974363f, - -0.10689265f, - 0.27119368f, - -0.40707609f, - -0.44006824f, - 0.048184391f, - -0.35585383f, - 0.081379525f, - -0.14954941f, - -0.086910933f, - 0.25871021f, - }; - - data.present_key_data = { - 0.18157977f, - 0.067748934f, - 0.17747428f, - -0.60858983f, - 0.37466997f, - -0.31031775f, - 0.068929464f, - -0.50602484f, - 0.27020213f, - 0.18695836f, - -0.12772733f, - -0.094510257f, - 0.16773923f, - 0.2553646f, - 0.62710083f, - -0.4104287f, - - 0.28574038f, - 0.71489328f, - 0.85403168f, - -0.36953211f, - 0.72569823f, - 0.071959481f, - 0.39290592f, - 0.114191f, - 0.46244919f, - 0.36657214f, - 0.25263548f, - -0.56724799f, - 0.52870286f, - 0.40744066f, - 0.53477514f, - -0.19667974f, - - 0.59305942f, - -0.34274116f, - 0.51532686f, - -0.6771847f, - 0.37796599f, - 0.2974802f, - -0.23222682f, - -0.32641917f, - 0.069483444f, - 0.26603413f, - 0.30602723f, - -0.53190047f, - 0.055485085f, - -0.027750492f, - 0.45660281f, - 0.074507415f, - - 0.053612024f, - 0.39396107f, - 0.0055841804f, - 0.013958037f, - 0.41617426f, - -0.019536257f, - 0.062942177f, - -0.17583926f, - 0.78452158f, - 0.66317415f, - 0.26726925f, - -0.82777733f, - 0.21530394f, - 0.58405197f, - 0.5030486f, - -0.179667f, - }; - data.present_value_data = { - -0.76709247f, - -0.46270815f, - -0.35976538f, - -0.23223713f, - -0.59623933f, - -0.20002009f, - 0.24588495f, - -0.022435799f, - -0.74713808f, - -0.032471806f, - -0.26195043f, - -0.023323059f, - -0.012878358f, - -0.65394855f, - -0.30813187f, - -0.055682987f, - - 0.075346529f, - -0.2111319f, - -0.69269204f, - -0.057460696f, - 0.41667086f, - -0.49291864f, - -0.4818126f, - 0.16590902f, - 0.14076985f, - -0.35622337f, - -0.79591244f, - 0.79998976f, - 0.46412975f, - 0.10587442f, - -0.54105842f, - 0.37600338f, - - -0.11125124f, - -0.46721438f, - 0.13045174f, - -0.41462412f, - -0.48987266f, - -0.65704155f, - -0.14998481f, - -0.027929567f, - -0.46080792f, - -0.10805842f, - 0.14124086f, - -0.52711409f, - -0.63168329f, - -0.55511469f, - 0.064640187f, - -0.46430096f, - - 0.16291694f, - -0.011891991f, - 0.18492112f, - -0.10898986f, - -0.34445491f, - -0.58089566f, - 0.12898374f, - 0.38064808f, - 0.27091578f, - -0.038513094f, - -0.63266265f, - 0.59264231f, - 0.22709084f, - 0.010100335f, - -0.10228923f, - 0.25197223f, - }; - + LoadTensor("CrossAttentionData_DiffSequenceLengths.query_data", data.query_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.key_data", data.key_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.value_data", data.value_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.fp32_output_data", data.fp32_output_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.present_key_data", data.present_key_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths.present_value_data", data.present_value_data); data.is_static_kv = true; } @@ -4265,101 +372,24 @@ void GetCrossAttentionData_DiffSequenceLengths_HeadSize8(AttentionTestData& data AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - data.query_data = { - 0.74714613f, -2.49789214f, -0.11628322f, 1.33038604f, 0.82568336f, 0.07685500f, 2.47562003f, 2.61135578f, - 1.55278158f, -1.85635769f, 0.36962336f, 0.87219834f, 0.69827259f, 0.95257485f, -0.77894646f, 1.46218395f, - 1.29534733f, 2.14051294f, 1.09895217f, 1.39164531f, -0.01471180f, -1.40148544f, -0.50825417f, 0.26134527f, - -0.70491123f, 0.63738143f, 2.13708138f, 0.05667466f, -0.44220763f, 0.85254443f, 2.00844359f, -1.23413038f}; - data.key_data = { - 1.70455408f, 0.07344571f, 0.18893155f, -1.48390186f, -0.86155319f, 0.10993601f, -0.29869685f, 0.73800445f, - 0.94670546f, -1.36712539f, -0.41328859f, 0.88237023f, 1.62447476f, 0.80396229f, -1.38206959f, 1.62546301f, - -1.61546838f, -0.56213129f, -0.23501799f, 0.89255226f, -1.95987988f, 0.85192877f, -0.06520678f, -1.32849765f, - 2.07457638f, -0.08192353f, -2.03260493f, 0.58190948f, 2.22535419f, -0.60754669f, 1.14538383f, 0.22928622f, - -0.11596665f, -0.57144678f, -0.23428933f, -0.68404931f, -1.46875453f, 1.32763886f, 0.28525546f, -0.11347114f, - 1.63199806f, -1.44967401f, -2.54707336f, 0.78083873f, -0.19109090f, 0.59508920f, 0.58886564f, 0.81380880f, - 0.54458785f, 0.21354041f, 0.03592521f, 0.27506533f, -0.87245977f, 0.65083951f, 0.32723498f, -0.48263270f, - 1.54926634f, -0.49424326f, 0.65303659f, 1.03355420f, 1.36284590f, 0.78218406f, -1.22659552f, 2.27737451f}; - data.value_data = { - 0.20429733f, -0.57036293f, 0.22116289f, 0.07601038f, 1.79898310f, 0.62182522f, 0.48815370f, -1.59284389f, - 0.33195397f, 0.34822315f, 0.54315579f, 1.06468117f, 1.34500551f, -0.09528533f, -1.30459058f, -0.07034321f, - -1.34877563f, 1.58868146f, -1.44948101f, 0.74792957f, 0.91922742f, -0.56811053f, 0.59939134f, -1.10749292f, - 1.36371183f, -0.89673072f, -0.28341034f, 0.93497890f, 1.62986696f, -0.83026254f, -0.20963377f, -2.14284325f, - -0.95242530f, 0.37379366f, 1.17815948f, -0.55676895f, 0.74420613f, 0.58715403f, -0.43127203f, 0.62706453f, - 0.50881875f, 2.14387321f, 0.85787302f, 2.32273459f, -0.04902139f, -0.04061748f, 1.55004728f, -0.25090796f, - -1.05647933f, -0.87152874f, 0.70491379f, -0.44258183f, 0.26371828f, 1.58179390f, 0.02976498f, 0.20476237f, - 1.20772719f, -0.99407929f, -0.15339416f, 0.54562038f, 1.29705775f, -0.28651321f, -0.90150839f, -1.09473300f}; - - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, -0.34948170f, -0.19608477f, 0.19725692f, 0.39987487f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, -0.23178342f, -0.13692456f, -0.04889601f, 0.48739988f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, 0.27376485f, -0.38174152f, -0.43700469f, 0.38040614f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f, 0.07120579f, -0.08055863f, 0.12095112f, -0.27988660f, - -0.10567203f, 0.26791072f, -0.08976898f, 0.31341976f, 0.06027532f, 0.14307594f, 0.31587386f, 0.16180152f, - 0.34785229f, 0.00531715f, -0.35168743f, -0.11641458f, 0.39196932f, 0.44535065f, 0.43545735f, 0.15593112f}; - - data.fp32_output_data = { - -0.73531479f, 0.17652693f, 0.43294340f, 0.10832195f, 1.06569219f, 0.84791648f, 0.37950000f, -0.19036117f, - 1.14446115f, -0.09822676f, -0.12345937f, 0.85349751f, 1.55650973f, 0.24238834f, -0.30006421f, -0.48439008f, - - -0.55764329f, -0.13255559f, 0.21757828f, 0.22631887f, 1.18009710f, 0.97638327f, 0.58746934f, -0.60751349f, - 1.29570508f, -0.01765576f, -0.19382195f, 1.03120971f, 1.47274101f, 0.09958147f, 0.22852209f, -0.86264789f}; + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.query_data", data.query_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.key_data", data.key_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.value_data", data.value_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.bias_data", data.bias_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.fp32_output_data", data.fp32_output_data); data.fp16_output_data = data.fp32_output_data; - - data.present_key_data = { - 1.97534585f, 0.49419305f, -0.21421000f, -1.92116845f, -0.58778834f, -0.27180552f, -0.73570156f, 1.11841059f, - -1.34467649f, -0.14138395f, -0.63815951f, 0.45528567f, -1.68611503f, 0.47018725f, -0.50221145f, -0.94809151f, - 0.15482518f, -0.15069944f, -0.63743091f, -1.12131596f, -1.19498968f, 0.94589734f, -0.15174922f, 0.26693499f, - 0.81537968f, 0.63428771f, -0.36721635f, -0.16220126f, -0.59869492f, 0.26909798f, -0.10976970f, -0.10222656f, - - 0.54123628f, -1.29785502f, -0.24349773f, 1.29695082f, 1.69568062f, 0.72340369f, -1.26111841f, 1.34557641f, - 1.66910720f, -0.01265316f, -1.86281407f, 0.99649012f, 2.29656005f, -0.68810534f, 1.26633501f, -0.05060038f, - 1.22652888f, -1.38040364f, -2.37728262f, 1.19541931f, -0.11988510f, 0.51453054f, 0.70981675f, 0.53392220f, - 1.14379716f, -0.42497289f, 0.82282746f, 1.44813490f, 1.43405175f, 0.70162547f, -1.10564446f, 1.99748790f}; - data.present_value_data = { - 0.09862530f, -0.30245221f, 0.13139391f, 0.38943014f, 1.85925841f, 0.76490116f, 0.80402756f, -1.43104243f, - -1.45444763f, 1.85659218f, -1.53925002f, 1.06134939f, 0.97950274f, -0.42503458f, 0.91526520f, -0.94569141f, - -1.05809736f, 0.64170438f, 1.08839047f, -0.24334919f, 0.80448145f, 0.73022997f, -0.11539817f, 0.78886604f, - -1.16215134f, -0.60361803f, 0.61514485f, -0.12916207f, 0.32399359f, 1.72486985f, 0.34563884f, 0.36656389f, - - 0.67980623f, 0.35354030f, 0.19146836f, 0.94826663f, 1.73697484f, 0.35006532f, -0.86913323f, 0.08558790f, - 1.71156406f, -0.89141357f, -0.63509774f, 0.81856430f, 2.02183628f, -0.38491189f, 0.22582358f, -1.98691213f, - 0.85667104f, 2.14919043f, 0.50618559f, 2.20632005f, 0.34294793f, 0.40473318f, 1.98550463f, -0.09497684f, - 1.55557942f, -0.98876214f, -0.50508159f, 0.42920581f, 1.68902707f, 0.15883744f, -0.46605104f, -0.93880188f}; - + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.present_key_data", data.present_key_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8.present_value_data", data.present_value_data); data.is_static_kv = true; } void GetCrossAttentionData_DiffSequenceLengths_HeadSize8_NoBias(AttentionTestData& data) { GetCrossAttentionData_DiffSequenceLengths_HeadSize8(data); data.bias_data.clear(); - data.fp32_output_data = { - -0.65824336f, -0.13227919f, 0.50652772f, -0.20617434f, 0.96178705f, 0.75033671f, 0.07374202f, -0.33853477f, - 0.79871416f, -0.14487229f, 0.21765450f, 0.94517386f, 1.19351113f, -0.20844331f, -0.78461820f, -0.64874089f, - - -0.51557893f, -0.43041292f, 0.32726392f, -0.11220890f, 1.03794634f, 0.89304829f, 0.25361922f, -0.68402284f, - 0.98060286f, -0.14295936f, 0.11289610f, 1.09369516f, 1.15080333f, -0.37929729f, -0.27804646f, -1.09627187f}; + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8_NoBias.fp32_output_data", data.fp32_output_data); data.fp16_output_data = data.fp32_output_data; - data.present_key_data = { - 1.70455408f, 0.07344571f, 0.18893155f, -1.48390186f, -0.86155319f, 0.10993601f, -0.29869685f, 