Merge branch 'main' into fused_conv_hardSigmoid

cgmanifests/generated/cgmanifest.json

@@ -36,7 +36,7 @@
       "component": {
         "type": "git",
         "git": {
-          "commitHash": "dcd5bd5fd593e31465af3d9ef291d26c646b0a4f",
+          "commitHash": "4a2c63365eff8823a5221db86ef490e828306f9d",
           "repositoryUrl": "https://github.com/abseil/abseil-cpp.git"
         },
         "comments": "abseil_cpp"
@@ -192,6 +192,16 @@
         "comments": "mp11"
       }
     },
+    {
+      "component": {
+        "type": "git",
+        "git": {
+          "commitHash": "c11386eb632eec7c1c2aa323142f73519f946e2a",
+          "repositoryUrl": "https://github.com/intel/neural-speed.git"
+        },
+        "comments": "neural_speed"
+      }
+    },
     {
       "component": {
         "type": "git",

cmake/deps.txt

@@ -12,7 +12,7 @@
 # NOTE: You must run deps_update_and_upload.py and generate_cgmanifest.py when ready to test your changes in a CI.
 # See https://microsoft.sharepoint.com/teams/ONNX2/_layouts/OneNote.aspx?id=%2Fteams%2FONNX2%2FShared%20Documents%2FNotebooks%2FONNX%20Ecosystem%20Team%20Notebook&wd=target%28Development.one%7C63D3AB47-51D1-4A62-9965-66882234BD44%2FAdd%20or%20update%20a%20dependency%20in%20deps.txt%7C0E9ED71D-89D5-40FA-B05F-C0123289C591%2F%29
 #
-abseil_cpp;https://github.com/abseil/abseil-cpp/archive/dcd5bd5fd593e31465af3d9ef291d26c646b0a4f.zip;6cc204586014e189f5c0fe3274f83162fa7c700c
+abseil_cpp;https://github.com/abseil/abseil-cpp/archive/refs/tags/20240116.0.zip;bc2cec6baaad67fcb6c0c38972b687d4797927e9
 cxxopts;https://github.com/jarro2783/cxxopts/archive/3c73d91c0b04e2b59462f0a741be8c07024c1bc0.zip;6c6ca7f8480b26c8d00476e0e24b7184717fe4f0
 date;https://github.com/HowardHinnant/date/archive/refs/tags/v3.0.1.zip;2dac0c81dc54ebdd8f8d073a75c053b04b56e159
 dlpack;https://github.com/dmlc/dlpack/archive/refs/tags/v0.6.zip;4d565dd2e5b31321e5549591d78aa7f377173445
@@ -34,6 +34,7 @@ microsoft_gsl;https://github.com/microsoft/GSL/archive/refs/tags/v4.0.0.zip;cf36
 microsoft_wil;https://github.com/microsoft/wil/archive/refs/tags/v1.0.230629.1.zip;e4a542a323c070376f7c2d1973d0f7ddbc1d2fa5
 mimalloc;https://github.com/microsoft/mimalloc/archive/refs/tags/v2.1.1.zip;d5ee7d34223d0567892db5179849939c8769dc41
 mp11;https://github.com/boostorg/mp11/archive/refs/tags/boost-1.82.0.zip;9bc9e01dffb64d9e0773b2e44d2f22c51aace063
+neural_speed;https://github.com/intel/neural-speed/archive/refs/tags/bestlav0.1.1.zip;65b0f7a0d04f72f0d5a8d48af70f0366f2ab3939
 onnx;https://github.com/onnx/onnx/archive/refs/tags/v1.15.0.zip;54c3f960a0541c5d8d3e60c2933e11f5d3688a11
 #use the commit of supporting all the plugins and TRT 8.6-GA (https://github.com/onnx/onnx-tensorrt/commit/0462dc31ae78f48744b6141ae376df1f96d3f459)
 onnx_tensorrt;https://github.com/onnx/onnx-tensorrt/archive/a43ce67187bab219520fd80f21af8bbd4354bc8c.zip;572535aefef477050f86744dfab1fef840198035

