Merge branch 'main' of https://github.com/microsoft/onnxruntime into …

…baijumeswani/update-checkpoint-params

.gitmodules

@@ -8,6 +8,3 @@
 	path = cmake/external/emsdk
 	url = https://github.com/emscripten-core/emsdk.git
 	branch = 3.1.44
-[submodule "cmake/external/onnxruntime-extensions"]
-	path = cmake/external/onnxruntime-extensions
-	url = https://github.com/microsoft/onnxruntime-extensions.git

VERSION_NUMBER

@@ -1 +1 @@
-1.16.0
+1.17.0

cmake/onnxruntime_rocm_hipify.cmake

@@ -10,6 +10,9 @@ set(contrib_ops_excluded_files
   "bert/attention_impl.cu"
   "bert/attention_softmax.h"
   "bert/attention_softmax.cu"
+  "bert/attention_prepare_qkv.cu"
+  "bert/decoder_attention_impl.h"
+  "bert/decoder_attention_impl.cu"
   "bert/decoder_masked_multihead_attention.h"
   "bert/decoder_masked_multihead_attention.cc"
   "bert/decoder_masked_self_attention.h"

csharp/src/Microsoft.ML.OnnxRuntime/Training/NativeTrainingMethods.shared.cs

@@ -65,10 +65,10 @@ static NativeTrainingMethods()
                 DOrtGetApi OrtGetApi = (DOrtGetApi)Marshal.GetDelegateForFunctionPointer(NativeMethods.OrtGetApiBase().GetApi, typeof(DOrtGetApi));
 
                 // TODO: Make this save the pointer, and not copy the whole structure across
-                api_ = (OrtApi)OrtGetApi(16 /*ORT_API_VERSION*/);
+                api_ = (OrtApi)OrtGetApi(17 /*ORT_API_VERSION*/);
 
                 OrtGetTrainingApi = (DOrtGetTrainingApi)Marshal.GetDelegateForFunctionPointer(api_.GetTrainingApi, typeof(DOrtGetTrainingApi));
-                trainingApiPtr = OrtGetTrainingApi(16 /*ORT_API_VERSION*/);
+                trainingApiPtr = OrtGetTrainingApi(17 /*ORT_API_VERSION*/);
                 if (trainingApiPtr != IntPtr.Zero)
                 {
                     trainingApi_ = (OrtTrainingApi)Marshal.PtrToStructure(trainingApiPtr, typeof(OrtTrainingApi));

docs/ContribOperators.md

@@ -1351,8 +1351,8 @@ This version of the operator has been available since version 1 of the 'com.micr
 #### Type Constraints
 
 <dl>
-<dt><tt>T1</tt> : tensor(int8), tensor(uint8), tensor(int32)</dt>
-<dd>Constrain 'x' and 'x_zero_point' to 8-bit integer tensors or 32-bit signed integer tensors.</dd>
+<dt><tt>T1</tt> : tensor(int8), tensor(uint8), tensor(int16), tensor(uint16), tensor(int32)</dt>
+<dd>Constrain 'x' and 'x_zero_point' to 8-bit integer tensors, 16-bit integer tensors, or 32-bit signed integer tensors.</dd>
 <dt><tt>T2</tt> : tensor(float16), tensor(float)</dt>
 <dd>Constrain 'y', 'x_scale' to float tensors.</dd>
 </dl>
@@ -4194,8 +4194,9 @@ This version of the operator has been available since version 1 of the 'com.micr
 ### <a name="com.microsoft.QuantizeLinear"></a><a name="com.microsoft.quantizelinear">**com.microsoft.QuantizeLinear**</a>
 
   The linear quantization operator. It consumes a full precision data, a scale, a zero point to compute the low precision / quantized tensor.
-  The quantization formula is y = saturate ((x / y_scale) + y_zero_point).For saturation, it saturates to [0, 255] if it's uint8, or [-128, 127] if it's int8.
-  For (x / y_scale), it's rounding to nearest ties to even. Refer to https://en.wikipedia.org/wiki/Rounding for details.
+  The quantization formula is y = saturate ((x / y_scale) + y_zero_point). For saturation, it saturates to [0, 255] if it's uint8, [-128, 127] if it's int8,
+  [0, 65,535] if it's uint16, and [-32,768, 32,767] if it's int16. For (x / y_scale), it's rounding to nearest ties to even.
+  Refer to https://en.wikipedia.org/wiki/Rounding for details.
   Scale and zero point must have same shape. They must be either scalar (per tensor) or 1-D tensor (per 'axis').
 