0.73800445f, - -1.61546838f, -0.56213129f, -0.23501799f, 0.89255226f, -1.95987988f, 0.85192877f, -0.06520678f, -1.32849765f, - -0.11596665f, -0.57144678f, -0.23428933f, -0.68404931f, -1.46875453f, 1.32763886f, 0.28525546f, -0.11347114f, - 0.54458785f, 0.21354041f, 0.03592521f, 0.27506533f, -0.87245977f, 0.65083951f, 0.32723498f, -0.48263270f, - - 0.94670546f, -1.36712539f, -0.41328859f, 0.88237023f, 1.62447476f, 0.80396229f, -1.38206959f, 1.62546301f, - 2.07457638f, -0.08192353f, -2.03260493f, 0.58190948f, 2.22535419f, -0.60754669f, 1.14538383f, 0.22928622f, - 1.63199806f, -1.44967401f, -2.54707336f, 0.78083873f, -0.19109090f, 0.59508920f, 0.58886564f, 0.81380880f, - 1.54926634f, -0.49424326f, 0.65303659f, 1.03355420f, 1.36284590f, 0.78218406f, -1.22659552f, 2.27737451f}; - data.present_value_data = { - 0.20429733f, -0.57036293f, 0.22116289f, 0.07601038f, 1.79898310f, 0.62182522f, 0.48815370f, -1.59284389f, - -1.34877563f, 1.58868146f, -1.44948101f, 0.74792957f, 0.91922742f, -0.56811053f, 0.59939134f, -1.10749292f, - -0.95242530f, 0.37379366f, 1.17815948f, -0.55676895f, 0.74420613f, 0.58715403f, -0.43127203f, 0.62706453f, - -1.05647933f, -0.87152874f, 0.70491379f, -0.44258183f, 0.26371828f, 1.58179390f, 0.02976498f, 0.20476237f, - - 0.33195397f, 0.34822315f, 0.54315579f, 1.06468117f, 1.34500551f, -0.09528533f, -1.30459058f, -0.07034321f, - 1.36371183f, -0.89673072f, -0.28341034f, 0.93497890f, 1.62986696f, -0.83026254f, -0.20963377f, -2.14284325f, - 0.50881875f, 2.14387321f, 0.85787302f, 2.32273459f, -0.04902139f, -0.04061748f, 1.55004728f, -0.25090796f, - 1.20772719f, -0.99407929f, -0.15339416f, 0.54562038f, 1.29705775f, -0.28651321f, -0.90150839f, -1.09473300f}; - + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8_NoBias.present_key_data", data.present_key_data); + LoadTensor("CrossAttentionData_DiffSequenceLengths_HeadSize8_NoBias.present_value_data", data.present_value_data); data.is_static_kv = true; } @@ -4379,219 +409,15 @@ void GetSelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias(AttentionTestDa AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - data.query_data = { - 0.19646919f, - -0.21386067f, - -0.27314855f, - 0.05131477f, - 0.21946897f, - -0.07689354f, - 0.4807642f, - 0.18482974f, - -0.0190681f, - -0.10788248f, - -0.15682198f, - 0.22904971f, - -0.06142776f, - -0.4403221f, - -0.10195574f, - 0.23799541f, - }; - data.key_data = { - -0.31750827f, - -0.32454824f, - 0.03155137f, - 0.03182759f, - 0.13440096f, - 0.34943179f, - 0.22445532f, - 0.11102351f, - 0.22244338f, - -0.17704109f, - -0.13821134f, - -0.27173677f, - -0.20628595f, - 0.13097612f, - -0.40789506f, - -0.06629883f, - }; - data.value_data = { - -0.06913724f, - -0.0063149f, - -0.07416971f, - -0.18773878f, - -0.07364869f, - 0.39338916f, - 0.44416002f, - 0.00183668f, - 0.12395295f, - -0.3843816f, - -0.18271452f, - -0.08517379f, - 0.36630916f, - -0.24954463f, - -0.01696574f, - 0.48555979f, - }; - - data.bias_data = { - 0.01948512f, - 0.11289453f, - -0.37937133f, - 0.3263408f, - 0.10306013f, - 0.04506801f, - -0.15723617f, - -0.19587921f, - -0.08297779f, - 0.18130077f, - 0.37545684f, - 0.01042234f, - 0.16931378f, - 0.08593655f, - 0.1249035f, - 0.17468905f, - 0.34234244f, - -0.41680501f, - 0.26368284f, - -0.25633363f, - -0.30577704f, - 0.07245696f, - -0.40428748f, - 0.38532683f, - }; - - data.past_key_data = { - 0.12724897f, - 0.22341636f, - -0.48387079f, - 0.09443188f, - 0.05678519f, - -0.34104036f, - -0.34692948f, - 0.19552953f, - -0.18123357f, - 0.1919703f, - 0.05438325f, - -0.11104943f, - 0.42513249f, - 0.34167f, - -0.14260243f, - -0.45640854f, - }; - data.past_value_data = { - -0.19523193f, - -0.10181432f, - 0.20495883f, - 0.49535848f, - -0.14408513f, - 0.26254781f, - 0.09317692f, - 0.1917018f, - -0.34887255f, - -0.10112371f, - -0.2591441f, - -0.15654399f, - 0.01312815f, - 0.16662455f, - -0.39409151f, - -0.36910505f, - }; - - data.fp32_output_data = { - -0.00033577532f, - -0.23549549f, - 0.19853255f, - 0.10450245f, - -0.26995566f, - 0.37128073f, - 0.064667389f, - 0.29624334f, - 0.040147364f, - -0.43521237f, - -0.096833363f, - -0.24481347f, - 0.037364807f, - -0.0091082826f, - -0.40797871f, - 0.26487666f, - }; - - data.present_key_data = { - 0.12724897f, - 0.22341636f, - -0.4838708f, - 0.094431877f, - -0.40048605f, - -0.14324747f, - 0.4070082f, - 0.042249933f, - - 0.056785189f, - -0.34104037f, - -0.34692949f, - 0.19552954f, - 0.30371475f, - 0.43536833f, - 0.34935883f, - 0.28571257f, - - -0.18123357f, - 0.1919703f, - 0.054383252f, - -0.11104943f, - 0.1394656f, - 0.0042596906f, - 0.2372455f, - -0.26131442f, - - 0.42513248f, - 0.34167001f, - -0.14260243f, - -0.45640853f, - -0.03697218f, - 0.21691267f, - -0.28299156f, - 0.10839023f, - }; - data.present_value_data = { - -0.19523193f, - -0.10181432f, - 0.20495883f, - 0.49535847f, - 0.27320519f, - -0.4231199f, - 0.18951313f, - -0.4440724f, - - -0.14408512f, - 0.26254782f, - 0.093176924f, - 0.1917018f, - -0.37942573f, - 0.46584612f, - 0.039872527f, - 0.38716352f, - - -0.34887254f, - -0.10112371f, - -0.2591441f, - -0.15654399f, - 0.46629539f, - -0.80118656f, - 0.08096832f, - -0.34150741f, - - 0.01312815f, - 0.16662455f, - -0.39409152f, - -0.36910504f, - 0.060532123f, - -0.17708766f, - -0.42125323f, - 0.87088662f, - }; - + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.query_data", data.query_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.key_data", data.key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.value_data", data.value_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.bias_data", data.bias_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.past_key_data", data.past_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.past_value_data", data.past_value_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.fp32_output_data", data.fp32_output_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.present_key_data", data.present_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_NoMask_NoRelPosBias.present_value_data", data.present_value_data); data.is_static_kv = false; } @@ -4611,112 +437,38 @@ void GetSelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias(Atten AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - data.query_data = { - 1.29534733f, 2.14051294f, 1.09895217f, 1.39164531f, -0.01471180f, -1.40148544f, -0.50825417f, 0.26134527f, - -0.70491123f, 0.63738143f, 2.13708138f, 0.05667466f, -0.44220763f, 0.85254443f, 2.00844359f, -1.23413038f, - -0.08030051f, -1.25450790f, -0.89664006f, -0.69433510f, 0.20943037f, 1.41880298f, 1.42875051f, 0.79920006f, - 1.57896936f, -1.13204634f, -0.61002654f, 0.43365243f, 0.22888106f, -0.38688308f, -0.45924744f, 0.99473029f}; - - data.key_data = { - 0.37680483f, 0.15317714f, 0.05767500f, 0.37780648f, -2.27755547f, 0.89294612f, -0.85582626f, 0.54963046f, - 1.67390800f, -1.06330085f, -2.99566054f, 0.68927419f, 1.66056263f, -0.77022851f, 0.15417719f, 0.94860524f, - -1.84928346f, -0.52135336f, 0.70491475f, 0.37400877f, 0.55338752f, 0.52915680f, 0.52876079f, -0.55780333f, - -1.49814773f, 0.18675917f, 0.31246936f, -1.32707596f, 0.42132780f, -1.69121027f, 0.20342645f, -0.34370381f}; - - data.value_data = { - 0.60890561f, -0.88021755f, 1.63002241f, 0.86171651f, 1.80559230f, 1.26110435f, -0.97890180f, -1.60215497f, - -0.79229754f, 1.07830989f, -0.85298145f, 2.76264572f, 0.01659799f, -1.49499071f, 0.85316724f, -2.56763911f, - 0.53017867f, 1.31909978f, -1.10940945f, 0.68858552f, -1.07115889f, -2.34016919f, 0.48310637f, -0.05351824f, - -0.08850761f, -0.56362265f, 0.05224326f, -2.47377181f, 0.44249821f, -0.10389519f, -0.46113095f, 2.81619215f}; - - data.bias_data = { - -0.38124341f, 0.02696526f, -0.11914945f, -0.43795273f, -0.34948170f, -0.19608477f, 0.19725692f, 0.39987487f, - 0.04772711f, -0.03419551f, -0.30606642f, 0.42656231f, -0.23178342f, -0.13692456f, -0.04889601f, 0.48739988f, - 0.27079183f, 0.42074734f, -0.40314156f, -0.43726659f, 0.27376485f, -0.38174152f, -0.43700469f, 0.38040614f, - -0.40546918f, 0.06927037f, 0.16979086f, 0.41458064f, 0.07120579f, -0.08055863f, 0.12095112f, -0.27988660f, - -0.10567203f, 0.26791072f, -0.08976898f, 0.31341976f, 0.06027532f, 0.14307594f, 0.31587386f, 0.16180152f, - 0.34785229f, 0.00531715f, -0.35168743f, -0.11641458f, 0.39196932f, 0.44535065f, 0.43545735f, 0.15593112f}; - - data.past_key_data = { - -1.00657940f, -0.46509427f, -1.65118766f, -0.17705369f, 1.71204090f, 0.53921354f, -1.67056096f, 0.42517155f, - -2.00129080f, 1.26244307f, 0.28864837f, 1.38792157f, -0.59647840f, -1.18904924f, 0.58950418f, -2.26774645f, - 1.88496518f, 0.59231639f, 0.33360308f, -1.23532701f, 0.10543400f, -1.77481365f, -0.79397631f, -0.22495472f, - -0.26800078f, -0.20456636f, 1.43141091f, 1.55566478f, -0.22702518f, 1.75312757f, -1.29037595f, -0.95538902f}; - data.past_value_data = { - 3.18056512f, 0.13370860f, -2.20253444f, 2.30826044f, 0.86762893f, -1.91499686f, 2.18277764f, 0.53384149f, - -0.43230706f, 0.49148068f, -0.29957789f, -3.56583714f, -1.46747136f, -0.40299624f, 1.78018796f, 2.84104395f, - -0.68692255f, 1.25688624f, -0.42734757f, -1.03185725f, 0.47858545f, 1.18466282f, -1.06095874f, -0.63918531f, - 1.41408277f, 0.74389833f, 0.89590931f, 1.06388271f, 1.29734015f, 0.42640167f, -0.99740052f, -2.79366398f}; - - data.fp32_output_data = { - 0.72723210f, -0.54989153f, 1.22711349f, 1.26993895f, 1.78235006f, 1.12648177f, -0.42493403f, -1.27518260f, - -0.43240935f, 0.49647018f, -0.30720428f, -3.51349354f, -1.45166361f, -0.40844491f, 1.77604592f, 2.79678369f, - 0.25752395f, 1.53741217f, -1.08321750f, 0.69643497f, -0.78710371f, -1.68901348f, 0.51954043f, -0.00401744f, - 1.11207914f, 0.40332735f, 0.58328331f, 0.10821819f, 1.17628312f, 