cmake/external/abseil-cpp.cmake

@@ -19,7 +19,7 @@ if(WIN32 AND NOT Patch_FOUND)
   set(ABSL_ENABLE_INSTALL ON)
 endif()
 # NB! Advancing Abseil version changes its internal namespace,
-# currently absl::lts_20230125 which affects abseil-cpp.natvis debugger
+# currently absl::lts_20240116 which affects abseil-cpp.natvis debugger
 # visualization file, that must be adjusted accordingly, unless we eliminate
 # that namespace at build time.
 FetchContent_Declare(

cmake/external/abseil-cpp.natvis

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="utf-8"?>
 <AutoVisualizer xmlns="http://schemas.microsoft.com/vstudio/debugger/natvis/2010">
-  <Type Name="absl::lts_20230802::InlinedVector&lt;*&gt;">
+  <Type Name="absl::lts_20240116::InlinedVector&lt;*&gt;">
     <Intrinsic Name="_size" Expression="storage_.metadata_.value >> 1"/>
     <Intrinsic Name="_is_allocated" Expression="(storage_.metadata_.value &amp; 1) == 1"/>
     <Intrinsic Name="_inlined_data" Expression="($T1*)storage_.data_.inlined.inlined_data"/>
@@ -24,7 +24,7 @@
     </Expand>
   </Type>
   <!-- Should handle both flat hash_set and hash_map -->
-  <Type Name="absl::lts_20230802::container_internal::raw_hash_set&lt;*&gt;">
+  <Type Name="absl::lts_20240116::container_internal::raw_hash_set&lt;*&gt;">
     <Intrinsic Name="_commonfields" Expression="settings_.value"/>
     <Intrinsic Name="_size" Expression="settings_.value.compressed_tuple_.value"/>
     <Intrinsic Name="_capacity" Expression="_commonfields().capacity_"/>
@@ -51,7 +51,7 @@
   </Type>
 
   <!-- Primitive types stored as a value -->
-  <Type Name="absl::lts_20230802::container_internal::Storage&lt;*,*,0&gt;">
+  <Type Name="absl::lts_20240116::container_internal::Storage&lt;*,*,0&gt;">
     <DisplayString IncludeView="noparens">*($T1 *){value}</DisplayString>
     <DisplayString ExcludeView="noparens">(*($T1 *){value})</DisplayString>
     <Expand>
@@ -60,15 +60,15 @@
   </Type>
 
   <!-- For storage inherited from the type -->
-  <Type Name="absl::lts_20230802::container_internal::Storage&lt;*,*,1&gt;">
+  <Type Name="absl::lts_20240116::container_internal::Storage&lt;*,*,1&gt;">
     <DisplayString IncludeView="noparens">*($T1 *)this</DisplayString>
     <DisplayString ExcludeView="noparens">(*($T1 *)this)</DisplayString>
     <Expand>
       <ExpandedItem>*($T1 *)this</ExpandedItem>
     </Expand>
   </Type>
 
-  <Type Name="absl::lts_20230802::container_internal::map_slot_type&lt;*&gt;">
+  <Type Name="absl::lts_20240116::container_internal::map_slot_type&lt;*&gt;">
     <DisplayString IncludeView="noparens">{value.first}, {value.second}</DisplayString>
     <DisplayString ExcludeView="noparens">({value.first}, {value.second})</DisplayString>
     <Expand>

cmake/external/neural_speed.cmake

@@ -7,12 +7,9 @@ endif()
 if(USE_NEURAL_SPEED)
   FetchContent_Declare(
       neural_speed
-      URL https://github.com/intel/neural-speed/archive/refs/tags/bestlav0.1.1.zip
-      URL_HASH SHA1=65b0f7a0d04f72f0d5a8d48af70f0366f2ab3939
+      URL ${DEP_URL_neural_speed}
+      URL_HASH SHA1=${DEP_SHA1_neural_speed}
   )
   set(BTLA_USE_OPENMP OFF)
-  FetchContent_MakeAvailable(neural_speed)
-  if(NOT neural_speed_POPULATED)
-    FetchContent_Populate(neural_speed)
-  endif()
+  onnxruntime_fetchcontent_makeavailable(neural_speed)
 endif()

cmake/external/xnnpack.cmake

@@ -6,10 +6,14 @@ set(FP16_BUILD_BENCHMARKS OFF CACHE INTERNAL "")
 set(PTHREADPOOL_BUILD_TESTS OFF CACHE INTERNAL "")
 set(PTHREADPOOL_BUILD_BENCHMARKS OFF CACHE INTERNAL "")
 