 #### Version
@@ -4232,8 +4233,8 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dl>
 <dt><tt>T1</tt> : tensor(float16), tensor(float)</dt>
 <dd>Constrain 'x', 'y_scale' to float tensors.</dd>
-<dt><tt>T2</tt> : tensor(int8), tensor(uint8)</dt>
-<dd>Constrain 'y_zero_point' and 'y' to 8-bit integer tensors.</dd>
+<dt><tt>T2</tt> : tensor(int8), tensor(uint8), tensor(int16), tensor(uint16)</dt>
+<dd>Constrain 'y_zero_point' and 'y' to 8-bit and 16-bit integer tensors.</dd>
 </dl>
 
 

docs/OperatorKernels.md

@@ -439,7 +439,7 @@ Do not modify directly.*
 |CDist|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|1+|**T** = tensor(double), tensor(float)|
 |ConvTransposeWithDynamicPads|*in* X:**T**<br> *in* W:**T**<br> *in* Pads:**tensor(int64)**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float)|
 |CropAndResize|*in* X:**T1**<br> *in* rois:**T1**<br> *in* batch_indices:**T2**<br> *in* crop_size:**T2**<br> *out* Y:**T1**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int32)|
-|DequantizeLinear|*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**|1+|**T1** = tensor(int32), tensor(int8), tensor(uint8)<br/> **T2** = tensor(float)|
+|DequantizeLinear|*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**|1+|**T1** = tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint8)<br/> **T2** = tensor(float)|
 |DynamicQuantizeLSTM|*in* X:**T**<br> *in* W:**T2**<br> *in* R:**T2**<br> *in* B:**T**<br> *in* sequence_lens:**T1**<br> *in* initial_h:**T**<br> *in* initial_c:**T**<br> *in* P:**T**<br> *in* W_scale:**T**<br> *in* W_zero_point:**T2**<br> *in* R_scale:**T**<br> *in* R_zero_point:**T2**<br> *out* Y:**T**<br> *out* Y_h:**T**<br> *out* Y_c:**T**|1+|**T** = tensor(float)<br/> **T1** = tensor(int32)<br/> **T2** = tensor(int8), tensor(uint8)|
 |DynamicQuantizeMatMul|*in* A:**T1**<br> *in* B:**T2**<br> *in* b_scale:**T1**<br> *in* b_zero_point:**T2**<br> *in* bias:**T1**<br> *out* Y:**T1**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int8), tensor(uint8)|
 |EmbedLayerNormalization|*in* input_ids:**T1**<br> *in* segment_ids:**T1**<br> *in* word_embedding:**T**<br> *in* position_embedding:**T**<br> *in* segment_embedding:**T**<br> *in* gamma:**T**<br> *in* beta:**T**<br> *in* mask:**T1**<br> *in* position_ids:**T1**<br> *out* output:**T**<br> *out* mask_index:**T1**<br> *out* embedding_sum:**T**|1+|**T** = tensor(float)|
@@ -472,7 +472,7 @@ Do not modify directly.*
 |QLinearSigmoid|*in* X:**T**<br> *in* X_scale:**tensor(float)**<br> *in* X_zero_point:**T**<br> *in* Y_scale:**tensor(float)**<br> *in* Y_zero_point:**T**<br> *out* Y:**T**|1+|**T** = tensor(int8), tensor(uint8)|
 |QLinearSoftmax|*in* X:**T**<br> *in* X_scale:**tensor(float)**<br> *in* x_zero_point:**T**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T**<br> *out* Y:**T**|1+|**T** = tensor(int8), tensor(uint8)|
 |QLinearWhere|*in* condition:**B**<br> *in* X:**T**<br> *in* x_scale:**TF**<br> *in* x_zero_point:**T**<br> *in* Y:**T**<br> *in* y_scale:**TF**<br> *in* y_zero_point:**T**<br> *in* z_scale:**TF**<br> *in* z_zero_point:**T**<br> *out* Z:**T**|1+|**T** = tensor(int8), tensor(uint8)|
-|QuantizeLinear|*in* x:**T1**<br> *in* y_scale:**T1**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int8), tensor(uint8)|
+|QuantizeLinear|*in* x:**T1**<br> *in* y_scale:**T1**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int16), tensor(int8), tensor(uint16), tensor(uint8)|
 |QuickGelu|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(float)|
 |Range|*in* start:**T**<br> *in* limit:**T**<br> *in* delta:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)|
 |SampleOp|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(float)|