0.40418532f, -0.74326056f, -1.28571272f}; + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.query_data", data.query_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.key_data", data.key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.value_data", data.value_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.bias_data", data.bias_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.past_key_data", + data.past_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.past_value_data", + data.past_value_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.fp32_output_data", + data.fp32_output_data); data.fp16_output_data = data.fp32_output_data; - - data.present_key_data = { - -1.00657940f, -0.46509427f, -1.65118766f, -0.17705369f, 1.71204090f, 0.53921354f, -1.67056096f, 0.42517155f, - 0.64759666f, 0.57392448f, -0.34546655f, -0.05946010f, -2.00379062f, 0.51120460f, -1.29283094f, 0.93003660f, - -2.00129080f, 1.26244307f, 0.28864837f, 1.38792157f, -0.59647840f, -1.18904924f, 0.58950418f, -2.26774645f, - 1.26843882f, -0.99403048f, -2.82586956f, 1.10385489f, 1.73176837f, -0.85078716f, 0.27512830f, 0.66871864f, - 1.88496518f, 0.59231639f, 0.33360308f, -1.23532701f, 0.10543400f, -1.77481365f, -0.79397631f, -0.22495472f, - -1.57849169f, -0.10060602f, 0.30177319f, -0.06325781f, 0.82715237f, 0.14741528f, 0.09175611f, -0.17739719f, - -0.26800078f, -0.20456636f, 1.43141091f, 1.55566478f, -0.22702518f, 1.75312757f, -1.29037595f, -0.95538902f, - -1.90361691f, 0.25602955f, 0.48226023f, -0.91249532f, 0.49253359f, -1.77176893f, 0.32437757f, -0.62359041f}; - data.present_value_data = { - 3.18056512f, 0.13370860f, -2.20253444f, 2.30826044f, 0.86762893f, -1.91499686f, 2.18277764f, 0.53384149f, - 0.50323355f, -0.61230683f, 1.54025340f, 1.17513633f, 1.86586761f, 1.40418029f, -0.66302794f, -1.44035339f, - -0.43230706f, 0.49148068f, -0.29957789f, -3.56583714f, -1.46747136f, -0.40299624f, 1.78018796f, 2.84104395f, - -0.44444525f, 1.08362699f, -1.20466888f, 2.64623117f, 0.40856731f, -1.04964006f, 1.28862453f, -2.41170788f, - -0.68692255f, 1.25688624f, -0.42734757f, -1.03185725f, 0.47858545f, 1.18466282f, -1.06095874f, -0.63918531f, - 0.42450663f, 1.58701050f, -1.19917846f, 1.00200534f, -1.01088357f, -2.19709325f, 0.79898024f, 0.10828328f, - 1.41408277f, 0.74389833f, 0.89590931f, 1.06388271f, 1.29734015f, 0.42640167f, -0.99740052f, -2.79366398f, - 0.25934470f, -0.55830550f, -0.29944417f, -2.59018636f, 0.83446753f, 0.34145546f, -0.02567360f, 2.97212315f}; - + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.present_key_data", + data.present_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias.present_value_data", + data.present_value_data); data.is_static_kv = false; } void GetSelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias(AttentionTestData& data) { GetSelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias(data); data.bias_data.clear(); - data.past_key_data = { - -1.27737117f, -0.88584161f, -1.24804604f, 0.26021290f, 1.43827605f, 0.92095506f, -1.23355627f, 0.04476542f, - -1.59582162f, 1.19317269f, 0.11885749f, 0.97334087f, -0.66768420f, -1.10849059f, 0.46855307f, -1.98785996f, - 1.61417341f, 0.17156902f, 0.73674464f, -0.79806042f, -0.16833085f, -1.39307213f, -0.35697165f, -0.60536087f, - 0.13746840f, -0.27383673f, 1.26162004f, 1.14108407f, -0.29823098f, 1.83368623f, -1.41132712f, -0.67550242f}; - data.past_value_data = { - 3.28623724f, -0.13420212f, -2.11276555f, 1.99484074f, 0.80735362f, -2.05807281f, 1.86690378f, 0.37204000f, - -0.78015935f, 0.48616353f, 0.05210955f, -3.44942260f, -1.85944068f, -0.84834689f, 1.34473062f, 2.68511271f, - -0.58125055f, 0.98897558f, -0.33757859f, -1.34527707f, 0.41831014f, 1.04158688f, -1.37683260f, -0.80098683f, - 1.06623054f, 0.73858118f, 1.24759674f, 1.18029726f, 0.90537083f, -0.01894896f, -1.43285787f, -2.94959521f}; - - data.fp32_output_data = { - 0.89556247f, -0.80034304f, 1.22928894f, 0.98303795f, 1.69871271f, 0.90572613f, -0.67420667f, -1.39078152f, - -0.78021139f, 0.48869953f, 0.04823331f, -3.42281842f, -1.85140634f, -0.85111630f, 1.34262550f, 2.66261697f, - 0.34449580f, 1.26394701f, -0.98046219f, 0.34879467f, -0.82231814f, -1.77519011f, 0.17237240f, -0.17839541f, - 0.72679031f, 0.35579273f, 0.89621741f, 0.10616791f, 0.76930743f, -0.04391927f, -1.14721453f, -1.25471735f}; + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias.past_key_data", + data.past_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias.past_value_data", + data.past_value_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias.fp32_output_data", + data.fp32_output_data); data.fp16_output_data = data.fp32_output_data; - - data.present_key_data = { - -1.27737117f, -0.88584161f, -1.24804604f, 0.26021290f, 1.43827605f, 0.92095506f, -1.23355627f, 0.04476542f, - 0.37680483f, 0.15317714f, 0.05767500f, 0.37780648f, -2.27755547f, 0.89294612f, -0.85582626f, 0.54963046f, - -1.59582162f, 1.19317269f, 0.11885749f, 0.97334087f, -0.66768420f, -1.10849059f, 0.46855307f, -1.98785996f, - 1.67390800f, -1.06330085f, -2.99566054f, 0.68927419f, 1.66056263f, -0.77022851f, 0.15417719f, 0.94860524f, - 1.61417341f, 0.17156902f, 0.73674464f, -0.79806042f, -0.16833085f, -1.39307213f, -0.35697165f, -0.60536087f, - -1.84928346f, -0.52135336f, 0.70491475f, 0.37400877f, 0.55338752f, 0.52915680f, 0.52876079f, -0.55780333f, - 0.13746840f, -0.27383673f, 1.26162004f, 1.14108407f, -0.29823098f, 1.83368623f, -1.41132712f, -0.67550242f, - -1.49814773f, 0.18675917f, 0.31246936f, -1.32707596f, 0.42132780f, -1.69121027f, 0.20342645f, -0.34370381f}; - data.present_value_data = { - 3.28623724f, -0.13420212f, -2.11276555f, 1.99484074f, 0.80735362f, -2.05807281f, 1.86690378f, 0.37204000f, - 0.60890561f, -0.88021755f, 1.63002241f, 0.86171651f, 1.80559230f, 1.26110435f, -0.97890180f, -1.60215497f, - -0.78015935f, 0.48616353f, 0.05210955f, -3.44942260f, -1.85944068f, -0.84834689f, 1.34473062f, 2.68511271f, - -0.79229754f, 1.07830989f, -0.85298145f, 2.76264572f, 0.01659799f, -1.49499071f, 0.85316724f, -2.56763911f, - -0.58125055f, 0.98897558f, -0.33757859f, -1.34527707f, 0.41831014f, 1.04158688f, -1.37683260f, -0.80098683f, - 0.53017867f, 1.31909978f, -1.10940945f, 0.68858552f, -1.07115889f, -2.34016919f, 0.48310637f, -0.05351824f, - 1.06623054f, 0.73858118f, 1.24759674f, 1.18029726f, 0.90537083f, -0.01894896f, -1.43285787f, -2.94959521f, - -0.08850761f, -0.56362265f, 0.05224326f, -2.47377181f, 0.44249821f, -0.10389519f, -0.46113095f, 2.81619215f}; - + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias.present_key_data", + data.present_key_data); + LoadTensor("SelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias.present_value_data", + data.present_value_data); data.is_static_kv = false; } @@ -4736,1682 +488,54 @@ void GetCrossAttentionData_WithPastPassedInDirectly_NoMask(AttentionTestData& da AttentionKernelType::AttentionKernel_CutlassMemoryEfficientAttention, }; - data.query_data = { - -0.10939738f, -0.11916742f, -0.23157823f, -0.12894472f, - -0.02661306f, 0.26251313f, 0.30725253f, -0.34759378f, - -0.11695808f, -0.13129434f, -0.17031054f, -0.14986445f, - -0.02826184f, 0.2797631f, 0.27337456f, -0.44312602f}; - data.past_key_data = { - 0.5967375f, 0.5966938f, 0.48602432f, 0.5341031f, - 0.55797786f, 0.5663399f, 0.57087725f, 0.6240304f, - 0.5352563f, 0.5648297f, 0.4972945f, 0.56637144f, + LoadTensor("CrossAttentionData_WithPastPassedInDirectly_NoMask.query_data", data.query_data); + LoadTensor("CrossAttentionData_WithPastPassedInDirectly_NoMask.past_key_data", data.past_key_data); + LoadTensor("CrossAttentionData_WithPastPassedInDirectly_NoMask.past_value_data", data.past_value_data); + LoadTensor("CrossAttentionData_WithPastPassedInDirectly_NoMask.fp32_output_data", data.fp32_output_data); + data.fp16_output_data = data.fp32_output_data; +} - 0.44123724f, 0.35872823f, 0.32176313f, 0.4490301f, - 0.3643952f, 0.51968557f, 0.50137347f, 0.5743993f, - 0.3905106f, 0.4741712f, 0.40881708f, 0.47243845f}; - data.past_value_data = { - 0.40251260f, 0.55487730f, 0.49565578f, 0.42683450f, - 0.44379145f, 0.58945787f, 0.54852820f, 0.43376005f, - 0.44116694f, 0.44007313f, 0.40293324f, 0.53202707f, +void GetCausal_EmptyPastState(std::vector& input, std::vector& output, std::vector& present) { + LoadTensor("Causal_EmptyPastState.input_data", input); + LoadTensor("Causal_EmptyPastState.output_data", output); + LoadTensor("Causal_EmptyPastState.present_data", present); +} - 0.35520583f, 0.47293650f, 0.45417705f, 0.33723440f, - 0.50175804f, 0.37620395f, 0.24103148f, 0.50958070f, - 0.56803876f, 0.37866923f, 0.32273075f, 0.44389135f}; +void GetAttentionDataWithNeoXRotaryEmbedding(std::vector& input, + std::vector& weights, + std::vector& bias, + std::vector& output) { + LoadTensor("AttentionDataWithNeoXRotaryEmbedding.input", input); + LoadTensor("AttentionDataWithNeoXRotaryEmbedding.weights", weights); + LoadTensor("AttentionDataWithNeoXRotaryEmbedding.bias", bias); + LoadTensor("AttentionDataWithNeoXRotaryEmbedding.output", output); +} - data.fp32_output_data = { - 0.44753647f, - 0.52339733f, - 0.46447957f, - 0.46852112f, - 0.44769368f, - 0.5231511f, - 0.464194f, - 0.46851689f, +void GetPackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias(PackedAttentionTestData& data) { + data.hidden_size = 32; + data.v_hidden_size = 32; + data.num_heads = 1; + data.batch_size = 2; + data.sequence_length = 2; + data.kv_sequence_length = 2; - 0.43687066f, - 0.3954815f, - 0.37647754f, - 0.44443309f, - 0.43690678f, - 0.39541441f, - 0.37764412f, - 0.44382966f, - }; -} + data.token_offset = {0, 2, 3, 1}; + data.cumulative_sequence_length = {0, 1, 3}; + data.token_count = 3; -void GetAttentionDataWithNeoXRotaryEmbedding(std::vector& input, std::vector& weights, std::vector& bias, - std::vector& output) { - input = { - 0.4287963f, 0.5977035f, 0.42293033f, 0.6351057f, 0.4845531f, 0.5391439f, 0.4124713f, 0.5433049f, - 0.37774163f, 0.3180431f, 0.44363722f, 