+if(CMAKE_SYSTEM_PROCESSOR MATCHES "^riscv64.*")
+  set(XNNPACK_USE_SYSTEM_LIBS OFF)
+endif()
+
 # BF16 instructions cause ICE in Android NDK compiler
 if(CMAKE_ANDROID_ARCH_ABI STREQUAL armeabi-v7a)
   set(XNNPACK_ENABLE_ARM_BF16 OFF)
-ENDIF()
+endif()
 
 # fp16 depends on psimd
 FetchContent_Declare(psimd URL ${DEP_URL_psimd} URL_HASH SHA1=${DEP_SHA1_psimd})

cmake/onnxruntime_common.cmake

@@ -189,6 +189,8 @@ elseif(NOT CMAKE_SYSTEM_NAME STREQUAL "Emscripten")
       set(ARM TRUE)
     elseif(dumpmachine_output MATCHES "^aarch64.*")
       set(ARM64 TRUE)
+    elseif(CMAKE_SYSTEM_PROCESSOR MATCHES "^riscv64.*")
+      set(RISCV64 TRUE)
     elseif(CMAKE_SYSTEM_PROCESSOR MATCHES "^(i.86|x86?)$")
       set(X86 TRUE)
     elseif(CMAKE_SYSTEM_PROCESSOR MATCHES "^(x86_64|amd64)$")
@@ -198,7 +200,7 @@ elseif(NOT CMAKE_SYSTEM_NAME STREQUAL "Emscripten")
 endif()
 
 
-if (ARM64 OR ARM OR X86 OR X64 OR X86_64)
+if (RISCV64 OR ARM64 OR ARM OR X86 OR X64 OR X86_64)
   if((WIN32 AND NOT CMAKE_CXX_STANDARD_LIBRARIES MATCHES kernel32.lib) OR ((ARM64 OR ARM) AND MSVC))
     # msvc compiler report syntax error with cpuinfo arm source files
     # and cpuinfo does not have code for getting arm uarch info under windows

cmake/onnxruntime_unittests.cmake

@@ -1277,6 +1277,9 @@ if (NOT onnxruntime_ENABLE_TRAINING_TORCH_INTEROP)
     if (onnxruntime_USE_CUDA)
       list(APPEND onnxruntime_shared_lib_test_LIBS cudart)
     endif()
+    if (onnxruntime_USE_ROCM)
+      list(APPEND onnxruntime_shared_lib_test_LIBS hip::host)
+    endif()
     if (onnxruntime_USE_TENSORRT)
       list(APPEND onnxruntime_shared_lib_test_LIBS ${TENSORRT_LIBRARY_INFER})
     endif()
@@ -1294,6 +1297,10 @@ if (NOT onnxruntime_ENABLE_TRAINING_TORCH_INTEROP)
       target_include_directories(onnxruntime_shared_lib_test PRIVATE ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES})
       target_sources(onnxruntime_shared_lib_test PRIVATE ${ONNXRUNTIME_SHARED_LIB_TEST_SRC_DIR}/cuda_ops.cu)
     endif()
+    if (onnxruntime_USE_ROCM)
+      target_include_directories(onnxruntime_shared_lib_test PRIVATE ${onnxruntime_ROCM_HOME}/include)
+      target_compile_definitions(onnxruntime_shared_lib_test PRIVATE __HIP_PLATFORM_AMD__)
+    endif()
     if (CMAKE_SYSTEM_NAME STREQUAL "Android")
       target_sources(onnxruntime_shared_lib_test PRIVATE
         "${ONNXRUNTIME_ROOT}/core/platform/android/cxa_demangle.cc"