docs/c_cxx/doxygen-header.html

@@ -16,7 +16,7 @@
 <!--END DISABLE_INDEX-->
 <script type="text/javascript" src="$relpath^jquery.js"></script>
 <script type="text/javascript" src="$relpath^dynsections.js"></script>
-<script async src="https://www.googletagmanager.com/gtag/js?id=UA-156955408-1"></script><script type="text/javascript">"use strict"; window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'UA-156955408-1'); </script> <script type="text/javascript" src="/assets/js/vendor/lunr.min.js"></script> <script type="text/javascript" src="/assets/js/just-the-docs.js"></script>
+<script async src="https://www.googletagmanager.com/gtag/js?id=UA-156955408-1"></script><script type="text/javascript">"use strict"; window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'UA-156955408-1'); </script>
 $treeview
 $search
 $mathjax

docs/python/README.rst

@@ -8,6 +8,11 @@ For more information on ONNX Runtime, please see `aka.ms/onnxruntime <https://ak
 Changes
 -------
 
+1.17.0
+^^^^^^
+
+Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.17.0
+
 1.16.0
 ^^^^^^
 

include/onnxruntime/core/graph/graph.h

@@ -1135,6 +1135,7 @@ class Graph {
 
   /**
   Directly insert the nodes in the function Node provided into this Graph.
+  The Graph needs to be Resolve()d after this call.
   @param node Node with Node::Type of Node::Type::Fused
   @returns Status indicating success or providing an error message.
   */

include/onnxruntime/core/session/onnxruntime_c_api.h

@@ -37,7 +37,7 @@
  *
  * This value is used by some API functions to behave as this version of the header expects.
  */
-#define ORT_API_VERSION 16
+#define ORT_API_VERSION 17
 
 #ifdef __cplusplus
 extern "C" {

js/common/lib/version.ts

@@ -4,4 +4,4 @@
 // This file is generated by /js/scripts/update-version.ts
 // Do not modify file content manually.
 
-export const version = '1.16.0';
+export const version = '1.17.0';

js/common/package.json

@@ -2,7 +2,7 @@
   "license": "MIT",
   "type": "module",
   "name": "onnxruntime-common",
-  "version": "1.16.0",
+  "version": "1.17.0",
   "repository": {
     "url": "https://github.com/Microsoft/onnxruntime.git",
     "type": "git"

js/node/lib/version.ts

@@ -4,4 +4,4 @@
 // This file is generated by /js/scripts/update-version.ts
 // Do not modify file content manually.
 
-export const version = '1.16.0';
+export const version = '1.17.0';

js/node/package.json

@@ -13,7 +13,7 @@
       3
     ]
   },
-  "version": "1.16.0",
+  "version": "1.17.0",
   "dependencies": {
     "onnxruntime-common": "file:../common"
   },

js/react_native/lib/version.ts

@@ -4,4 +4,4 @@
 // This file is generated by /js/scripts/update-version.ts
 // Do not modify file content manually.
 