0.5182994f, 0.43589768f, 0.48627475f, 0.45227078f, 0.51325303f, - 0.59149283f, 0.6034224f, 0.56825185f, 0.47176513f, 0.66173404f, 0.49446547f, 0.5832309f, 0.27636415f, - 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0.03793691f, 0.03096287f, 0.11050637f, 0.10998675f, 0.12480867f, 0.088841766f, 0.0804085f, 0.113147214f, - -0.11442338f, 0.053937837f, -0.04511106f, -0.09592314f, -0.02383636f, 0.069052935f, 0.04716301f, -0.05178404f, - -0.03024149f, 0.085217014f, -0.121402994f, 0.015347943f, 0.022425294f, -0.07818891f, 0.078054994f, -0.1083958f, - -0.05834791f, 0.04009199f, -0.07349795f, -0.07219167f, -0.089493856f, 0.025990576f, 0.020532757f, 0.07246506f, - -0.034432396f, 0.054167867f, 0.0843644f, 0.1060082f, 0.12247771f, 0.063865885f, 0.120768756f, -0.00836885f, - 0.10737455f, -0.12000655f, -0.066089064f, -0.09552364f, 0.09734517f, -0.060768515f, 0.11830413f, 0.1221661f, - -0.07856314f, 0.043814376f, 0.002162397f, 0.005835071f, 0.013402358f, -0.052697614f, 0.12051603f, 0.11143386f, - -0.019188747f, 0.07610595f, 0.011842102f, 0.054800317f, 0.06510745f, 0.05464466f, -0.071982205f, 0.027735293f, - 0.02007015f, 0.09013231f, -0.06230253f, -0.049612865f, -0.0976035f, 0.0039717704f, 0.07875933f, 0.0059824437f, - 0.014342174f, 0.06719974f, 0.04155186f, 0.0065541416f, 0.09478274f, -0.024600789f, 0.052067786f, -0.023668855f, - 0.07919648f, 0.0666706f, 0.020469442f, -0.12470782f, -0.0055578053f, -0.086057246f, 0.051694766f, 0.07114144f, - -0.087324664f, -0.09780298f, 0.111033216f, 0.0016970783f, -0.0686499f, 0.023414046f, 0.056988567f, -0.037096992f, - -0.07404406f, -0.03129123f, 0.09924726f, -0.07421176f, 0.051687375f, 0.05500026f, -0.050002858f, -0.035964176f, - -0.009300381f, -0.09416711f, -0.11180408f, -0.026925936f, 0.079236224f, -0.053548455f, 0.04158762f, -0.07253668f, - 0.054335028f, 0.07685059f, -0.116550386f, 0.08047663f, 0.007648021f, 0.08489932f, 0.0063565224f, -0.013558909f, - 0.062186584f, 0.027359605f, 0.111387104f, 0.008492142f, 0.0926635f, 0.04966609f, 0.03609039f, 0.08157928f, - 0.022451013f, -0.020238876f, 0.12231578f, -0.049836785f, -0.049515948f, 0.031997114f, -0.10183413f, 0.0011652112f, - 0.06394687f, -0.121086136f, 0.027382448f, -0.012821287f, 0.051565826f, 0.014416143f, -0.0125038475f, 0.048808083f, - 0.025086328f, 0.0063593388f, -0.08069469f, 0.06882568f, -0.06697106f, 0.04646136f, 0.08697687f, -0.034030527f, - 0.054751158f, -0.023869723f, 0.08562763f, -0.070191875f, 0.09019026f, 0.015961125f, 0.004218504f, 0.029824317f, - 0.08514762f, -0.08592425f, 0.0642595f, 0.054575577f, -0.08613354f, 0.009840354f, 0.0032888204f, -0.090920016f, - -0.04916376f, -0.013575569f, 0.07639252f, 0.12187165f, 0.060026824f, 0.06150043f, 0.10690208f, 0.06361288f, - 0.097332284f, -0.07109025f, -0.012643233f, 0.10800016f, -0.06456825f, 0.10837218f, 0.0013162196f, 0.08441797f, - -0.1143685f, 0.040167436f, -0.016026706f, 0.053332493f, 0.09022151f, -0.12273988f, -0.033404678f, 0.11205059f, - -0.01208888f, -0.0030140132f, 0.08252995f, -0.10544956f, 0.07570286f, 0.048434198f, 0.121613264f, 0.025429755f, - -0.07472932f, -0.09557468f, -0.04835771f, 0.121463805f, -0.032501236f, 0.0067884475f, -0.077393815f, 0.108694255f, - -0.022245944f, -0.012404636f, 0.017383188f, 0.120815784f, 0.12111379f, -0.048650414f, -0.083798185f, 0.123583525f, - 0.111606196f, 0.1203351f, 0.028109416f, 0.11536527f, 0.10866012f, 0.028443366f, -0.05447565f, 0.049032032f, - 0.02061762f, 0.1157669f, -0.0077940077f, -0.118153796f, -0.113350615f, 0.05505249f, -0.041882172f, 0.057925686f, - -0.10258281f, -0.09037614f, 0.1054488f, -0.059303492f, 0.07517955f, 0.115489215f, -0.041769817f, 0.044067547f, - 0.058327496f, -0.05487314f, -0.03615266f, 0.11601317f, 0.095056474f, 0.057407066f, -0.11016603f, 0.010294333f, - 0.096548215f, -0.05726476f, 0.011792123f, 0.019032374f, -0.11002648f, 0.07365605f, 0.02415447f, 0.0829203f, - -0.10780208f, -0.07414892f, 0.074496776f, 0.049104437f, 0.059883133f, 0.0895475f, 0.0060168207f, -0.03545022f, - 0.01123184f, -0.08018194f, -0.076099426f, 0.05938296f, 0.015770048f, 0.02600509f, -0.104634404f, -0.018804625f, - -0.06444827f, 0.06952596f, -0.11891967f, 0.07561223f, 0.0881912f, -0.09313339f, 0.06665172f, -0.03877653f, - -0.021109238f, -0.0950138f, 0.040632993f, -0.046781987f, -0.10913634f, 0.056697905f, -0.078700095f, 0.076099694f, - 0.037763387f, -0.06088917f, 0.085528105f, -0.046229854f, 0.00979723f, 0.1113663f, 0.036610514f, 0.07728267f, - 0.103454694f, 0.054175317f, 0.028469935f, 0.10844749f, -0.025300667f, 0.057627216f, 0.0056156516f, 0.05524978f, - -0.010633022f, -0.11832908f, -0.123220146f, 0.085026175f, 0.109172985f, -0.0521968f, 0.024486333f, -0.07291271f, - -0.040802956f, 0.0773468f, -0.07468565f, 0.09964684f, 0.06944609f, 0.09447388f, 0.028680414f, -0.05227098f, - -0.034188926f, 0.06474827f, 0.034068793f, 0.076197445f, 0.0071588755f, 0.02210252f, -0.015157148f, -0.041274518f, - 0.039721638f, -0.0041104704f, -0.015653118f, -0.015993163f, -0.09791076f, 0.041946843f, 0.04202664f, 0.068808004f, - 0.11926198f, -0.08643682f, -0.08702189f, -0.0371003f, -0.027634531f, 0.048333406f, 0.0246934f, -0.051542178f, - -0.058001295f, 0.119721115f, 0.0058310926f, -0.026220575f, 0.11391167f, -0.09974091f, -0.030742407f, -0.109102756f, - -0.010545328f, -0.06355572f, 0.025655583f, 0.024547994f, 0.03435652f, 0.085986495f, 0.098213285f, 0.10841088f, - -0.017484605f, 0.1045932f, -0.06684981f, -0.02272904f, -0.11855188f, -0.027729899f, 0.080963165f, 0.013070375f, - 0.012285203f, -0.062388107f, -0.080192596f, 0.06567258f, -0.055504948f, -0.098769635f, -0.008021668f, 0.11364633f, - 0.11141585f, -0.019893765f, -0.06620477f, -0.0018479079f, -0.04986687f, -0.12288031f, 0.103291094f, -0.11170758f, - -0.09939325f, 0.0031500757f, 0.039072126f, 0.07819526f, -0.021386996f, 0.07164991f, -0.108162194f, 0.10669248f, - 0.016798392f, -0.031565547f, -0.00089368224f, -0.025154322f, 0.01896426f, -0.123588145f, -0.04039198f, 0.025806248f, - 0.07369381f, -0.01955527f, 0.034324422f, 0.07249893f, -0.007222444f, -0.10478635f, 0.029678345f, 0.012263432f, - -0.03602113f, -0.0820308f, 0.10400115f, 0.074464634f, -0.11038381f, 0.03313631f, 0.024632469f, 0.0046253204f, - -0.059992403f, -0.016449094f, -0.09816241f, -0.05029261f, -0.016355842f, 0.06858541f, 0.06876728f, 0.09230435f, - 0.08108127f, -0.110682994f, -0.032294348f, -0.11990692f, 0.03392738f, -0.08298041f, -0.05477166f, -0.011435077f, - 0.10570291f, -0.03953588f, 0.07989067f, -0.031246617f, -0.0014988184f, 0.108662054f, 0.05255395f, -0.028169408f, - -0.11841178f, -0.02798815f, 0.038782105f, -0.12102358f, -0.0057162493f, -0.11218251f, 0.11841786f, 0.11197908f, - 0.08845696f, 0.014620528f, -0.11858247f, -0.0007520765f, 0.08343084f, 0.093437895f, 0.085087344f, -0.004926607f, - -0.113425806f, -0.007898435f, 0.12126432f, -0.028470427f, 0.112855196f, 0.05825992f, 0.017919883f, 0.059206665f, - 0.03112097f, 0.077684835f, 0.03172362f, -0.076384336f, -0.04669325f, -0.06266852f, 0.11156085f, -0.06758098f, - -0.015924037f, 0.019525155f, 0.10438733f, 0.0021187663f, 0.082140565f, 0.051481813f, 0.05049731f, 0.05348997f}; + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias.query_data", data.query_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias.key_data", data.key_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias.value_data", data.value_data); + data.bias_data = {}; + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias.qkv_data", data.qkv_data); - bias = { - 0.012921274f, 0.015607655f, -0.0025690347f, -0.09620342f, -0.038310394f, 0.028336182f, -0.057742983f, 0.11910392f, - -0.021329686f, -0.029287532f, -0.06831166f, 0.06367178f, 0.12070382f, 0.11052747f, -0.1134135f, -0.010906458f, - -0.027275577f, -0.03126064f, -0.11263193f, 0.12486756f, 0.101218015f, -0.08797003f, 0.078801036f, -0.03685227f, - 0.11405747f, -0.00369519f, 0.06526601f, -0.007782519f, -0.037164003f, -0.11565806f, -0.0938476f, 0.11805937f, - 0.11596902f, 0.12006892f, 0.09075862f, -0.11265291f, -0.079891264f, 0.027362347f, -0.11551541f, -0.004822135f, - 0.040745273f, -0.039045155f, 0.021577373f, 0.0087329f, -0.048070773f, 0.014996886f, 0.026346415f, -0.104582444f, - 0.115239695f, 0.12411316f, -0.10270241f, -0.029949531f, -0.003467828f, -0.0010737777f, -0.044124424f, 0.008305907f, - 0.037034288f, 0.037558764f, 0.07044493f, 0.02371332f, 0.042554155f, -0.016748935f, -0.03282152f, 0.057627276f, - 0.098468795f, 0.0013111085f, -0.09694767f, 0.040279135f, -0.098205775f, 0.040443808f, 0.11919229f, -0.08456744f, - -0.01728569f, 0.11710292f, 0.05050887f, 0.119447425f, -0.058948025f, -0.014045924f, -0.08559723f, -0.06781402f, - 0.026872516f, 0.10124619f, 0.111734346f, -0.04656139f, 0.106011614f, -0.0891671f, -0.117075205f, 0.016492844f, - 0.11645143f, 0.09561485f, -0.091205105f, -0.026062101f, 0.11059967f, 0.06537457f, 0.0026543885f, -0.055801243f, - 0.07915078f, 0.10557233f, 0.08071566f, 0.052541316f, -0.05650419f, -0.12145753f, 0.11263573f, 0.029210433f, - 0.015763626f, 0.046862796f, -0.04714054f, -0.09059784f, 0.068236336f, -0.015073091f, -0.11961791f, -0.023493499f, - -0.018783271f, -0.09126243f, -0.09896237f, -0.028903782f, -0.10383962f, 0.06351283f, -0.12072772f, -0.056735456f, - -0.090958446f, -0.044440717f, -0.124009505f, -0.035018772f, -0.08290787f, 0.0768452f, -0.10442828f, 0.11727749f, - 0.11758995f, 0.03290361f, -0.0113247335f, -0.07405861f, -0.055556238f, -0.08457345f, 0.018916026f, 0.11854942f, - -0.04181321f, -0.051882207f, 0.027751818f, -0.11699322f, -0.042488053f, -0.08696966f, -0.08996944f, -0.037741214f, - 0.097063705f, 0.053180724f, 0.03476517f, 0.104185596f, 0.072988436f, -0.0014739782f, 0.030967787f, -0.017249301f, - 0.06111832f, 0.02802904f, 0.049923286f, -0.11694123f, -0.016943783f, 0.066462934f, 0.04678969f, 0.031156898f, - -0.050833255f, 0.08095451f, -0.026759312f, -0.06783678f, -0.08926612f, 