cmake/riscv64.toolchain.cmake

@@ -0,0 +1,35 @@
+# Copyright (c) 2024 SiFive, Inc. All rights reserved.
+# Copyright (c) 2024, Phoebe Chen <[email protected]>
+# Licensed under the MIT License.
+
+set(CMAKE_SYSTEM_NAME Linux)
+set(CMAKE_SYSTEM_PROCESSOR riscv64)
+
+list(APPEND CMAKE_TRY_COMPILE_PLATFORM_VARIABLES RISCV_TOOLCHAIN_ROOT)
+
+if(NOT RISCV_TOOLCHAIN_ROOT)
+  message(FATAL_ERROR "RISCV_TOOLCHAIN_ROOT is not defined. Please set the RISCV_TOOLCHAIN_ROOT variable.")
+endif()
+
+set(CMAKE_C_COMPILER "${RISCV_TOOLCHAIN_ROOT}/bin/riscv64-unknown-linux-gnu-gcc")
+set(CMAKE_ASM_COMPILER "${RISCV_TOOLCHAIN_ROOT}/bin/riscv64-unknown-linux-gnu-gcc")
+set(CMAKE_CXX_COMPILER "${RISCV_TOOLCHAIN_ROOT}/bin/riscv64-unknown-linux-gnu-g++")
+
+set(CMAKE_FIND_ROOT_PATH ${RISCV_TOOLCHAIN_ROOT})
+set(CMAKE_SYSROOT "${RISCV_TOOLCHAIN_ROOT}/sysroot")
+set(CMAKE_INCLUDE_PATH "${RISCV_TOOLCHAIN_ROOT}/sysroot/usr/include/")
+set(CMAKE_LIBRARY_PATH "${RISCV_TOOLCHAIN_ROOT}/sysroot/usr/lib/")
+set(CMAKE_PROGRAM_PATH "${RISCV_TOOLCHAIN_ROOT}/sysroot/usr/bin/")
+
+if(RISCV_QEMU_PATH)
+  message(STATUS "RISCV_QEMU_PATH=${RISCV_QEMU_PATH} is defined during compilation.")
+  set(CMAKE_CROSSCOMPILING_EMULATOR "${RISCV_QEMU_PATH};-L;${CMAKE_SYSROOT}")
+endif()
+
+set(CMAKE_CROSSCOMPILING TRUE)
+
+set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
+set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)
+set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)
+set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)
+

docs/ContribOperators.md

@@ -2398,24 +2398,28 @@ This version of the operator has been available since version 1 of the 'com.micr
 #### Attributes
 
 <dl>
+<dt><tt>do_rotary</tt> : int</dt>
+<dd>Whether to use rotary position embedding. Default value is 0.</dd>
 <dt><tt>kv_num_heads</tt> : int (required)</dt>
 <dd>Number of attention heads for k and v</dd>
 <dt><tt>local_window_size</tt> : int</dt>
 <dd>left_window_size for local attention (like Mistral). Default value is -1 meaning unused.</dd>
 <dt><tt>num_heads</tt> : int (required)</dt>
 <dd>Number of attention heads for q</dd>
+<dt><tt>rotary_interleaved</tt> : int</dt>
+<dd>Rotate using interleaved pattern. Default value is 0 (False).</dd>
 <dt><tt>scale</tt> : float</dt>
 <dd>Custom scale will be used if specified. Default value is 1/sqrt(head_size)</dd>
 </dl>
 
-#### Inputs
+#### Inputs (7 - 9)
 
 <dl>
 <dt><tt>query</tt> : T</dt>
-<dd>Query with shape (batch_size, sequence_length, hidden_size)</dd>
-<dt><tt>key</tt> : T</dt>
+<dd>Query with shape (batch_size, sequence_length, hidden_size), or packed QKV with shape(batch_size, sequence_length, d) where d is (num_heads * head_size + 2 * kv_num_heads * head_size).</dd>
+<dt><tt>key</tt> (optional) : T</dt>
 <dd>Key with shape (batch_size, kv_sequence_length, kv_hidden_size) </dd>
-<dt><tt>value</tt> : T</dt>
+<dt><tt>value</tt> (optional) : T</dt>
 <dd>Value with shape (batch_size, kv_sequence_length, kv_hidden_size)</dd>
 <dt><tt>past_key</tt> (optional) : T</dt>
 <dd>past state key with support for format BNSH. When past_key uses same tensor as present_key(k-v cache), it is of length max_sequence_length... otherwise of length past_sequence_length.</dd>
@@ -2425,6 +2429,10 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dd>1d Tensor of shape (batch_size). Indicates past sequence lengths for token generation case.</dd>
 <dt><tt>total_sequence_length</tt> : M</dt>
 <dd>Scalar tensor of total sequence length (past + new).</dd>
+<dt><tt>cos_cache</tt> (optional) : T</dt>
+<dd>2D tensor with shape (max_sequence_length, head_size / 2).</dd>
+<dt><tt>sin_cache</tt> (optional) : T</dt>
+<dd>2D tensor with shape (max_sequence_length, head_size / 2).</dd>
 </dl>
 