-export const version = '1.16.0';
+export const version = '1.17.0';

js/react_native/package.json

@@ -36,7 +36,7 @@
     "registry": "https://registry.npmjs.org/"
   },
   "source": "lib/index",
-  "version": "1.16.0",
+  "version": "1.17.0",
   "main": "dist/commonjs/index",
   "homepage": "https://github.com/microsoft/onnxruntime/blob/main/js/react_native/README.md",
   "files": [

js/react_native/yarn.lock

@@ -5188,7 +5188,7 @@ onetime@^5.1.0, onetime@^5.1.2:
     mimic-fn "^2.1.0"
 
 "onnxruntime-common@file:../common":
-  version "1.16.0"
+  version "1.17.0"
 
 open@^6.2.0:
   version "6.4.0"

js/web/docs/webgpu-operators.md

@@ -46,6 +46,7 @@ Do not modify directly.*
 | GlobalMaxPool | ai.onnx(1+); com.ms.internal.nhwc(1+) |  |
 | Greater | ai.onnx(7-8,9-12,13+) |  |
 | GreaterOrEqual | ai.onnx(12-15,16+) |  |
+| If | ai.onnx(1-10,11-12,13-18,19+) |  |
 | InstanceNormalization | ai.onnx(6+); com.ms.internal.nhwc(6+) |  |
 | LayerNormalization | ai.onnx(17+) |  |
 | LeakyRelu | ai.onnx(6-15,16+) |  |

js/web/lib/version.ts

@@ -4,4 +4,4 @@
 // This file is generated by /js/scripts/update-version.ts
 // Do not modify file content manually.
 
-export const version = '1.16.0';
+export const version = '1.17.0';

js/web/lib/wasm/jsep/backend-webgpu.ts

@@ -4,7 +4,7 @@
 import {Env} from 'onnxruntime-common';
 
 import {configureLogger, LOG_DEBUG} from './log';
-import {TensorView} from './tensor';
+import {TensorView} from './tensor-view';
 import {createGpuDataManager, GpuDataManager} from './webgpu/gpu-data-manager';
 import {RunFunction, WEBGPU_OP_RESOLVE_RULES} from './webgpu/op-resolve-rules';
 import {ProgramManager} from './webgpu/program-manager';

js/web/lib/wasm/jsep/init.ts

@@ -8,7 +8,7 @@ import {DataType, getTensorElementSize} from '../wasm-common';
 
 import {WebGpuBackend} from './backend-webgpu';
 import {LOG_DEBUG} from './log';
-import {TensorView} from './tensor';
+import {TensorView} from './tensor-view';
 import {ShapeUtil} from './util';
 import {ComputeContext, ComputeContextInputsOutputsMapping, ProgramInfo, ProgramInfoLoader} from './webgpu/types';
 

js/web/lib/wasm/jsep/tensor-view.ts

@@ -0,0 +1,39 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+import {Tensor} from 'onnxruntime-common';
+
+import {tensorTypeToTypedArrayConstructor} from '../wasm-common';
+
+export const createView = (dataBuffer: ArrayBuffer, type: Tensor.Type): Int32Array|Uint32Array|BigInt64Array|
+    BigUint64Array|Uint8Array|Float32Array|Float64Array|Int8Array|Int16Array|Uint16Array =>
+        new (tensorTypeToTypedArrayConstructor(type))(dataBuffer);
+
+/**
+ * a TensorView does not own the data.
+ */
+export interface TensorView {
+  readonly data: number;
+  readonly dataType: number;
+  readonly dims: readonly number[];
+
+  /**
+   * get a Float32Array data view of the tensor data. tensor data must be on CPU.
+   */
+  getFloat32Array(): Float32Array;
+
+  /**
+   * get a BigInt64Array data view of the tensor data. tensor data must be on CPU.
+   */
+  getBigInt64Array(): BigInt64Array;
+
+  /**
+   * get a Int32Array data view of the tensor data. tensor data must be on CPU.
+   */
+  getInt32Array(): Int32Array;
+
+  /**
+   * create a new tensor view with the same data but different dimensions.
+   */
+  reshape(newDims: readonly number[]): TensorView;
+}