0.0010999292f, -0.098703265f, 0.07819982f, - 0.016622037f, -0.026472524f, 0.10805431f, -0.0021841824f, 0.014784232f, 0.081945494f, 0.02112551f, 0.0006199628f, - 0.1143356f, -0.09599832f, 0.061794326f, 0.031698108f, -0.019378498f, 0.040865794f, 0.01023905f, -0.07774389f, - -0.08447838f, -0.06274469f, 0.11284082f, 0.09761292f, -0.013365716f, 0.0630935f, 0.07569803f, 0.10532519f}; + // Do not test fp32 + data.fp32_output_data = {}; - output = { - -0.41288602f, 0.34693867f, 0.17056748f, -0.3000056f, 0.0037139729f, 0.6446975f, 0.35701394f, 0.4783501f, - 0.060810767f, -0.17548372f, 0.5347075f, -0.24958763f, 0.37899846f, -0.0033716336f, -0.14532009f, -0.3094958f, - 0.22858009f, -0.27370766f, 0.2448737f, -0.117854f, 0.4475677f, -0.15341815f, 0.20634943f, -0.2152504f, - -0.20829634f, -0.31435978f, -0.04319033f, -0.11306764f, -0.08076568f, -0.65668076f, -0.02969347f, -0.14298177f, - -0.41666374f, 0.22916545f, -0.043889944f, 0.44246197f, -0.25989074f, 0.0654705f, 0.20024723f, 0.116754055f, - -0.26155314f, -0.47822088f, 0.4269185f, 0.19983053f, 0.78657573f, 0.29853833f, -0.22293046f, 0.5119251f, - 0.25182527f, 0.18829623f, -0.22877915f, 0.018463401f, 0.046938226f, -0.24568044f, -0.067069344f, 0.16568068f, - 0.43599105f, -0.49316847f, 0.41968888f, 0.24670804f, 0.24518725f, 0.40178925f, 0.2817499f, 0.38869864f, - -0.37167335f, 0.37696028f, 0.2491411f, -0.4069539f, -0.025512135f, 0.697503f, 0.2736748f, 0.5130744f, - 0.08440733f, -0.08830104f, 0.4914955f, -0.26050097f, 0.35520625f, 0.03804043f, -0.10277921f, -0.32093158f, - 0.30793336f, -0.19618958f, 0.30210054f, -0.08955928f, 0.4240442f, -0.118735656f, 0.15663856f, -0.21542141f, - -0.1299509f, -0.34627512f, -0.0056000445f, -0.16983509f, -0.061221946f, -0.6379185f, 0.019689217f, -0.10790968f, - -0.44443697f, 0.25593972f, -0.019389862f, 0.46486115f, -0.22341447f, 0.0059498344f, 0.162151f, 0.017600633f, - -0.22027948f, -0.50053084f, 0.4946542f, 0.19559412f, 0.7739278f, 0.27242374f, -0.22544684f, 0.5744761f, - 0.29612914f, 0.16445178f, -0.28533965f, -0.019356813f, 0.048583828f, -0.18184364f, -0.028799001f, 0.15345171f, - 0.44764367f, -0.5045303f, 0.48955107f, 0.23092999f, 0.18916695f, 0.44125485f, 0.2561466f, 0.3750417f, - -0.4177165f, 0.4242855f, 0.23527762f, -0.43983376f, -0.015554033f, 0.7411243f, 0.29571885f, 0.49034935f, - 0.09105395f, -0.19059415f, 0.45305496f, -0.25565678f, 0.3147282f, 0.072712675f, -0.15744011f, -0.2522229f, - 0.28598517f, -0.115885735f, 0.18716305f, -0.076459914f, 0.42896318f, 0.00024261838f, 0.24630134f, -0.29495132f, - -0.1497713f, -0.3328632f, -0.020976782f, -0.18259642f, 0.052318588f, -0.6616767f, -0.03201641f, -0.077634454f, - -0.46381223f, 0.35139352f, -0.10998587f, 0.37857378f, -0.29113406f, 0.02714412f, 0.118249506f, 0.0014535487f, - -0.22025385f, -0.5309402f, 0.5069752f, 0.27742988f, 0.85060954f, 0.24166244f, -0.30255532f, 0.58699757f, - 0.37641618f, 0.2186183f, -0.37271595f, 0.087486595f, 0.08526345f, -0.22383334f, -0.06866325f, 0.19303375f, - 0.42361736f, -0.4988973f, 0.53478855f, 0.27574676f, 0.19689696f, 0.5228985f, 0.2286603f, 0.41254547f, - -0.38715667f, 0.4025734f, 0.24896201f, -0.40581006f, -0.007268807f, 0.69798714f, 0.3008909f, 0.5033461f, - 0.040404595f, -0.15796751f, 0.39680687f, -0.24920885f, 0.28985906f, 0.11799197f, -0.16544515f, -0.30313727f, - 0.30446523f, -0.13475142f, 0.22777845f, -0.03863262f, 0.39835036f, -0.05059766f, 0.18062752f, -0.23713541f, - -0.1575769f, -0.31721163f, -0.02570787f, -0.17792636f, -0.0038699396f, -0.63370764f, -0.011535684f, -0.07881303f, - -0.47101083f, 0.24331519f, -0.059330232f, 0.4296828f, -0.2792168f, 0.011085652f, 0.06865603f, 0.024540272f, - -0.1942445f, -0.5154834f, 0.5137167f, 0.30345967f, 0.7880432f, 0.22699502f, -0.23210928f, 0.5624612f, - 0.3241039f, 0.2758873f, -0.35064527f, 0.08398114f, 0.080884576f, -0.21506889f, -0.0025116205f, 0.116575986f, - 0.43586755f, -0.5633712f, 0.46149772f, 0.21475634f, 0.21229926f, 0.42853355f, 0.25883353f, 0.39509213f}; + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias.fp16_output_data", data.fp16_output_data); } void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias(PackedAttentionTestData& data) { @@ -6428,96 +552,20 @@ void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias(PackedAttention data.skip_kernel_types = { AttentionKernelType::AttentionKernel_TrtFusedCrossAttention}; - { - data.query_data = { - -1.83615911f, 0.08698978f, 0.05601556f, -1.14510250f, -2.30377889f, -0.39893439f, 0.73342341f, -0.09851928f, - -0.45148617f, -0.16055907f, -1.48271382f, -0.07961921f, -0.65701288f, -0.25778309f, -0.72851723f, 0.86755788f, - - -0.69794613f, 1.27221310f, 0.01081287f, 0.61428916f, -0.00753688f, 0.33604777f, -0.65822184f, -0.83206612f, - 0.14741525f, 1.17016482f, -0.68234873f, -1.34005868f, -0.22676668f, -0.29179415f, -0.15037467f, 0.15722550f, - -0.20033565f, -1.51847255f, 0.95205748f, 0.54009491f, 1.19315910f, 0.81655478f, 0.87503016f, 0.09732430f, - -0.53218621f, -0.11167067f, 0.67364228f, -0.59705222f, -0.24946509f, 0.20462716f, -0.56092483f, -0.65660709f}; - } - { - data.key_data = { - 0.86949563f, -0.10868365f, -0.37917313f, -1.23103046f, 0.25640076f, -1.50652349f, 0.71594471f, 0.49057019f, - -1.41292810f, -0.19686662f, 1.25451696f, -1.59823179f, -1.16262913f, 0.84965342f, 0.61178929f, -1.26162946f, - - 0.56394553f, -0.14227687f, 1.25733399f, -0.11350060f, 0.02068172f, -0.21710102f, 1.00936651f, 0.04366954f, - 0.72092402f, -1.80008531f, 1.11335325f, -0.58614230f, 0.15335107f, -0.43153843f, -0.81098813f, 1.15529966f, - 0.47295785f, 0.65468878f, -1.44158995f, -0.05122741f, -0.34755200f, 0.66963655f, 0.72664660f, 1.59155345f, - -1.13806772f, 0.70947856f, -0.65793264f, -0.50718778f, -1.20698619f, 0.32613355f, 0.61786091f, -0.34040576f}; - } - - { - data.value_data = { - -1.19203627f, 0.38844836f, 0.68121153f, 0.21624038f, -1.77549291f, 0.18574584f, 0.90408206f, -0.22868094f, - -0.95558548f, 1.38712502f, 0.81038797f, 0.14359820f, 0.15352470f, 0.00469783f, 0.03943123f, 0.53865469f, - - -1.60517013f, -0.88120216f, 1.91317511f, -0.54577649f, 0.62921578f, 0.57512373f, -0.31156173f, 0.57847321f, - 0.04376111f, -0.09540533f, -0.38106504f, 1.00102639f, -0.56325150f, 0.90788037f, -0.33356044f, 0.74308902f, - -0.15860432f, -0.24945745f, 0.67483073f, 0.18782829f, -0.56960964f, 1.16764832f, -0.72244978f, 0.55027384f, - -0.37327161f, 1.19222152f, -0.23447749f, 0.06147140f, 0.32951999f, 1.06427121f, 2.26385999f, 0.23828916f}; - } - - { - data.bias_data = {}; - } - - { - data.qkv_data = { - -1.83615911f, 0.08698978f, 0.05601556f, -1.14510250f, -2.30377889f, -0.39893439f, 0.73342341f, -0.09851928f, - 0.86949563f, -0.10868365f, -0.37917313f, -1.23103046f, 0.25640076f, -1.50652349f, 0.71594471f, 0.49057019f, - -1.19203627f, 0.38844836f, 0.68121153f, 0.21624038f, -1.77549291f, 0.18574584f, 0.90408206f, -0.22868094f, - - -0.45148617f, -0.16055907f, -1.48271382f, -0.07961921f, -0.65701288f, -0.25778309f, -0.72851723f, 0.86755788f, - -1.41292810f, -0.19686662f, 1.25451696f, -1.59823179f, -1.16262913f, 0.84965342f, 0.61178929f, -1.26162946f, - -0.95558548f, 1.38712502f, 0.81038797f, 0.14359820f, 0.15352470f, 0.00469783f, 0.03943123f, 0.53865469f, - - -0.69794613f, 1.27221310f, 0.01081287f, 0.61428916f, -0.00753688f, 0.33604777f, -0.65822184f, -0.83206612f, - 0.56394553f, -0.14227687f, 1.25733399f, -0.11350060f, 0.02068172f, -0.21710102f, 1.00936651f, 0.04366954f, - -1.60517013f, -0.88120216f, 1.91317511f, -0.54577649f, 0.62921578f, 0.57512373f, -0.31156173f, 0.57847321f, - - 0.14741525f, 1.17016482f, -0.68234873f, -1.34005868f, -0.22676668f, -0.29179415f, -0.15037467f, 0.15722550f, - 0.72092402f, -1.80008531f, 1.11335325f, -0.58614230f, 0.15335107f, -0.43153843f, -0.81098813f, 1.15529966f, - 0.04376111f, -0.09540533f, -0.38106504f, 1.00102639f, -0.56325150f, 0.90788037f, -0.33356044f, 0.74308902f, - - -0.20033565f, -1.51847255f, 0.95205748f, 0.54009491f, 1.19315910f, 0.81655478f, 0.87503016f, 0.09732430f, - 0.47295785f, 0.65468878f, -1.44158995f, -0.05122741f, -0.34755200f, 0.66963655f, 0.72664660f, 1.59155345f, - -0.15860432f, -0.24945745f, 0.67483073f, 0.18782829f, -0.56960964f, 1.16764832f, -0.72244978f, 0.55027384f, - - -0.53218621f, -0.11167067f, 0.67364228f, -0.59705222f, -0.24946509f, 0.20462716f, -0.56092483f, -0.65660709f, - -1.13806772f, 0.70947856f, -0.65793264f, -0.50718778f, -1.20698619f, 0.32613355f, 0.61786091f, -0.34040576f, - -0.37327161f, 1.19222152f, -0.23447749f, 0.06147140f, 0.32951999f, 1.06427121f, 2.26385999f, 0.23828916f}; - } + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.query_data", data.query_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.key_data", data.key_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.value_data", data.value_data); + data.bias_data = {}; + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.qkv_data", data.qkv_data); // shape: batch_size, num_heads, sequence_length, sequence_length - { - data.rel_pos_bias_data = { - 0.4781123f, 0.82420444f, 0.654424f, 0.3995186f, - 0.5482078f, 0.55570245f, 0.4216576f, 0.46001542f, - 0.4781123f, 0.82420444f, 0.654424f, 0.3995186f, - 0.5482078f, 0.55570245f, 0.4216576f, 0.46001542f}; - - data.broadcast_rel_pos_bias = false; - } - - { - // Do not test fp32 - data.fp32_output_data = {}; - } + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.rel_pos_bias_data", data.rel_pos_bias_data); + data.broadcast_rel_pos_bias = false; - { - data.fp16_output_data = { - -1.1923828f, 0.38842773f, 0.68115234f, 0.21618652f, -1.7753906f, 0.18579102f, 0.90429688f, -0.2286377f, - -0.95556641f, 1.3867188f, 0.81054688f, 0.14355469f, 0.15356445f, 0.004699707f, 0.039428711f, 0.53857422f, + // Do not test fp32 + data.fp32_output_data = {}; - -0.72265625f, -0.49584961f, 1.1572266f, -0.098266602f, -0.10211182f, 0.93652344f, -0.56201172f, 