 #### Outputs
@@ -5761,7 +5769,7 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dd>Size of the vocabulary. If not provided, it will be inferred from the decoder subgraph's output shape</dd>
 </dl>
 
-#### Inputs (5 - 14)
+#### Inputs (5 - 15)
 
 <dl>
 <dt><tt>input_ids</tt> : F</dt>
@@ -5792,6 +5800,8 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dd>Only keep this list of (layer, head) of QK in the final cross_qk output when use_cross_qk is set. Default collect allits shape is (number of (layer, head) to keep, 2), i.e., [[layer_id1, head_id1], [layer_id2, head_id2]......]</dd>
 <dt><tt>extra_decoding_ids</tt> (optional) : I</dt>
 <dd>Part of the decoder_input_ids that we need cross qk for it. it is of shape  (batch_size, extra_decoding_ids_len).In such case, we should remove this from the tail of the decoder_input_ids, and put it here. ids < 0 in it (for multiple batch) are treated as stop of the extra_decoding_ids for corresponding batch.</dd>
+<dt><tt>temperature</tt> (optional) : T</dt>
+<dd>Temperature value to apply to logits processing during this execution's decoding. Shape is (1)</dd>
 </dl>
 
 #### Outputs (1 - 5)

docs/OperatorKernels.md

@@ -499,7 +499,7 @@ Do not modify directly.*
 |TransposeMatMul|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float)|
 |Trilu|*in* X:**T**<br> *in* k:**tensor(int64)**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(int64)|
 |Unique|*in* x:**T**<br> *out* y:**T**<br> *out* idx:**tensor(int64)**<br> *out* counts:**tensor(int64)**|1+|**T** = tensor(float)|
-|WhisperBeamSearch|*in* input_ids:**F**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* num_beams:**I**<br> *in* num_return_sequences:**I**<br> *in* length_penalty:**T**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**M**<br> *in* prefix_vocab_mask:**M**<br> *in* attention_mask:**I**<br> *in* decoder_input_ids:**I**<br> *in* logits_processor:**I**<br> *in* cross_qk_layer_head:**I**<br> *in* extra_decoding_ids:**I**<br> *out* sequences:**I**<br> *out* sequences_scores:**T**<br> *out* scores:**T**<br> *out* cross_qk:**V**<br> *out* non_speech_probs:**T**|1+|**T** = tensor(float)|
+|WhisperBeamSearch|*in* input_ids:**F**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* num_beams:**I**<br> *in* num_return_sequences:**I**<br> *in* length_penalty:**T**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**M**<br> *in* prefix_vocab_mask:**M**<br> *in* attention_mask:**I**<br> *in* decoder_input_ids:**I**<br> *in* logits_processor:**I**<br> *in* cross_qk_layer_head:**I**<br> *in* extra_decoding_ids:**I**<br> *in* temperature:**T**<br> *out* sequences:**I**<br> *out* sequences_scores:**T**<br> *out* scores:**T**<br> *out* cross_qk:**V**<br> *out* non_speech_probs:**T**|1+|**T** = tensor(float)|
 |WordConvEmbedding|*in* Sequence:**T**<br> *in* W:**T1**<br> *in* B:**T1**<br> *in* C:**T1**<br> *out* Y:**T1**|1+|**T** = tensor(int32)<br/> **T1** = tensor(float)|
 | |
 | |
@@ -682,7 +682,8 @@ Do not modify directly.*
 |PRelu|*in* X:**T**<br> *in* slope:**T**<br> *out* Y:**T**|16+|**T** = tensor(double), tensor(float), tensor(float16)|
 |||[9, 15]|**T** = tensor(double), tensor(float), tensor(float16)|
 |||[7, 8]|**T** = tensor(double), tensor(float), tensor(float16)|
-|Pad|*in* data:**T**<br> *in* pads:**tensor(int64)**<br> *in* constant_value:**T**<br> *in* axes:**Tind**<br> *out* output:**T**<br><br>or<br><br>*in* data:**T**<br> *in* pads:**tensor(int64)**<br> *in* constant_value:**T**<br> *out* output:**T**<br><br>or<br><br>*in* data:**T**<br> *out* output:**T**|13+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16)|
+|Pad|*in* data:**T**<br> *in* pads:**tensor(int64)**<br> *in* constant_value:**T**<br> *in* axes:**Tind**<br> *out* output:**T**<br><br>or<br><br>*in* data:**T**<br> *in* pads:**tensor(int64)**<br> *in* constant_value:**T**<br> *out* output:**T**<br><br>or<br><br>*in* data:**T**<br> *out* output:**T**|18+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16)|
+|||[13, 17]|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16)|
 |||[11, 12]|**T** = tensor(double), tensor(float), tensor(float16)|
 |||[2, 10]|**T** = tensor(double), tensor(float), tensor(float16)|
 |ParametricSoftplus|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(float16)|
@@ -843,7 +844,7 @@ Do not modify directly.*
 |GreedySearch|*in* input_ids:**I**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**I**<br> *in* prefix_vocab_mask:**I**<br> *in* attention_mask:**I**<br> *out* sequences:**I**|1+|**T** = tensor(float), tensor(float16)|
 |GridSample|*in* X:**T1**<br> *in* Grid:**T1**<br> *out* Y:**T2**|1+|**T1** = tensor(float)<br/> **T2** = tensor(float)|
 |GroupNorm|*in* X:**T**<br> *in* gamma:**M**<br> *in* beta:**M**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
-|GroupQueryAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *in* seqlens_k:**M**<br> *in* total_sequence_length:**M**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(bfloat16), tensor(float16)|
+|GroupQueryAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *in* seqlens_k:**M**<br> *in* total_sequence_length:**M**<br> *in* cos_cache:**T**<br> *in* sin_cache:**T**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(bfloat16), tensor(float16)|
 |Inverse|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(float16)|
 |Irfft|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(float16)|
 |LongformerAttention|*in* input:**T**<br> *in* weight:**T**<br> *in* bias:**T**<br> *in* mask:**T**<br> *in* global_weight:**T**<br> *in* global_bias:**T**<br> *in* global:**G**<br> *out* output:**T**|1+|**T** = tensor(float), tensor(float16)|
@@ -876,7 +877,7 @@ Do not modify directly.*
 |TransposeMatMul|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)|
 |Trilu|*in* X:**T**<br> *in* k:**tensor(int64)**<br> *out* Y:**T**|1+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |UnfoldTensor|*in* input:**T**<br> *out* output:**T**|1+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
-|WhisperBeamSearch|*in* input_ids:**F**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* num_beams:**I**<br> *in* num_return_sequences:**I**<br> *in* length_penalty:**T**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**M**<br> *in* prefix_vocab_mask:**M**<br> *in* attention_mask:**I**<br> *in* decoder_input_ids:**I**<br> *in* logits_processor:**I**<br> *in* cross_qk_layer_head:**I**<br> *in* extra_decoding_ids:**I**<br> *out* sequences:**I**<br> *out* sequences_scores:**T**<br> *out* scores:**T**<br> *out* cross_qk:**V**<br> *out* non_speech_probs:**T**|1+|**T** = tensor(float), tensor(float16)|
+|WhisperBeamSearch|*in* input_ids:**F**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* num_beams:**I**<br> *in* num_return_sequences:**I**<br> *in* length_penalty:**T**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**M**<br> *in* prefix_vocab_mask:**M**<br> *in* attention_mask:**I**<br> *in* decoder_input_ids:**I**<br> *in* logits_processor:**I**<br> *in* cross_qk_layer_head:**I**<br> *in* extra_decoding_ids:**I**<br> *in* temperature:**T**<br> *out* sequences:**I**<br> *out* sequences_scores:**T**<br> *out* scores:**T**<br> *out* cross_qk:**V**<br> *out* non_speech_probs:**T**|1+|**T** = tensor(float), tensor(float16)|
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