0.56103516f, - -0.27758789f, 0.89697266f, -0.26831055f, 0.27734375f, 0.12451172f, 1.0283203f, 1.6679688f, 0.35424805f, - - -1.3427734f, -0.76660156f, 1.6884766f, -0.41259766f, 0.41162109f, 0.68261719f, -0.38598633f, 0.57324219f, - -0.17407227f, 0.57763672f, -0.3046875f, 0.51025391f, -0.097045898f, 0.98974609f, 1.0234375f, 0.47949219f}; - } + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias.fp16_output_data", data.fp16_output_data); } void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias(PackedAttentionTestData& data) { @@ -6534,214 +582,28 @@ void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias(Packed data.skip_kernel_types = { AttentionKernelType::AttentionKernel_TrtFusedCrossAttention}; - { - data.query_data = { - -1.83615911f, 0.08698978f, 0.05601556f, -1.14510250f, -2.30377889f, -0.39893439f, 0.73342341f, -0.09851928f, - -0.45148617f, -0.16055907f, -1.48271382f, -0.07961921f, -0.65701288f, -0.25778309f, -0.72851723f, 0.86755788f, - - -1.61145306f, 1.15819526f, 0.92267495f, 0.05697182f, -1.15679109f, 0.30815905f, -0.16966841f, 1.59468949f, - 1.06674862f, -0.94525659f, -1.26431036f, 0.54500824f, 2.33555818f, -1.55515289f, -1.15762365f, 0.94301772f, - -0.11946517f, -0.52010381f, 1.17592037f, 1.18040121f, 1.71579909f, 0.74054289f, -0.28932455f, 0.43039253f, - -0.59887785f, -1.49919224f, 1.02610373f, 0.28144905f, 0.54606986f, 0.89283150f, -1.55426455f, 0.81868863f, - 0.52380687f, -0.98392582f, -1.63426089f, -0.48980984f, 0.39993629f, -0.29305443f, 0.89878768f, -0.56480503f, - 0.36021376f, 0.23860840f, -0.31765643f, -0.26952648f, -1.24825561f, 1.21374047f, 0.23826340f, 0.63743669f, - -0.24714193f, 1.01905107f, -0.93621284f, -0.84905517f, -1.20235336f, -2.04996300f, -0.01251672f, -1.23131406f, - 0.75130051f, 1.48657084f, -0.17923722f, -0.58394587f, 0.90255487f, -0.60496974f, -0.31978402f, 0.04127264f, - -0.74666536f, 1.14945197f, 0.85595274f, 0.87929201f, 0.52238762f, -0.38138887f, -0.09198012f, 0.10379392f, - 0.03910975f, 0.37068886f, 0.38653150f, -0.84676158f, 0.88043237f, -0.70293593f, -1.86805880f, 0.50196815f, - 1.79820418f, 0.49160564f, -1.04994130f, -0.65047348f, 0.03673789f, -1.43390560f, 0.33562672f, 0.16967399f, - -0.71324098f, -0.24858820f, -0.42040613f, -0.47096899f, -2.18410730f, 1.29030848f, 0.95546865f, -0.01637810f, - 2.10404348f, -0.25014257f, 2.06826448f, 0.68731880f, -0.72305721f, -3.06288505f, 1.35467649f, -2.27782655f, - -2.04115343f, 0.01709199f, 1.14326739f, -2.85616302f, -1.63115931f, 1.21209049f, -2.88173485f, 0.29401016f, - 0.96896434f, 1.49846828f, -1.48152626f, -0.40123838f, 0.66036439f, -2.08949637f, 0.93013203f, 1.78407586f, - -0.16418101f, 0.30182290f, 0.76461935f, 0.89762378f, -0.70261180f, 1.31333566f, 0.86440170f, -0.55341989f}; - } - { - data.key_data = { - 0.86949563f, -0.10868365f, -0.37917313f, -1.23103046f, 0.25640076f, -1.50652349f, 0.71594471f, 0.49057019f, - -1.41292810f, -0.19686662f, 1.25451696f, -1.59823179f, -1.16262913f, 0.84965342f, 0.61178929f, -1.26162946f, - - -0.39776036f, -0.32152289f, 0.83949518f, -0.68910766f, 2.10605407f, -1.13187802f, -0.02778089f, -0.46233135f, - -2.59193254f, -0.02682346f, 0.07309747f, -1.76444602f, -1.02990091f, -0.92442840f, 0.80414194f, -1.34978604f, - 0.18744308f, 0.95530021f, 1.00306034f, -0.06650767f, 0.14434582f, -0.07039906f, -0.42095628f, 1.47149456f, - -0.32872301f, 0.28885615f, -0.12510297f, -0.35719556f, 0.36152089f, -0.06192274f, -0.28507957f, 0.75713438f, - -0.59390724f, -0.20499256f, 0.45794842f, 0.49178654f, -0.25790799f, -0.32643789f, 0.38682714f, -0.26962680f, - 0.32060453f, 0.06873609f, 1.35627246f, -0.55090475f, 0.75872916f, -0.72157520f, -0.75826746f, -0.43329650f, - -1.35081804f, -0.40014201f, 0.26041570f, 0.23221464f, 0.90103126f, -0.98436964f, 0.78283572f, -1.78756905f, - 0.56045622f, 0.52480292f, -0.67152452f, -1.51145959f, 0.35886180f, -0.41121563f, 0.61315238f, -1.03636253f, - 0.32577509f, -0.24800496f, 0.61258811f, -0.14612751f, 0.82892537f, -0.14666887f, 0.26352236f, 0.27397016f, - -0.54198223f, -0.38484800f, -0.05891366f, -0.79304564f, -0.58239877f, 0.26545495f, -0.38297540f, 0.79097033f, - 1.70193112f, -0.31023103f, -0.33280775f, 0.70939517f, -1.27211368f, -0.58704966f, -1.81665146f, 0.03955793f, - -0.40429014f, 0.48408982f, 1.63168097f, 0.71464306f, 0.93015838f, -0.16759235f, -2.20110703f, 0.78718776f, - 1.27983427f, 1.74217772f, -1.50595713f, 1.52578330f, 0.56935966f, -0.94778556f, -1.28090227f, -0.02918145f, - 0.99273205f, 2.60591888f, 1.39687920f, -0.34032899f, 0.35641205f, 0.91440523f, -0.69939649f, 2.64614010f, - 0.65847164f, -1.24047744f, -0.11745319f, 0.80385536f, -0.55450106f, -0.64750642f, -0.84041762f, 0.10586573f, - -1.74471772f, 0.38858974f, 0.77225429f, -0.47355813f, 0.59074765f, -0.50501788f, -1.72981727f, -1.25862873f}; - } - - { - data.value_data = { - -1.19203627f, 0.38844836f, 0.68121153f, 0.21624038f, -1.77549291f, 0.18574584f, 0.90408206f, -0.22868094f, - -0.95558548f, 1.38712502f, 0.81038797f, 0.14359820f, 0.15352470f, 0.00469783f, 0.03943123f, 0.53865469f, - - 0.50737989f, 1.88879848f, -0.66337180f, -1.29574990f, -1.86634719f, -1.01549423f, -0.28819263f, -0.00019580f, - -2.00984406f, -0.95374167f, 0.84587288f, -1.78314638f, -0.26245379f, -1.30501473f, -1.76663613f, 0.81748939f, - 0.80457681f, -0.33367968f, -0.10504961f, 0.27371234f, -0.07084391f, -0.40500754f, -0.04883647f, -0.94577336f, - 1.02707481f, -0.13490768f, -0.18182218f, -0.93900180f, 1.18116772f, 1.98105478f, -0.36385471f, 1.03757906f, - 0.14796616f, -0.83527970f, 0.16718683f, 1.49241018f, 0.43081248f, -1.43449056f, 0.39671475f, -0.70072436f, - 0.17739578f, 0.32338822f, -0.67136252f, 0.01797877f, -0.59793222f, 0.78523242f, 0.25322497f, 1.50049233f, - -0.67545807f, 0.50556731f, 0.18512395f, -1.26351786f, -1.42564654f, -1.06456351f, -1.15261269f, -0.49967349f, - -1.68690670f, -1.10258508f, 0.07205302f, 1.72984779f, -0.86800003f, -0.91829145f, -0.97764057f, -0.55795985f, - -0.85447711f, 0.16153991f, 1.38688803f, -1.06463683f, -1.42907071f, 0.43985835f, -0.49964419f, 0.67612225f, - -0.17095472f, -0.31460449f, 0.78414583f, 0.25754923f, 0.49601099f, 1.01128983f, -0.85820115f, 1.31935477f, - 1.41204929f, -1.20291567f, 0.22243243f, 2.67244053f, 0.75709999f, -0.44346970f, 0.94684786f, -0.61597395f, - -0.37711632f, -0.30456182f, -0.73898333f, 0.39148647f, -0.04324996f, -1.18526721f, -1.38802266f, 0.82284755f, - 0.33568430f, -3.36413050f, 1.40020049f, 1.05561769f, -1.90628219f, 1.38226020f, 0.99804544f, 1.02540088f, - -1.05158651f, -3.61572313f, -2.07312417f, 0.55376863f, -0.07229304f, 0.02950740f, -1.17457461f, 0.59849799f, - 0.56384206f, 0.21395147f, 1.26861954f, 2.02004290f, -0.83739442f, -0.11827546f, -0.42885846f, -1.55389440f, - -1.04708695f, 1.04990900f, 0.61408597f, 0.48327276f, 0.61544299f, -0.57864964f, -0.80768973f, 0.39645281f}; - } - - { - data.bias_data = {}; - } - - { - data.qkv_data = { - -1.83615911f, 0.08698978f, 0.05601556f, -1.14510250f, -2.30377889f, -0.39893439f, 0.73342341f, -0.09851928f, - 0.86949563f, -0.10868365f, -0.37917313f, -1.23103046f, 0.25640076f, -1.50652349f, 0.71594471f, 0.49057019f, - -1.19203627f, 0.38844836f, 0.68121153f, 0.21624038f, -1.77549291f, 0.18574584f, 0.90408206f, -0.22868094f, - - -0.45148617f, -0.16055907f, -1.48271382f, -0.07961921f, -0.65701288f, -0.25778309f, -0.72851723f, 0.86755788f, - -1.41292810f, -0.19686662f, 1.25451696f, -1.59823179f, -1.16262913f, 0.84965342f, 0.61178929f, -1.26162946f, - -0.95558548f, 1.38712502f, 0.81038797f, 0.14359820f, 0.15352470f, 0.00469783f, 0.03943123f, 0.53865469f, - - -1.61145306f, 1.15819526f, 0.92267495f, 0.05697182f, -1.15679109f, 0.30815905f, -0.16966841f, 1.59468949f, - -0.39776036f, -0.32152289f, 0.83949518f, -0.68910766f, 2.10605407f, -1.13187802f, -0.02778089f, -0.46233135f, - 0.50737989f, 1.88879848f, -0.66337180f, -1.29574990f, -1.86634719f, -1.01549423f, -0.28819263f, -0.00019580f, - - 1.06674862f, -0.94525659f, -1.26431036f, 0.54500824f, 2.33555818f, -1.55515289f, -1.15762365f, 0.94301772f, - -2.59193254f, -0.02682346f, 0.07309747f, -1.76444602f, -1.02990091f, -0.92442840f, 0.80414194f, -1.34978604f, - -2.00984406f, -0.95374167f, 0.84587288f, -1.78314638f, -0.26245379f, -1.30501473f, -1.76663613f, 0.81748939f, - - -0.11946517f, -0.52010381f, 1.17592037f, 1.18040121f, 1.71579909f, 0.74054289f, -0.28932455f, 0.43039253f, - 0.18744308f, 0.95530021f, 1.00306034f, -0.06650767f, 0.14434582f, -0.07039906f, -0.42095628f, 1.47149456f, - 0.80457681f, -0.33367968f, -0.10504961f, 0.27371234f, -0.07084391f, -0.40500754f, -0.04883647f, -0.94577336f, - - -0.59887785f, -1.49919224f, 1.02610373f, 0.28144905f, 0.54606986f, 0.89283150f, -1.55426455f, 0.81868863f, - -0.32872301f, 0.28885615f, -0.12510297f, -0.35719556f, 0.36152089f, -0.06192274f, -0.28507957f, 0.75713438f, - 1.02707481f, -0.13490768f, -0.18182218f, -0.93900180f, 1.18116772f, 1.98105478f, -0.36385471f, 1.03757906f, - - 0.52380687f, -0.98392582f, -1.63426089f, -0.48980984f, 0.39993629f, -0.29305443f, 0.89878768f, -0.56480503f, - -0.59390724f, -0.20499256f, 0.45794842f, 0.49178654f, -0.25790799f, -0.32643789f, 0.38682714f, -0.26962680f, - 0.14796616f, -0.83527970f, 0.16718683f, 1.49241018f, 0.43081248f, -1.43449056f, 0.39671475f, -0.70072436f, - - 0.36021376f, 0.23860840f, -0.31765643f, -0.26952648f, -1.24825561f, 1.21374047f, 0.23826340f, 0.63743669f, - 0.32060453f, 0.06873609f, 1.35627246f, -0.55090475f, 0.75872916f, -0.72157520f, -0.75826746f, -0.43329650f, - 0.17739578f, 0.32338822f, -0.67136252f, 0.01797877f, -0.59793222f, 0.78523242f, 0.25322497f, 1.50049233f, - - -0.24714193f, 1.01905107f, -0.93621284f, -0.84905517f, -1.20235336f, -2.04996300f, -0.01251672f, -1.23131406f, - -1.35081804f, -0.40014201f, 0.26041570f, 0.23221464f, 0.90103126f, -0.98436964f, 0.78283572f, -1.78756905f, - -0.67545807f, 0.50556731f, 0.18512395f, -1.26351786f, -1.42564654f, -1.06456351f, -1.15261269f, -0.49967349f, - - 0.75130051f, 1.48657084f, -0.17923722f, -0.58394587f, 0.90255487f, -0.60496974f, -0.31978402f, 0.04127264f, - 0.56045622f, 0.52480292f, -0.67152452f, -1.51145959f, 0.35886180f, -0.41121563f, 0.61315238f, -1.03636253f, - -1.68690670f, -1.10258508f, 0.07205302f, 1.72984779f, -0.86800003f, -0.91829145f, -0.97764057f, -0.55795985f, - - -0.74666536f, 1.14945197f, 0.85595274f, 0.87929201f, 0.52238762f, -0.38138887f, -0.09198012f, 0.10379392f, - 0.32577509f, -0.24800496f, 0.61258811f, -0.14612751f, 0.82892537f, -0.14666887f, 0.26352236f, 0.27397016f, - -0.85447711f, 0.16153991f, 1.38688803f, -1.06463683f, -1.42907071f, 0.43985835f, -0.49964419f, 0.67612225f, - - 0.03910975f, 0.37068886f, 0.38653150f, -0.84676158f, 0.88043237f, -0.70293593f, -1.86805880f, 0.50196815f, - -0.54198223f, -0.38484800f, -0.05891366f, -0.79304564f, -0.58239877f, 0.26545495f, -0.38297540f, 0.79097033f, - -0.17095472f, -0.31460449f, 0.78414583f, 0.25754923f, 0.49601099f, 1.01128983f, -0.85820115f, 1.31935477f, - - 1.79820418f, 0.49160564f, -1.04994130f, -0.65047348f, 0.03673789f, -1.43390560f, 0.33562672f, 0.16967399f, - 1.70193112f, -0.31023103f, -0.33280775f, 0.70939517f, -1.27211368f, -0.58704966f, -1.81665146f, 0.03955793f, - 1.41204929f, -1.20291567f, 0.22243243f, 2.67244053f, 0.75709999f, -0.44346970f, 0.94684786f, -0.61597395f, - - -0.71324098f, -0.24858820f, -0.42040613f, -0.47096899f, -2.18410730f, 1.29030848f, 0.95546865f, -0.01637810f, - -0.40429014f, 0.48408982f, 1.63168097f, 0.71464306f, 0.93015838f, -0.16759235f, -2.20110703f, 0.78718776f, - -0.37711632f, -0.30456182f, -0.73898333f, 0.39148647f, -0.04324996f, -1.18526721f, -1.38802266f, 0.82284755f, - - 2.10404348f, -0.25014257f, 2.06826448f, 0.68731880f, -0.72305721f, -3.06288505f, 1.35467649f, -2.27782655f, - 1.27983427f, 1.74217772f, -1.50595713f, 1.52578330f, 0.56935966f, -0.94778556f, -1.28090227f, -0.02918145f, - 0.33568430f, -3.36413050f, 1.40020049f, 1.05561769f, -1.90628219f, 1.38226020f, 0.99804544f, 1.02540088f, - - -2.04115343f, 0.01709199f, 1.14326739f, -2.85616302f, -1.63115931f, 1.21209049f, -2.88173485f, 0.29401016f, - 0.99273205f, 2.60591888f, 1.39687920f, -0.34032899f, 0.35641205f, 0.91440523f, -0.69939649f, 2.64614010f, - -1.05158651f, -3.61572313f, -2.07312417f, 0.55376863f, -0.07229304f, 0.02950740f, -1.17457461f, 0.59849799f, - - 0.96896434f, 1.49846828f, -1.48152626f, -0.40123838f, 0.66036439f, -2.08949637f, 0.93013203f, 1.78407586f, - 0.65847164f, -1.24047744f, -0.11745319f, 0.80385536f, -0.55450106f, -0.64750642f, -0.84041762f, 0.10586573f, - 0.56384206f, 0.21395147f, 1.26861954f, 2.02004290f, -0.83739442f, -0.11827546f, -0.42885846f, -1.55389440f, - - -0.16418101f, 0.30182290f, 0.76461935f, 0.89762378f, -0.70261180f, 1.31333566f, 0.86440170f, -0.55341989f, - -1.74471772f, 0.38858974f, 0.77225429f, -0.47355813f, 0.59074765f, -0.50501788f, -1.72981727f, -1.25862873f, - -1.04708695f, 1.04990900f, 0.61408597f, 0.48327276f, 0.61544299f, -0.57864964f, -0.80768973f, 0.39645281f}; - } + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.query_data", data.query_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.key_data", data.key_data); + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.value_data", data.value_data); + data.bias_data = {}; + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.qkv_data", data.qkv_data); // shape: 1, num_heads, sequence_length, sequence_length - { - data.rel_pos_bias_data = { - 0.09734076f, -0.01747033f, 0.008497253f, -0.03361112f, -0.028750911f, -0.017142132f, -0.11563814f, 0.10432467f, - 0.057628587f, 0.030893803f, -0.096876964f, 0.11924802f, -0.009177148f, 0.05799888f, -0.030559167f, 0.034150958f, - 0.07427484f, 0.028848544f, -0.031371966f, 0.07186346f, -0.093020484f, -0.066411436f, 0.06858949f, 0.07350862f, - 0.008785307f, -0.07727124f, 0.09184219f, 0.081774f, 0.008513406f, -0.04256621f, -0.078802094f, -0.09632437f, - -0.0073524266f, 0.035430342f, -0.01940021f, 0.05564849f, -0.03556633f, -0.11830491f, -0.05839123f, -0.05537042f, - 0.06146671f, 0.0026960075f, -0.07718696f, -0.06268193f, 0.039188996f, 0.07048777f, -0.0009800941f, -0.04509197f, - 0.04516627f, -0.09005861f, 0.06470743f, 0.12054373f, 0.03366275f, 0.009849519f, 0.015899211f, 0.11534238f, - -0.002090156f, -0.0851126f, -0.05993013f, 0.030745044f, -0.02415888f, 0.06568785f, -0.012787953f, 0.021764219f, - - -0.07153495f, 0.072637364f, 0.09073421f, 0.041491434f, -0.11252555f, -0.059031114f, 0.11179088f, 0.0655573f, - -0.11293891f, 0.05239816f, -0.110543296f, -0.017368436f, -0.050893307f, 0.04980643f, -0.12137364f, -0.08896659f, - 0.04159136f, -0.021769747f, 0.018932432f, 0.087893024f, -0.014453113f, 0.012075469f, 0.0026388168f, -0.07094294f, - 0.035509557f, 0.065090835f, 0.115079954f, -0.11314371f, 0.121840075f, 0.030929685f, -0.051646978f, -0.10540052f, - -0.08004643f, -0.089356855f, -0.112021506f, 0.07381505f, -0.06653316f, -0.11657183f, 0.08264731f, 0.10898076f, - -0.006200552f, -0.0960899f, -0.015346348f, -0.047637567f, 0.051793993f, -0.09059112f, -0.034093216f, 0.108242184f, - -0.049242377f, -0.12165685f, -0.09124553f, 0.05479528f, -0.048966378f, -0.027208641f, 0.10195236f, 0.047513425f, - 0.013226762f, -0.07403794f, 0.06855075f, -0.06551643f, -0.084110215f, 0.11237715f, 0.07026932f, -0.014076158f}; - - data.broadcast_rel_pos_bias = true; - } - - { - data.fp32_output_data = {}; - } - - { - data.fp16_output_data = { - -1.1923828f, 0.38842773f, 0.68115234f, 0.21618652f, -1.7753906f, 0.18579102f, 0.90429688f, -0.2286377f, - -0.95556641f, 1.3867188f, 0.81054688f, 0.14355469f, 0.15356445f, 0.004699707f, 0.039428711f, 0.53857422f, + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.rel_pos_bias_data", + data.rel_pos_bias_data); + data.broadcast_rel_pos_bias = true; - 0.46826172f, -0.38012695f, 0.23950195f, 0.50976562f, -0.35839844f, -0.4597168f, 0.0065727234f, -0.62060547f, - -0.28198242f, -0.4128418f, -0.44287109f, 0.22363281f, 0.062408447f, 0.058746338f, -0.75292969f, 0.82275391f, + // Do not test fp32 + data.fp32_output_data = {}; - 0.18103027f, 0.17089844f, 0.31738281f, -0.098022461f, -1.0439453f, -0.43823242f, -0.19689941f, -0.25537109f, - -0.38745117f, -0.32739258f, -0.40332031f, 0.23425293f, 0.13305664f, -0.3503418f, -1.0107422f, 0.859375f, - - 0.14135742f, -0.1895752f, 0.50634766f, 0.25634766f, -1.0400391f, -0.37524414f, -0.16821289f, -0.30371094f, - -0.68164062f, -1.4511719f, -0.52636719f, 0.19763184f, 0.082946777f, 0.1776123f, -0.97021484f, 0.73828125f, - - 0.23144531f, -0.75341797f, 0.52148438f, 0.52148438f, -0.92041016f, -0.27001953f, 0.054473877f, -0.19238281f, - -0.68212891f, -1.3339844f, -0.75f, 0.37451172f, -0.060058594f, 0.0034179688f, -0.8671875f, 0.65429688f, - - 0.20629883f, -0.37646484f, 0.37646484f, 0.13183594f, -0.94873047f, -0.34375f, -0.059875488f, -0.22937012f, - -0.58105469f, -0.63671875f, -0.50732422f, 0.30419922f, 0.086791992f, -0.23132324f, -0.91210938f, 0.74902344f, - - 0.49804688f, -1.3681641f, 0.75146484f, 1.0007825f, -0.93847656f, 0.23278809f, 0.44604492f, 0.047668457f, - -1.1943359f, -0.75732422f, 0.48681641f, -0.67480469f, -0.0028400421f, -0.37817383f, -1.2705078f, 0.81201172f, - - 0.13586426f, 0.0039863586f, 0.36181641f, 0.22192383f, -0.89648438f, -0.609375f, -0.26049805f, -0.43920898f, - -1.046875f, -0.19360352f, 0.30297852f, -0.20007324f, 0.20483398f, -0.50097656f, -1.1142578f, 0.71923828f, - - 0.37207031f, -1.8447266f, 0.88818359f, 0.71191406f, -1.3359375f, 0.56396484f, 0.52001953f, 0.36254883f, - -0.73681641f, -0.90722656f, -0.29516602f, 0.021835327f, 0.030609131f, -0.098083496f, -0.96777344f, 0.75927734f}; - } + LoadTensor("PackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias.fp16_output_data", + data.fp16_output_data); } bool SkipAttentionKernel(AttentionTestData& data, AttentionKernelType kernel_type) { - return std::find(data.skip_kernel_types.begin(), data.skip_kernel_types.end(), kernel_type) != data.skip_kernel_types.end(); + return data.skip_kernel_types.end() != std::find(data.skip_kernel_types.begin(), + data.skip_kernel_types.end(), + kernel_type); } } // namespace test diff --git a/onnxruntime/test/contrib_ops/attention_op_test_helper.h b/onnxruntime/test/contrib_ops/attention_op_test_helper.h index d12a761c8142e..0ed30596ac136 100644 --- a/onnxruntime/test/contrib_ops/attention_op_test_helper.h +++ b/onnxruntime/test/contrib_ops/attention_op_test_helper.h @@ -53,8 +53,6 @@ struct PackedAttentionTestData : public BaseAttentionTestData { std::vector cumulative_sequence_length; }; -// Disable some tests in Windows since prefast build might crash with large test data. -#if !defined(_MSC_VER) // Return packed weights and bias for input projection. void GetAttentionWeight(std::vector& weight_data, int elements = 64 * 3 * 64, int offset = 0, int step = 1); void GetAttentionBias(std::vector& bias_data, int elements = 3 * 64, int offset = 0, int step = 1); @@ -68,8 +66,6 @@ void GetCrossAttentionData_Batch1_HeadSize32_LeftSidePadding_NoBias(AttentionTes void GetCrossAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedKV(AttentionTestData& data); void GetSelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV(AttentionTestData& data); -void GetPackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias(PackedAttentionTestData& data); -#endif void GetCrossAttentionData_HeadSize16_8(AttentionTestData& data); void GetCrossAttentionData_HeadSize16_8_NoBias(AttentionTestData& data); @@ -87,10 +83,16 @@ void GetSelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias(Atten void GetSelfAttentionData_WithPastAndPresent_HeadSize8_NoMask_NoRelPosBias_NoBias(AttentionTestData& data); void GetCrossAttentionData_WithPastPassedInDirectly_NoMask(AttentionTestData& data); +void GetCausal_EmptyPastState(std::vector& input, std::vector& output, std::vector& present); + void GetAttentionDataCutlassRelPosBias(AttentionTestData& data); -void GetAttentionDataWithNeoXRotaryEmbedding(std::vector& input, std::vector& weights, std::vector& bias, +void GetAttentionDataWithNeoXRotaryEmbedding(std::vector& input, + std::vector& weights, + std::vector& bias, std::vector& output); +void GetPackedMultiHeadAttentionData_Batch2_HeadSize32_NoRelPosBias(PackedAttentionTestData& data); + void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_RelPosBias(PackedAttentionTestData& data); void GetPackedMultiHeadAttentionData_Batch2_HeadSize8_BroadcastRelPosBias(PackedAttentionTestData& data); diff --git a/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc b/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc index f458031a35ef3..c2230501b081d 100644 --- a/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc +++ b/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc @@ -456,8 +456,6 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, bool disable_cpu } } -// Disable some tests in Windows since prefast build might crash with large test data. -#if !defined(_MSC_VER) // Test fused cross attention kernel // It requires head_size > 32 and head_size <= 64 for T4 GPU; hidden_size == v_hidden_size. TEST(MultiHeadAttentionTest, CrossAttention_Batch2_HeadSize40) { @@ -509,7 +507,6 @@ TEST(MultiHeadAttentionTest, SelfAttention_Batch2_HeadSize32_NoBias_NoMask_Packe GetSelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV(data); RunMultiHeadAttentionTests(data); } -#endif // This tests qk_head_size != v_head_size TEST(MultiHeadAttentionTest, CrossAttention_Batch2_HeadSize16_8) { @@ -577,7 +574,8 @@ TEST(MultiHeadAttentionTest, SelfAttention_WithPastAndPresent_NoMask_NoRelPosBia RunMultiHeadAttentionTests(data, /*disable_cpu=*/false, /*disable_cuda=*/true); } -TEST(MultiHeadAttentionTest, CrossAttention_WithPastPassedInDirectly_NoMask) { +// This test is disabled since it is not used in Whisper anymore, and it fails in ROCm. +TEST(MultiHeadAttentionTest, DISABLED_CrossAttention_WithPastPassedInDirectly_NoMask) { // Whisper decoder cross attention with past_kv in place of current KV and no present_kv AttentionTestData data; GetCrossAttentionData_WithPastPassedInDirectly_NoMask(data); diff --git a/onnxruntime/test/contrib_ops/packed_multihead_attention_op_test.cc b/onnxruntime/test/contrib_ops/packed_multihead_attention_op_test.cc index 919c082ec4bf3..fc2b58680c84f 100644 --- a/onnxruntime/test/contrib_ops/packed_multihead_attention_op_test.cc +++ b/onnxruntime/test/contrib_ops/packed_multihead_attention_op_test.cc @@ -199,7 +199,6 @@ static void RunPackedMultiHeadAttentionTest( } } -#if !defined(_MSC_VER) TEST(PackedMultiHeadAttentionTest, PackedQKV_NoPadding_NoBias_trt) { AttentionTestData data; GetSelfAttentionData_Batch2_HeadSize32_NoBias_NoMask_PackedQKV(data); @@ -411,7 +410,6 @@ TEST(PackedMultiHeadAttentionTest, PackedQKV_Padding_NoBias_unfused) { data.token_count, AttentionKernelType::AttentionKernel_Unfused); } -#endif TEST(PackedMultiHeadAttentionTest, PackedQKV_Padding_NoBias_RelPosBias) { PackedAttentionTestData data; diff --git a/onnxruntime/test/testdata/attention/attention_test_data.txt 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+0.37207031,-1.8447266,0.88818359,0.71191406,-1.3359375,0.56396484,0.52001953,0.36254883, +-0.73681641,-0.90722656,-0.29516602,0.021835327,0.030609131,-0.098083496,-0.96777344,0.75927734 +=== diff --git a/onnxruntime/test/util/include/tensors_from_file.h b/onnxruntime/test/util/include/tensors_from_file.h new file mode 100644 index 0000000000000..0e3da9d26b91a --- /dev/null +++ b/onnxruntime/test/util/include/tensors_from_file.h @@ -0,0 +1,17 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include +#include +#include + +namespace onnxruntime { +namespace test { + +// Read a dictionary of name to float tensors mapping from a text file. +void LoadTensorsFromFile(const std::string& path, std::unordered_map>& tensors); + +} // namespace test +} // namespace onnxruntime diff --git a/onnxruntime/test/util/tensors_from_file.cc b/onnxruntime/test/util/tensors_from_file.cc new file mode 100644 index 0000000000000..a99b5a5b4ea49 --- /dev/null +++ b/onnxruntime/test/util/tensors_from_file.cc @@ -0,0 +1,107 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include +#include +#include +#include +#include "test/util/include/tensors_from_file.h" +#include "core/common/common.h" + +namespace onnxruntime { +namespace test { + +static inline void TrimLeft(std::string& s) { + s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](unsigned char ch) { + return !std::isspace(ch); + })); +} + +static inline void TrimRight(std::string& s) { + s.erase(std::find_if(s.rbegin(), s.rend(), [](unsigned char ch) { + return !std::isspace(ch); + }).base(), + s.end()); +} + +static inline void Trim(std::string& s) { + TrimRight(s); + TrimLeft(s); +} + +static inline bool StartsWith(const std::string& s, const std::string& prefix) { + return s.compare(0, prefix.size(), prefix) == 0; +} + +void LoadTensorsFromFile(const std::string& path, std::unordered_map>& tensors) { + std::ifstream infile(path); + if (!infile.good()) { + ORT_THROW("Cannot open file:", path); + } + + // File format is like the following: + // name:TestCaseName1.TensorName1 + // 1.1, 2.3 + // === + // name:TestCaseName2.TensorName2 + // 3.3, 4.5, + // 5.6, 6.7 + // === + // Note that "name:" and "===" shall be at the beginning of a line without leading space! + const std::string name_prefix = "name:"; + const std::string end_tensor_prefix = "==="; + + std::string line; + while (std::getline(infile, line)) { + if (line.empty()) { + continue; + } + + std::string name; + if (StartsWith(line, name_prefix)) { + name = line.substr(name_prefix.length()); + Trim(name); + } + if (name.empty()) { + ORT_THROW("Failed to find name in line:", line); + } + + std::vector values; + while (std::getline(infile, line)) { + if (line.empty()) { + continue; + } + if (StartsWith(line, end_tensor_prefix)) { + break; + } + + std::istringstream ss(line); + for (std::string token; std::getline(ss, token, ',');) { + Trim(token); + if (token.empty()) { + continue; + } + + ORT_TRY { + float value = std::stof(token); + values.push_back(value); + } + ORT_CATCH(const std::exception&) { + ORT_THROW("Failed to parse float from name='", name, ", token='", token); + } + } + } + + if (values.size() == 0) { + ORT_THROW("No values for name=", name); + } + + auto result = tensors.insert({name, values}); + if (result.second == false) { + ORT_THROW("Failed to insert: duplicated name=", name); + } + } +} + +} // namespace test +} // namespace onnxruntime From ebcd9b5cae2ce221cfdb080eb9b9a69b48557f78 Mon Sep 17 00:00:00 2001 From: PeixuanZuo <94887879+PeixuanZuo@users.noreply.github.com> Date: Wed, 16 Aug 2023 12:33:36 +0800 Subject: [PATCH 11/12] Fix deprecated optimum interface (#17112) The `latest_model_name` argument to create an {self.__class__.__name__} is deprecated since optimum 1.6.0. Replace it with `model_name` --- .../python/tools/transformers/models/bert/eval_squad.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/onnxruntime/python/tools/transformers/models/bert/eval_squad.py b/onnxruntime/python/tools/transformers/models/bert/eval_squad.py index 66265d7b1ea71..0cbda8894528a 100644 --- a/onnxruntime/python/tools/transformers/models/bert/eval_squad.py +++ b/onnxruntime/python/tools/transformers/models/bert/eval_squad.py @@ -29,8 +29,13 @@ from evaluate import evaluator from optimum.onnxruntime import ORTModelForQuestionAnswering from optimum.onnxruntime.modeling_ort import ORTModel +from optimum.version import __version__ as optimum_version +from packaging import version as version_check from transformers import AutoTokenizer, pipeline +if version_check.parse(optimum_version) < version_check.parse("1.6.0"): + raise ImportError(f"Please install optimum>=1.6.0. The version {optimum_version} was found.") + PRETRAINED_SQUAD_MODELS = [ "bert-large-uncased-whole-word-masking-finetuned-squad", "deepset/roberta-base-squad2", @@ -62,7 +67,7 @@ def load_onnx_model( model = ORTModelForQuestionAnswering.from_pretrained(model_id, from_transformers=True) if onnx_path is not None: - model.latest_model_name = Path(onnx_path).name + model.model_name = Path(onnx_path).name if provider != "CPUExecutionProvider": model.device = torch.device("cuda:0") @@ -71,7 +76,7 @@ def load_onnx_model( model.device = torch.device("cpu") model.model = ORTModel.load_model(onnx_path) else: - onnx_path = os.path.join(model.model_save_dir.as_posix(), model.latest_model_name) + onnx_path = os.path.join(model.model_save_dir.as_posix(), model.model_name) if provider != "CPUExecutionProvider": model.to("cuda") From 8998b6811dd654c84c773d447807265b82acfa9d Mon Sep 17 00:00:00 2001 From: Jian Chen Date: Tue, 15 Aug 2023 22:56:38 -0700 Subject: [PATCH 12/12] Fix NPM Packaging Pipeline (#17182) ### Description ### Motivation and Context --- .../ci_build/github/azure-pipelines/npm-packaging-pipeline.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/ci_build/github/azure-pipelines/npm-packaging-pipeline.yml b/tools/ci_build/github/azure-pipelines/npm-packaging-pipeline.yml index 93ace4e303606..ec85002503c0e 100644 --- a/tools/ci_build/github/azure-pipelines/npm-packaging-pipeline.yml +++ b/tools/ci_build/github/azure-pipelines/npm-packaging-pipeline.yml @@ -51,7 +51,7 @@ stages: BuildConfig: 'Release' PoolName: 'onnxruntime-Ubuntu2004-AMD-CPU' PackageName: 'onnxruntime-react-native' - BuildAndroidAARStageDependsOn: 'Extract_commit' + BuildAndroidAARStageDependsOn: 'Precheck_and_extract_commit' - stage: Download_Node_Package_And_Publish_Validation_Script dependsOn: