diff --git a/cmake/deps.txt b/cmake/deps.txt
index 828593038e113..9b8c716f12236 100644
--- a/cmake/deps.txt
+++ b/cmake/deps.txt
@@ -34,7 +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/v1.0.250325.1.zip;826c8bd47c2258ec61b8b218e031e5b33d27f761
 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
-onnx;https://github.com/onnx/onnx/archive/refs/tags/v1.19.1.zip;c5215b5697dcdfd71799f001b8c4054a6bba6b09
+onnx;https://github.com/onnx/onnx/archive/refs/tags/v1.20.1.zip;30b80c81a1a381188896e86abe460c3c3f3091fd
 # Use the latest commit of 10.9-GA
 onnx_tensorrt;https://github.com/onnx/onnx-tensorrt/archive/d5dce67db7c2e64b07e055571f5ec06f7f254de2.zip;01114d3b67650857281fa50faa2e412130a63b69
 protobuf;https://github.com/protocolbuffers/protobuf/archive/refs/tags/v21.12.zip;7cf2733949036c7d52fda017badcab093fe73bfa
diff --git a/cmake/external/onnx b/cmake/external/onnx
index 54b72a5edd399..d3f6b795aedb4 160000
--- a/cmake/external/onnx
+++ b/cmake/external/onnx
@@ -1 +1 @@
-Subproject commit 54b72a5edd399eb096ee09fecdef03201e9bde89
+Subproject commit d3f6b795aedb48eaecc881bf5e8f5dd6efbe25b3
diff --git a/cmake/onnxruntime_unittests.cmake b/cmake/onnxruntime_unittests.cmake
index 01c7fa3ac1126..28a8fed411500 100644
--- a/cmake/onnxruntime_unittests.cmake
+++ b/cmake/onnxruntime_unittests.cmake
@@ -1128,7 +1128,7 @@ onnxruntime_add_static_library(onnx_test_data_proto ${TEST_SRC_DIR}/proto/tml.pr
 add_dependencies(onnx_test_data_proto onnx_proto ${onnxruntime_EXTERNAL_DEPENDENCIES})
 #onnx_proto target should mark this definition as public, instead of private
 target_compile_definitions(onnx_test_data_proto PRIVATE "-DONNX_API=")
-onnxruntime_add_include_to_target(onnx_test_data_proto onnx_proto)
+onnxruntime_add_include_to_target(onnx_test_data_proto onnx_proto ${PROTOBUF_LIB})
 if (MSVC)
     # Cutlass code has an issue with the following:
     # warning C4100: 'magic': unreferenced formal parameter
diff --git a/cmake/patches/onnx/onnx.patch b/cmake/patches/onnx/onnx.patch
index 047cb527bb4da..76e94a71364bf 100644
--- a/cmake/patches/onnx/onnx.patch
+++ b/cmake/patches/onnx/onnx.patch
@@ -1,8 +1,8 @@
 diff --git a/CMakeLists.txt b/CMakeLists.txt
-index cc3ef140..f70312ba 100644
+index 584c0419a..5d4ffff99 100644
 --- a/CMakeLists.txt
 +++ b/CMakeLists.txt
-@@ -57,6 +57,7 @@ option(ONNX_USE_LITE_PROTO "Use lite protobuf instead of full." OFF)
+@@ -52,6 +52,7 @@ option(ONNX_USE_LITE_PROTO "Use lite protobuf instead of full." OFF)
  option(ONNX_DISABLE_EXCEPTIONS "Disable exception handling." OFF)
  option(ONNX_DISABLE_STATIC_REGISTRATION "Disable static registration for ONNX operator schemas." OFF)
  option(ONNX_USE_UNITY_BUILD "Enable Unity (Jumbo) build for" OFF)
@@ -10,9 +10,9 @@ index cc3ef140..f70312ba 100644
  if(WIN32)
    option(ONNX_USE_MSVC_STATIC_RUNTIME "Build with MSVC static runtime" OFF)
  endif()
-@@ -409,14 +410,28 @@ relative_protobuf_generate_cpp(ONNX_PROTO_SRCS
- 
- add_library(onnx_proto ${ONNX_PROTO_SRCS})
+@@ -397,14 +398,28 @@ relative_protobuf_generate_cpp(ONNX_PROTO_SRCS
+                                onnx/onnx-operators.in.proto
+                                onnx/onnx-data.in.proto)
  
 -file(GLOB_RECURSE __tmp_srcs "${ONNX_ROOT}/onnx/*.h" "${ONNX_ROOT}/onnx/*.cc")
 -file(GLOB_RECURSE onnx_gtests_src "${ONNX_ROOT}/onnx/test/cpp/*.h"
@@ -20,7 +20,7 @@ index cc3ef140..f70312ba 100644
 -    "${ONNX_ROOT}/onnx/backend/test/cpp/*.cc"
 -    "${ONNX_ROOT}/onnx/backend/test/cpp/*.h")
 -list(REMOVE_ITEM __tmp_srcs "${ONNX_ROOT}/onnx/cpp2py_export.cc")
--list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src})
+-list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src} "${ONNX_ROOT}/onnx/test/cmake/main.cc")
 -list(APPEND ONNX_SRCS ${__tmp_srcs})
 +if(ONNX_MINIMAL_BUILD)
 +    message(STATUS "Configuring ONNX minimal build")
@@ -41,37 +41,40 @@ index cc3ef140..f70312ba 100644
 +        "${ONNX_ROOT}/onnx/backend/test/cpp/*.cc"
 +        "${ONNX_ROOT}/onnx/backend/test/cpp/*.h")
 +    list(REMOVE_ITEM __tmp_srcs "${ONNX_ROOT}/onnx/cpp2py_export.cc")
-+    list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src})
++    list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src} "${ONNX_ROOT}/onnx/test/cmake/main.cc")
 +    list(APPEND ONNX_SRCS ${__tmp_srcs})
 +endif()
  
- # Hide all symbols we don't need
- set_target_properties(onnx_proto PROPERTIES CXX_VISIBILITY_PRESET hidden)
-@@ -438,19 +453,6 @@ add_onnx_global_defines(onnx_proto)
- target_include_directories(onnx_proto PUBLIC
-   $<BUILD_INTERFACE:${ONNX_ROOT}>
-   $<BUILD_INTERFACE:${CMAKE_CURRENT_BINARY_DIR}>)
--if(MSVC)
--  # For disabling Protobuf related warnings
--  target_compile_options(onnx_proto PUBLIC
--    /wd4146 # unary minus operator applied to unsigned type,
--            # result still unsigned
--    /wd4244 # 'argument': conversion from 'google::
--            # protobuf::uint64' to 'int', possible
--            # loss of data
--    /wd4267 # Conversion from 'size_t' to 'int',
--            # possible loss of data
--    /wd4141 # 'inline': used more than once
--  )
--endif()
+ set(LINKED_PROTOBUF_TARGET protobuf::libprotobuf)
+ if(ONNX_USE_LITE_PROTO)
+diff --git a/cmake/Utils.cmake b/cmake/Utils.cmake
+index 07f2b9071..388d9f7a3 100644
+--- a/cmake/Utils.cmake
++++ b/cmake/Utils.cmake
+@@ -31,18 +31,7 @@ endfunction()
  
- if(CMAKE_SYSTEM_NAME STREQUAL "AIX")
-   # whole-archive linker option not available on AIX.
+ function(add_onnx_compile_options target)
+   if(MSVC)
+-    # For disabling Protobuf related warnings
+-    set(protobuf_warnings
+-        /wd4146 # unary minus operator applied to unsigned type, result still
+-                # unsigned
+-        /wd4244 # 'argument': conversion from 'google::protobuf::uint64' to
+-                # 'int', possible loss of data
+-        /wd4267 # Conversion from 'size_t' to 'int', possible loss of data
+-        /wd4141 # 'inline': used more than once
+-        /wd4047 # '=': 'uintptr_t' differs in levels of indirection from 'void *'
+-    )
+     add_msvc_runtime_flag(${target})
+-    target_compile_options(${target} PUBLIC ${protobuf_warnings})
+     if(ONNX_WERROR)
+       target_compile_options(${target} PRIVATE "/WX")
+     endif()
 diff --git a/onnx/defs/nn/old.cc b/onnx/defs/nn/old.cc
-index ad6dd0c1..50259f32 100644
+index 887151217..ac2e8c463 100644
 --- a/onnx/defs/nn/old.cc
 +++ b/onnx/defs/nn/old.cc
-@@ -4091,7 +4091,6 @@ ONNX_OPERATOR_SET_SCHEMA(
+@@ -4152,7 +4152,6 @@ ONNX_OPERATOR_SET_SCHEMA(
      GroupNormalization,
      18,
      OpSchema()
@@ -79,16 +82,3 @@ index ad6dd0c1..50259f32 100644
          .SetDoc(GroupNormalization_ver18_doc)
          .Attr("epsilon", "The epsilon value to use to avoid division by zero.", AttributeProto::FLOAT, 1e-5f)
          .Attr(
-diff --git a/onnx/defs/schema.h b/onnx/defs/schema.h
-index 7e9bc27f..4b87c5a5 100644
---- a/onnx/defs/schema.h
-+++ b/onnx/defs/schema.h
-@@ -999,7 +999,7 @@ class OpSchemaRegistry final : public ISchemaRegistry {
-   class OpSchemaRegisterOnce final {
-    public:
-     // Export to cpp custom register macro
--    explicit OpSchemaRegisterOnce(
-+    OpSchemaRegisterOnce(
-         OpSchema op_schema,
-         int opset_version_to_load = 0,
-         bool fail_duplicate_schema = true) {
diff --git a/cmake/vcpkg-ports/onnx/binskim.patch b/cmake/vcpkg-ports/onnx/binskim.patch
index 047cb527bb4da..76e94a71364bf 100644
--- a/cmake/vcpkg-ports/onnx/binskim.patch
+++ b/cmake/vcpkg-ports/onnx/binskim.patch
@@ -1,8 +1,8 @@
 diff --git a/CMakeLists.txt b/CMakeLists.txt
-index cc3ef140..f70312ba 100644
+index 584c0419a..5d4ffff99 100644
 --- a/CMakeLists.txt
 +++ b/CMakeLists.txt
-@@ -57,6 +57,7 @@ option(ONNX_USE_LITE_PROTO "Use lite protobuf instead of full." OFF)
+@@ -52,6 +52,7 @@ option(ONNX_USE_LITE_PROTO "Use lite protobuf instead of full." OFF)
  option(ONNX_DISABLE_EXCEPTIONS "Disable exception handling." OFF)
  option(ONNX_DISABLE_STATIC_REGISTRATION "Disable static registration for ONNX operator schemas." OFF)
  option(ONNX_USE_UNITY_BUILD "Enable Unity (Jumbo) build for" OFF)
@@ -10,9 +10,9 @@ index cc3ef140..f70312ba 100644
  if(WIN32)
    option(ONNX_USE_MSVC_STATIC_RUNTIME "Build with MSVC static runtime" OFF)
  endif()
-@@ -409,14 +410,28 @@ relative_protobuf_generate_cpp(ONNX_PROTO_SRCS
- 
- add_library(onnx_proto ${ONNX_PROTO_SRCS})
+@@ -397,14 +398,28 @@ relative_protobuf_generate_cpp(ONNX_PROTO_SRCS
+                                onnx/onnx-operators.in.proto
+                                onnx/onnx-data.in.proto)
  
 -file(GLOB_RECURSE __tmp_srcs "${ONNX_ROOT}/onnx/*.h" "${ONNX_ROOT}/onnx/*.cc")
 -file(GLOB_RECURSE onnx_gtests_src "${ONNX_ROOT}/onnx/test/cpp/*.h"
@@ -20,7 +20,7 @@ index cc3ef140..f70312ba 100644
 -    "${ONNX_ROOT}/onnx/backend/test/cpp/*.cc"
 -    "${ONNX_ROOT}/onnx/backend/test/cpp/*.h")
 -list(REMOVE_ITEM __tmp_srcs "${ONNX_ROOT}/onnx/cpp2py_export.cc")
--list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src})
+-list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src} "${ONNX_ROOT}/onnx/test/cmake/main.cc")
 -list(APPEND ONNX_SRCS ${__tmp_srcs})
 +if(ONNX_MINIMAL_BUILD)
 +    message(STATUS "Configuring ONNX minimal build")
@@ -41,37 +41,40 @@ index cc3ef140..f70312ba 100644
 +        "${ONNX_ROOT}/onnx/backend/test/cpp/*.cc"
 +        "${ONNX_ROOT}/onnx/backend/test/cpp/*.h")
 +    list(REMOVE_ITEM __tmp_srcs "${ONNX_ROOT}/onnx/cpp2py_export.cc")
-+    list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src})
++    list(REMOVE_ITEM __tmp_srcs ${onnx_gtests_src} "${ONNX_ROOT}/onnx/test/cmake/main.cc")
 +    list(APPEND ONNX_SRCS ${__tmp_srcs})
 +endif()
  
- # Hide all symbols we don't need
- set_target_properties(onnx_proto PROPERTIES CXX_VISIBILITY_PRESET hidden)
-@@ -438,19 +453,6 @@ add_onnx_global_defines(onnx_proto)
- target_include_directories(onnx_proto PUBLIC
-   $<BUILD_INTERFACE:${ONNX_ROOT}>
-   $<BUILD_INTERFACE:${CMAKE_CURRENT_BINARY_DIR}>)
--if(MSVC)
--  # For disabling Protobuf related warnings
--  target_compile_options(onnx_proto PUBLIC
--    /wd4146 # unary minus operator applied to unsigned type,
--            # result still unsigned
--    /wd4244 # 'argument': conversion from 'google::
--            # protobuf::uint64' to 'int', possible
--            # loss of data
--    /wd4267 # Conversion from 'size_t' to 'int',
--            # possible loss of data
--    /wd4141 # 'inline': used more than once
--  )
--endif()
+ set(LINKED_PROTOBUF_TARGET protobuf::libprotobuf)
+ if(ONNX_USE_LITE_PROTO)
+diff --git a/cmake/Utils.cmake b/cmake/Utils.cmake
+index 07f2b9071..388d9f7a3 100644
+--- a/cmake/Utils.cmake
++++ b/cmake/Utils.cmake
+@@ -31,18 +31,7 @@ endfunction()
  
- if(CMAKE_SYSTEM_NAME STREQUAL "AIX")
-   # whole-archive linker option not available on AIX.
+ function(add_onnx_compile_options target)
+   if(MSVC)
+-    # For disabling Protobuf related warnings
+-    set(protobuf_warnings
+-        /wd4146 # unary minus operator applied to unsigned type, result still
+-                # unsigned
+-        /wd4244 # 'argument': conversion from 'google::protobuf::uint64' to
+-                # 'int', possible loss of data
+-        /wd4267 # Conversion from 'size_t' to 'int', possible loss of data
+-        /wd4141 # 'inline': used more than once
+-        /wd4047 # '=': 'uintptr_t' differs in levels of indirection from 'void *'
+-    )
+     add_msvc_runtime_flag(${target})
+-    target_compile_options(${target} PUBLIC ${protobuf_warnings})
+     if(ONNX_WERROR)
+       target_compile_options(${target} PRIVATE "/WX")
+     endif()
 diff --git a/onnx/defs/nn/old.cc b/onnx/defs/nn/old.cc
-index ad6dd0c1..50259f32 100644
+index 887151217..ac2e8c463 100644
 --- a/onnx/defs/nn/old.cc
 +++ b/onnx/defs/nn/old.cc
-@@ -4091,7 +4091,6 @@ ONNX_OPERATOR_SET_SCHEMA(
+@@ -4152,7 +4152,6 @@ ONNX_OPERATOR_SET_SCHEMA(
      GroupNormalization,
      18,
      OpSchema()
@@ -79,16 +82,3 @@ index ad6dd0c1..50259f32 100644
          .SetDoc(GroupNormalization_ver18_doc)
          .Attr("epsilon", "The epsilon value to use to avoid division by zero.", AttributeProto::FLOAT, 1e-5f)
          .Attr(
-diff --git a/onnx/defs/schema.h b/onnx/defs/schema.h
-index 7e9bc27f..4b87c5a5 100644
---- a/onnx/defs/schema.h
-+++ b/onnx/defs/schema.h
-@@ -999,7 +999,7 @@ class OpSchemaRegistry final : public ISchemaRegistry {
-   class OpSchemaRegisterOnce final {
-    public:
-     // Export to cpp custom register macro
--    explicit OpSchemaRegisterOnce(
-+    OpSchemaRegisterOnce(
-         OpSchema op_schema,
-         int opset_version_to_load = 0,
-         bool fail_duplicate_schema = true) {
diff --git a/cmake/vcpkg-ports/onnx/fix-dependency-protobuf.patch b/cmake/vcpkg-ports/onnx/fix-dependency-protobuf.patch
index a1abf66f67dc6..4a438def6cf1b 100644
--- a/cmake/vcpkg-ports/onnx/fix-dependency-protobuf.patch
+++ b/cmake/vcpkg-ports/onnx/fix-dependency-protobuf.patch
@@ -1,8 +1,8 @@
 diff --git a/CMakeLists.txt b/CMakeLists.txt
-index 47995579..1542b11f 100644
+index 4a7df7d71..257d77e61 100644
 --- a/CMakeLists.txt
 +++ b/CMakeLists.txt
-@@ -169,6 +169,7 @@ if(NOT DEFINED CMAKE_POSITION_INDEPENDENT_CODE)
+@@ -159,6 +159,7 @@ if(NOT DEFINED CMAKE_POSITION_INDEPENDENT_CODE)
    set(CMAKE_POSITION_INDEPENDENT_CODE ON)
  endif()
  
@@ -11,14 +11,14 @@ index 47995579..1542b11f 100644
  if(NOT ONNX_BUILD_CUSTOM_PROTOBUF)
    if((ONNX_USE_LITE_PROTO AND TARGET protobuf::libprotobuf-lite) OR ((NOT ONNX_USE_LITE_PROTO) AND TARGET protobuf::libprotobuf))
 diff --git a/cmake/ONNXConfig.cmake.in b/cmake/ONNXConfig.cmake.in
-index a5129bfd..d450b51e 100644
+index aa1ef47d9..d450b51e5 100644
 --- a/cmake/ONNXConfig.cmake.in
 +++ b/cmake/ONNXConfig.cmake.in
 @@ -4,9 +4,8 @@
  # library version information
  set(ONNX_VERSION "@ONNX_VERSION@")
  
--if((NOT @@ONNX_USE_PROTOBUF_SHARED_LIBS@@) AND @@Build_Protobuf@@)
+-if(NOT @ONNX_USE_PROTOBUF_SHARED_LIBS@)
 -  find_package(Protobuf REQUIRED CONFIG)
 -endif()
 +include(CMakeFindDependencyMacro)
diff --git a/cmake/vcpkg-ports/onnx/portfile.cmake b/cmake/vcpkg-ports/onnx/portfile.cmake
index d19535c863a8f..c526529466e97 100644
--- a/cmake/vcpkg-ports/onnx/portfile.cmake
+++ b/cmake/vcpkg-ports/onnx/portfile.cmake
@@ -4,7 +4,7 @@ vcpkg_from_github(
     OUT_SOURCE_PATH SOURCE_PATH
     REPO onnx/onnx
     REF "v${VERSION}"
-    SHA512 cf6ff4c0bb6cc16ce5f4d6267480d35f3c7a5fde94d10e1358928ff6e4ec6d756a7c5d34a500e60bbd8eb1912c8af21aa763719321b330f56a0eb6b9b810ef60
+    SHA512 4bbc4c09e4bb3eb6049d653ce49200564e8c5dcf1154a30f894f24e15f1986d1f2fe2f4ca32fe383c559e2a0b20681f33d649376bf63e4345df6972a2c78eac8
     PATCHES
         fix-cmakelists.patch
         fix-dependency-protobuf.patch
diff --git a/cmake/vcpkg-ports/onnx/vcpkg.json b/cmake/vcpkg-ports/onnx/vcpkg.json
index ad0d1aaf15f51..5800b031aa143 100644
--- a/cmake/vcpkg-ports/onnx/vcpkg.json
+++ b/cmake/vcpkg-ports/onnx/vcpkg.json
@@ -1,6 +1,6 @@
 {
   "name": "onnx",
-  "version-semver": "1.19.1",
+  "version-semver": "1.20.1",
   "port-version": 1,
   "description": "Open standard for machine learning interoperability",
   "homepage": "https://onnx.ai",
diff --git a/docs/How_To_Update_ONNX_Dev_Notes.md b/docs/How_To_Update_ONNX_Dev_Notes.md
index 8c1280431c384..67e7c2ab22a30 100644
--- a/docs/How_To_Update_ONNX_Dev_Notes.md
+++ b/docs/How_To_Update_ONNX_Dev_Notes.md
@@ -34,6 +34,7 @@ git add onnx
 
 1. Modify [cmake/vcpkg-ports/onnx/binskim.patch](/cmake/vcpkg-ports/onnx/binskim.patch) to be the same as [cmake/patches/onnx/onnx.patch](/cmake/patches/onnx/onnx.patch).
 2. The other patches are required/created by vcpkg repository to build ONNX. We just need to re-run diff to makes sure the patches can be applied in the updated ONNX version.
+   a. VCPKG relies these patches to build ONNX.
 3. Update [cmake/vcpkg-ports/onnx/portfile.cmake](/cmake/vcpkg-ports/onnx/portfile.cmake) with the correct commit id and SHA512. (alternatively, build it with the wrong SHA and ORT should tell you the expected one.)
 4. Upload your package: [Follow the instructions](https://microsoft.sharepoint.com/:o:/r/teams/ONNX2/_layouts/15/Doc.aspx?sourcedoc=%7B170774BE-E1C6-4F8B-A3AE-984F211FE410%7D&wd=target(Development.one%7C63D3AB47-51D1-4A62-9965-66882234BD44%2FUpdate%20a%20VCPKG%20package%7CB6AE6A97-94FC-4436-8FC6-08C21AE895DA%2F)&wdpartid=%7BB5CF19CC-40FE-0EC7-32B6-8119B427B32A%7D%7B1%7D&wdsectionfileid=%7B9DD25660-A195-48EA-B9E0-DF8B902AFDD7%7D&ovuser=72f988bf-86f1-41af-91ab-2d7cd011db47%2Ctitaiwang%40microsoft.com&clickparams=eyJBcHBOYW1lIjoiVGVhbXMtRGVza3RvcCIsIkFwcFZlcnNpb24iOiI0OS8yNTA5MTExNjAxNiIsIkhhc0ZlZGVyYXRlZFVzZXIiOmZhbHNlfQ%3D%3D&CID=fb9dcaa1-c0b5-1000-5597-c19e3adf468c&cidOR=SPO)one%7C63d3ab47-51d1-4a62-9965-66882234bd44%2FAdd%20or%20Update%20a%20C%2B%2B%20dependency%7Cb6ae6a97-94fc-4436-8fc6-08c21ae895da%2F%29&wdorigin=NavigationUrl
 
diff --git a/docs/OperatorKernels.md b/docs/OperatorKernels.md
index d7be243323c17..ebed2b1972ba9 100644
--- a/docs/OperatorKernels.md
+++ b/docs/OperatorKernels.md
@@ -60,7 +60,8 @@ Do not modify directly.*
 |BitwiseOr|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |BitwiseXor|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |BlackmanWindow|*in* size:**T1**<br> *out* output:**T2**|17+|**T1** = tensor(int32), tensor(int64)<br/> **T2** = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
-|Cast|*in* input:**T1**<br> *out* output:**T2**|24+|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
+|Cast|*in* input:**T1**<br> *out* output:**T2**|25+|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
+|||24|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||23|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
@@ -80,7 +81,8 @@ Do not modify directly.*
 |||[11, 12]|**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)|
 |||[4, 10]|**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)|
 |ConcatFromSequence|*in* input_sequence:**S**<br> *out* concat_result:**T**|11+|**S** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))|
-|ConstantOfShape|*in* input:**T1**<br> *out* output:**T2**|24+|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|ConstantOfShape|*in* input:**T1**<br> *out* output:**T2**|25+|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||20|**T1** = tensor(int64)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -104,7 +106,8 @@ Do not modify directly.*
 |DepthToSpace|*in* input:**T**<br> *out* output:**T**|13+|**T** = tensor(double), tensor(float), tensor(uint8)|
 |||[11, 12]|**T** = tensor(double), tensor(float), tensor(uint8)|
 |||[1, 10]|**T** = tensor(double), tensor(float)|
-|DequantizeLinear|*in* x:**T**<br> *in* x_scale:**tensor(float)**<br> *in* x_zero_point:**T**<br> *out* y:**tensor(float)**<br><br>or<br><br>*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**<br><br>or<br><br>*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T3**|24+|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
+|DequantizeLinear|*in* x:**T**<br> *in* x_scale:**tensor(float)**<br> *in* x_zero_point:**T**<br> *out* y:**tensor(float)**<br><br>or<br><br>*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**<br><br>or<br><br>*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T3**|25+|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
+|||24|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
 |||23|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
 |||[21, 22]|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
 |||[19, 20]|**T1** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int32), tensor(int8), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
@@ -137,7 +140,8 @@ Do not modify directly.*
 |||[8, 12]|**T** = 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)|
 |EyeLike|*in* input:**T1**<br> *out* output:**T2**|22+|**T1** = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)<br/> **T2** = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)|
 |||[9, 21]|**T1** = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)<br/> **T2** = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)|
-|Flatten|*in* input:**T**<br> *out* output:**T**|24+|**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)|
+|Flatten|*in* input:**T**<br> *out* output:**T**|25+|**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)|
+|||24|**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)|
 |||23|**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)|
 |||[21, 22]|**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)|
 |||[13, 20]|**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)|
@@ -182,7 +186,8 @@ Do not modify directly.*
 |Hardmax|*in* input:**T**<br> *out* output:**T**|13+|**T** = tensor(float)|
 |||[11, 12]|**T** = tensor(float)|
 |||[1, 10]|**T** = tensor(float)|
-|Identity|*in* input:**T**<br> *out* output:**T**<br><br>or<br><br>*in* input:**V**<br> *out* output:**V**|24+|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|Identity|*in* input:**T**<br> *out* output:**T**<br><br>or<br><br>*in* input:**V**<br> *out* output:**V**|25+|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -190,7 +195,8 @@ Do not modify directly.*
 |||[14, 15]|**V** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), 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)|
 |||13|**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)|
 |||[1, 12]|**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)|
-|If|*in* cond:**B**<br> *out* outputs:**V**|24+|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|If|*in* cond:**B**<br> *out* outputs:**V**|25+|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**B** = tensor(bool)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -225,7 +231,8 @@ Do not modify directly.*
 |LogSoftmax|*in* input:**T**<br> *out* output:**T**|13+|**T** = tensor(double), tensor(float)|
 |||[11, 12]|**T** = tensor(double), tensor(float)|
 |||[1, 10]|**T** = tensor(double), tensor(float)|
-|Loop|*in* M:**I**<br> *in* cond:**B**<br> *in* v_initial:**V**<br> *out* v_final_and_scan_outputs:**V**|24+|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|Loop|*in* M:**I**<br> *in* cond:**B**<br> *in* v_initial:**V**<br> *out* v_final_and_scan_outputs:**V**|25+|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**B** = tensor(bool)<br/> **I** = tensor(int64)<br/> **V** = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -289,7 +296,8 @@ Do not modify directly.*
 |PRelu|*in* X:**T**<br> *in* slope:**T**<br> *out* Y:**T**|16+|**T** = tensor(float)|
 |||[9, 15]|**T** = tensor(float)|
 |||[7, 8]|**T** = tensor(float)|
-|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**|24+|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
+|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**|25+|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**T** = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -305,7 +313,8 @@ Do not modify directly.*
 |QLinearConv|*in* x:**T1**<br> *in* x_scale:**tensor(float)**<br> *in* x_zero_point:**T1**<br> *in* w:**T2**<br> *in* w_scale:**tensor(float)**<br> *in* w_zero_point:**T2**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T3**<br> *in* B:**T4**<br> *out* y:**T3**|10+|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(int8), tensor(uint8)<br/> **T4** = tensor(int32)|
 |QLinearMatMul|*in* a:**T1**<br> *in* a_scale:**TS**<br> *in* a_zero_point:**T1**<br> *in* b:**T2**<br> *in* b_scale:**TS**<br> *in* b_zero_point:**T2**<br> *in* y_scale:**TS**<br> *in* y_zero_point:**T3**<br> *out* y:**T3**<br><br>or<br><br>*in* a:**T1**<br> *in* a_scale:**tensor(float)**<br> *in* a_zero_point:**T1**<br> *in* b:**T2**<br> *in* b_scale:**tensor(float)**<br> *in* b_zero_point:**T2**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T3**<br> *out* y:**T3**|21+|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(int8), tensor(uint8)<br/> **TS** = tensor(float)|
 |||[10, 20]|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(int8), tensor(uint8)|
-|QuantizeLinear|*in* x:**T1**<br> *in* y_scale:**T1**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**<br><br>or<br><br>*in* x:**T1**<br> *in* y_scale:**T2**<br> *in* y_zero_point:**T3**<br> *out* y:**T3**<br><br>or<br><br>*in* x:**T1**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**|24+|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)|
+|QuantizeLinear|*in* x:**T1**<br> *in* y_scale:**T1**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**<br><br>or<br><br>*in* x:**T1**<br> *in* y_scale:**T2**<br> *in* y_zero_point:**T3**<br> *out* y:**T3**<br><br>or<br><br>*in* x:**T1**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**|25+|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)|
+|||24|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)|
 |||23|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)|
 |||[21, 22]|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)|
 |||[19, 20]|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int8), tensor(uint8)|
@@ -369,7 +378,8 @@ Do not modify directly.*
 |Relu|*in* X:**T**<br> *out* Y:**T**|14+|**T** = tensor(double), tensor(float), tensor(int32), tensor(int8)|
 |||13|**T** = tensor(double), tensor(float)|
 |||[6, 12]|**T** = tensor(double), tensor(float)|
-|Reshape|*in* data:**T**<br> *in* shape:**tensor(int64)**<br> *out* reshaped:**T**<br><br>or<br><br>*in* data:**T**<br> *out* reshaped:**T**|24+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **shape** = tensor(int64)|
+|Reshape|*in* data:**T**<br> *in* shape:**tensor(int64)**<br> *out* reshaped:**T**<br><br>or<br><br>*in* data:**T**<br> *out* reshaped:**T**|25+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **shape** = tensor(int64)|
+|||24|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **shape** = tensor(int64)|
 |||23|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **shape** = tensor(int64)|
 |||[21, 22]|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **shape** = tensor(int64)|
 |||[19, 20]|**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)<br/> **shape** = tensor(int64)|
@@ -391,7 +401,8 @@ Do not modify directly.*
 |STFT|*in* signal:**T1**<br> *in* frame_step:**T2**<br> *in* window:**T1**<br> *in* frame_length:**T2**<br> *out* output:**T1**|17+|**T1** = tensor(double), tensor(float)<br/> **T2** = tensor(int32), tensor(int64)|
 |Scale|*in* input:**T**<br> *out* output:**T**|1+|**T** = tensor(float)|
 |ScaledTanh|*in* input:**T**<br> *out* output:**T**|1+|**T** = tensor(float)|
-|Scan|*in* initial_state_and_scan_inputs:**V**<br> *out* final_state_and_scan_outputs:**V**<br><br>or<br><br>*in* sequence_lens:**I**<br> *in* initial_state_and_scan_inputs:**V**<br> *out* final_state_and_scan_outputs:**V**|24+|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|Scan|*in* initial_state_and_scan_inputs:**V**<br> *out* final_state_and_scan_outputs:**V**<br><br>or<br><br>*in* sequence_lens:**I**<br> *in* initial_state_and_scan_inputs:**V**<br> *out* final_state_and_scan_outputs:**V**|25+|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|||24|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||23|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[19, 20]|**V** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
@@ -416,7 +427,8 @@ Do not modify directly.*
 |SequenceErase|*in* input_sequence:**S**<br> *in* position:**I**<br> *out* output_sequence:**S**|11+|**I** = tensor(int32), tensor(int64)<br/> **S** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))|
 |SequenceInsert|*in* input_sequence:**S**<br> *in* tensor:**T**<br> *in* position:**I**<br> *out* output_sequence:**S**|11+|**I** = tensor(int32), tensor(int64)<br/> **S** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))|
 |SequenceLength|*in* input_sequence:**S**<br> *out* length:**I**|11+|**I** = tensor(int64)<br/> **S** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))|
-|Shape|*in* data:**T**<br> *out* shape:**T1**|24+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
+|Shape|*in* data:**T**<br> *out* shape:**T1**|25+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
+|||24|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||23|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||[21, 22]|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||[19, 20]|**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)<br/> **T1** = tensor(int64)|
@@ -433,7 +445,8 @@ Do not modify directly.*
 |||[7, 21]|**T** = tensor(double), tensor(float)|
 |Sinh|*in* input:**T**<br> *out* output:**T**|22+|**T** = tensor(float)|
 |||[9, 21]|**T** = tensor(float)|
-|Size|*in* data:**T**<br> *out* size:**T1**|24+|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
+|Size|*in* data:**T**<br> *out* size:**T1**|25+|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
+|||24|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||23|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||[21, 22]|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
 |||[19, 20]|**T** = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(int64)|
@@ -460,7 +473,8 @@ Do not modify directly.*
 |||[11, 23]|**I** = tensor(int32), tensor(int64)<br/> **S** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))<br/> **T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(string)|
 |Sqrt|*in* X:**T**<br> *out* Y:**T**|13+|**T** = tensor(double), tensor(float)|
 |||[6, 12]|**T** = tensor(double), tensor(float)|
-|Squeeze|*in* data:**T**<br> *in* axes:**tensor(int64)**<br> *out* squeezed:**T**<br><br>or<br><br>*in* data:**T**<br> *out* squeezed:**T**|24+|**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)|
+|Squeeze|*in* data:**T**<br> *in* axes:**tensor(int64)**<br> *out* squeezed:**T**<br><br>or<br><br>*in* data:**T**<br> *out* squeezed:**T**|25+|**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)|
+|||24|**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)|
 |||23|**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)|
 |||[21, 22]|**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)|
 |||[13, 20]|**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)|
@@ -489,14 +503,16 @@ Do not modify directly.*
 |||[11, 23]|**I** = tensor(int64)<br/> **T** = tensor(double), tensor(float), tensor(int32), tensor(int64)|
 |||10|**I** = tensor(int64)<br/> **T** = tensor(double), tensor(float)|
 |||[1, 9]|**I** = tensor(int64)<br/> **T** = tensor(double), tensor(float)|
-|Transpose|*in* data:**T**<br> *out* transposed:**T**|24+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
+|Transpose|*in* data:**T**<br> *out* transposed:**T**|25+|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
+|||24|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||23|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||[21, 22]|**T** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int4), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint4), tensor(uint64), tensor(uint8)|
 |||[13, 20]|**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)|
 |||[1, 12]|**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)|
 |Trilu|*in* input:**T**<br> *in* k:**tensor(int64)**<br> *out* output:**T**|14+|**T** = tensor(bool), tensor(double), tensor(float), tensor(int64)|
 |Unique|*in* X:**T**<br> *out* Y:**T**<br> *out* indices:**tensor(int64)**<br> *out* inverse_indices:**tensor(int64)**<br> *out* counts:**tensor(int64)**|11+|**T** = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(string)|
-|Unsqueeze|*in* data:**T**<br> *in* axes:**tensor(int64)**<br> *out* expanded:**T**<br><br>or<br><br>*in* data:**T**<br> *out* expanded:**T**|24+|**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)|
+|Unsqueeze|*in* data:**T**<br> *in* axes:**tensor(int64)**<br> *out* expanded:**T**<br><br>or<br><br>*in* data:**T**<br> *out* expanded:**T**|25+|**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)|
+|||24|**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)|
 |||23|**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)|
 |||[21, 22]|**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)|
 |||[13, 20]|**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)|
diff --git a/js/web/docs/webgl-operators.md b/js/web/docs/webgl-operators.md
index 799d275dadb7c..8e55d8c4e2564 100644
--- a/js/web/docs/webgl-operators.md
+++ b/js/web/docs/webgl-operators.md
@@ -30,7 +30,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [BitwiseOr](https://github.com/onnx/onnx/blob/main/docs/Operators.md#BitwiseOr) |  |
 | [BitwiseXor](https://github.com/onnx/onnx/blob/main/docs/Operators.md#BitwiseXor) |  |
 | [BlackmanWindow](https://github.com/onnx/onnx/blob/main/docs/Operators.md#BlackmanWindow) |  |
-| [Cast](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Cast) | [6-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-6), [9-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-9), [13-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-13), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-24) |
+| [Cast](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Cast) | [6-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-6), [9-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-9), [13-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-13), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Cast-25) |
 | [CastLike](https://github.com/onnx/onnx/blob/main/docs/Operators.md#CastLike) |  |
 | [Ceil](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Ceil) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Ceil-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Ceil-13) |
 | [Celu](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Celu) |  |
@@ -63,7 +63,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [Exp](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Exp) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Exp-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Exp-13) |
 | [Expand](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Expand) |  |
 | [EyeLike](https://github.com/onnx/onnx/blob/main/docs/Operators.md#EyeLike) |  |
-| [Flatten](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Flatten) | [1-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-1), [9-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-9), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-24) |
+| [Flatten](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Flatten) | [1-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-1), [9-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-9), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-25) |
 | [Floor](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Floor) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Floor-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Floor-13) |
 | [GRU](https://github.com/onnx/onnx/blob/main/docs/Operators.md#GRU) |  |
 | [Gather](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Gather) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Gather-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Gather-11), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Gather-13) |
@@ -83,7 +83,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [HardSigmoid](https://github.com/onnx/onnx/blob/main/docs/Operators.md#HardSigmoid) |  |
 | [HardSwish](https://github.com/onnx/onnx/blob/main/docs/Operators.md#HardSwish) |  |
 | [Hardmax](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Hardmax) |  |
-| [Identity](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Identity) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-1), [13](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-13), [14-15](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-14), [16-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-16), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-24) |
+| [Identity](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Identity) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-1), [13](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-13), [14-15](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-14), [16-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-16), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Identity-25) |
 | [If](https://github.com/onnx/onnx/blob/main/docs/Operators.md#If) |  |
 | [ImageDecoder](https://github.com/onnx/onnx/blob/main/docs/Operators.md#ImageDecoder) |  |
 | [InstanceNormalization](https://github.com/onnx/onnx/blob/main/docs/Operators.md#InstanceNormalization) | [6-21](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#InstanceNormalization-6), [22+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#InstanceNormalization-22) |
@@ -125,7 +125,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [OptionalHasElement](https://github.com/onnx/onnx/blob/main/docs/Operators.md#OptionalHasElement) |  |
 | [Or](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Or) | [7+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Or-7) |
 | [PRelu](https://github.com/onnx/onnx/blob/main/docs/Operators.md#PRelu) | [7-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#PRelu-7), [9-15](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#PRelu-9), [16+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#PRelu-16) |
-| [Pad](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Pad) | [2-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-2), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-11), [13-17](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-13), [18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-18), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-24) |
+| [Pad](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Pad) | [2-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-2), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-11), [13-17](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-13), [18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-18), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pad-25) |
 | [Pow](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Pow) | [7-11](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pow-7), [12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pow-12), [13-14](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pow-13), [15+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pow-15) |
 | [QLinearConv](https://github.com/onnx/onnx/blob/main/docs/Operators.md#QLinearConv) |  |
 | [QLinearMatMul](https://github.com/onnx/onnx/blob/main/docs/Operators.md#QLinearMatMul) |  |
@@ -150,7 +150,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [ReduceSumSquare](https://github.com/onnx/onnx/blob/main/docs/Operators.md#ReduceSumSquare) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#ReduceSumSquare-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#ReduceSumSquare-11), [13-17](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#ReduceSumSquare-13), [18+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#ReduceSumSquare-18) |
 | [RegexFullMatch](https://github.com/onnx/onnx/blob/main/docs/Operators.md#RegexFullMatch) |  |
 | [Relu](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Relu) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Relu-6), [13](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Relu-13), [14+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Relu-14) |
-| [Reshape](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Reshape) | [5-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-5), [13](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-13), [14-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-14), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-24) |
+| [Reshape](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Reshape) | [5-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-5), [13](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-13), [14-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-14), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Reshape-25) |
 | [Resize](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Resize) | [10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Resize-10), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Resize-11), [13-17](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Resize-13), [18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Resize-18), [19+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Resize-19) |
 | [ReverseSequence](https://github.com/onnx/onnx/blob/main/docs/Operators.md#ReverseSequence) |  |
 | [RoiAlign](https://github.com/onnx/onnx/blob/main/docs/Operators.md#RoiAlign) |  |
@@ -169,7 +169,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [SequenceInsert](https://github.com/onnx/onnx/blob/main/docs/Operators.md#SequenceInsert) |  |
 | [SequenceLength](https://github.com/onnx/onnx/blob/main/docs/Operators.md#SequenceLength) |  |
 | [SequenceMap](https://github.com/onnx/onnx/blob/main/docs/Operators.md#SequenceMap) |  |
-| [Shape](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Shape) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-1), [13-14](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-13), [15-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-15), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-24) |
+| [Shape](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Shape) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-1), [13-14](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-13), [15-18](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-15), [19-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-19), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Shape-25) |
 | [Shrink](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Shrink) |  |
 | [Sigmoid](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Sigmoid) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sigmoid-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sigmoid-13) |
 | [Sign](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Sign) |  |
@@ -185,7 +185,7 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [Split](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Split) | [2-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Split-2), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Split-11) |
 | [SplitToSequence](https://github.com/onnx/onnx/blob/main/docs/Operators.md#SplitToSequence) |  |
 | [Sqrt](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Sqrt) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sqrt-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sqrt-13) |
-| [Squeeze](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Squeeze) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-24) |
+| [Squeeze](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Squeeze) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Squeeze-25) |
 | [StringConcat](https://github.com/onnx/onnx/blob/main/docs/Operators.md#StringConcat) |  |
 | [StringNormalizer](https://github.com/onnx/onnx/blob/main/docs/Operators.md#StringNormalizer) |  |
 | [StringSplit](https://github.com/onnx/onnx/blob/main/docs/Operators.md#StringSplit) |  |
@@ -199,10 +199,10 @@ See [Compatibility](../README.md#Compatibility) for a list of the supported plat
 | [ThresholdedRelu](https://github.com/onnx/onnx/blob/main/docs/Operators.md#ThresholdedRelu) |  |
 | [Tile](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Tile) | [6-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Tile-6), [13+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Tile-13) |
 | [TopK](https://github.com/onnx/onnx/blob/main/docs/Operators.md#TopK) |  |
-| [Transpose](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Transpose) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-1), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-24) |
+| [Transpose](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Transpose) | [1-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-1), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Transpose-25) |
 | [Trilu](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Trilu) |  |
 | [Unique](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Unique) |  |
-| [Unsqueeze](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Unsqueeze) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-23), [24+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-24) |
+| [Unsqueeze](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Unsqueeze) | [1-10](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-1), [11-12](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-11), [13-20](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-13), [21-22](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-21), [23](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-23), [24](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-24), [25+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Unsqueeze-25) |
 | [Upsample](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Upsample) | [7-8](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Upsample-7), [9](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Upsample-9) |
 | [Where](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Where) |  |
 | [Xor](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Xor) | [7+](https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Xor-7) |
diff --git a/onnxruntime/core/framework/kernel_type_str_resolver_utils.cc b/onnxruntime/core/framework/kernel_type_str_resolver_utils.cc
index 0a6d53f6af1f3..65ad60f478d78 100644
--- a/onnxruntime/core/framework/kernel_type_str_resolver_utils.cc
+++ b/onnxruntime/core/framework/kernel_type_str_resolver_utils.cc
@@ -53,326 +53,368 @@ Status AddLayoutTransformationRequiredOpsToKernelTypeStrResolver(KernelTypeStrRe
   // clang-format off
   constexpr uint8_t kLayoutTransformationRequiredOpsKernelTypeStrResolverBytes[] = {
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+      0xf0, 0xfc, 0xff, 0xff, 0xf0, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x44, 0xfd, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00,
+      0xd8, 0xfc, 0xff, 0xff, 0x14, 0xfd, 0xff, 0xff, 0xa8, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0xfd, 0xff, 0xff,
+      0x00, 0x00, 0x00, 0x01, 0x70, 0xfd, 0xff, 0xff, 0x02, 0x00, 0x00, 0x00, 0x3c, 0xfd, 0xff, 0xff,
+      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00,
+      0x0c, 0x00, 0x00, 0x00, 0x3a, 0x54, 0x72, 0x61, 0x6e, 0x73, 0x70, 0x6f, 0x73, 0x65, 0x3a, 0x31,
+      0x00, 0x00, 0x00, 0x00, 0x64, 0xfd, 0xff, 0xff, 0xac, 0x02, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x52, 0xfd, 0xff, 0xff,
+      0x00, 0x00, 0x00, 0x01, 0x4c, 0xfd, 0xff, 0xff, 0x88, 0xfd, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00,
+      0x0a, 0x00, 0x00, 0x00, 0x3a, 0x47, 0x61, 0x74, 0x68, 0x65, 0x72, 0x3a, 0x31, 0x31, 0x00, 0x00,
+      0xb0, 0xfd, 0xff, 0xff, 0x60, 0x02, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x9e, 0xfd, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01,
+      0x98, 0xfd, 0xff, 0xff, 0xd4, 0xfd, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x54, 0x69, 0x6e, 0x64, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x30, 0xfe, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0xfc, 0xfd, 0xff, 0xff,
+      0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00,
+      0x20, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x3a, 0x44, 0x65, 0x71, 0x75, 0x61, 0x6e, 0x74,
+      0x69, 0x7a, 0x65, 0x4c, 0x69, 0x6e, 0x65, 0x61, 0x72, 0x3a, 0x32, 0x31, 0x00, 0x00, 0x00, 0x00,
+      0x30, 0xfe, 0xff, 0xff, 0x8c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x1e, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01,
+      0x8c, 0xfe, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0x58, 0xfe, 0xff, 0xff, 0x88, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0xac, 0xfe, 0xff, 0xff, 0x02, 0x00, 0x00, 0x00, 0x40, 0xfe, 0xff, 0xff, 0x7c, 0xfe, 0xff, 0xff,
+      0x18, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00,
+      0x24, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x3a, 0x44, 0x65, 0x71,
+      0x75, 0x61, 0x6e, 0x74, 0x69, 0x7a, 0x65, 0x4c, 0x69, 0x6e, 0x65, 0x61, 0x72, 0x3a, 0x32, 0x34,
+      0x00, 0x00, 0x00, 0x00, 0xb4, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00,
+      0x02, 0x00, 0x00, 0x00, 0x54, 0x32, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0x0c, 0xff, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0xd8, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
+      0x0c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x54, 0x31, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xff, 0xff, 0xff, 0x02, 0x00, 0x00, 0x00,
+      0xc8, 0xfe, 0xff, 0xff, 0x04, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00,
+      0x02, 0x00, 0x00, 0x00, 0x54, 0x33, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0xf6, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0x28, 0xff, 0xff, 0xff, 0x18, 0x00, 0x00, 0x00,
       0x04, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
       0x48, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x3a, 0x44, 0x65, 0x71, 0x75, 0x61, 0x6e, 0x74,
-      0x69, 0x7a, 0x65, 0x4c, 0x69, 0x6e, 0x65, 0x61, 0x72, 0x3a, 0x31, 0x33, 0x00, 0x00, 0x00, 0x00,
-      0x98, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00,
+      0x69, 0x7a, 0x65, 0x4c, 0x69, 0x6e, 0x65, 0x61, 0x72, 0x3a, 0x31, 0x30, 0x00, 0x00, 0x00, 0x00,
+      0x60, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00,
       0x78, 0x5f, 0x73, 0x63, 0x61, 0x6c, 0x65, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
-      0xc8, 0xfe, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0xc0, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
+      0xbc, 0xff, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0x88, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
       0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x79, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-      0x04, 0x00, 0x00, 0x00, 0xb2, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0xe4, 0xfe, 0xff, 0xff,
-      0x2c, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
-      0x04, 0x00, 0x00, 0x00, 0x0c, 0xff, 0xff, 0xff, 0x02, 0x00, 0x00, 0x00, 0xcc, 0xfe, 0xff, 0xff,
-      0x08, 0xff, 0xff, 0xff, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-      0x18, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x3a, 0x49, 0x64, 0x65, 0x6e, 0x74, 0x69, 0x74,
-      0x79, 0x3a, 0x32, 0x31, 0x00, 0x00, 0x00, 0x00, 0x30, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
-      0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x56, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
-      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x26, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01,
-      0x20, 0xff, 0xff, 0xff, 0x5c, 0xff, 0xff, 0xff, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
-      0x01, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x3a, 0x54, 0x72, 0x61,
-      0x6e, 0x73, 0x70, 0x6f, 0x73, 0x65, 0x3a, 0x32, 0x34, 0x00, 0x00, 0x00, 0x84, 0xff, 0xff, 0xff,
-      0x8c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
-      0x04, 0x00, 0x00, 0x00, 0x72, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0x6c, 0xff, 0xff, 0xff,
-      0xa8, 0xff, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
-      0x50, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x3a, 0x53, 0x71, 0x75,
-      0x65, 0x65, 0x7a, 0x65, 0x3a, 0x32, 0x33, 0x00, 0xd0, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
-      0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x61, 0x78, 0x65, 0x73, 0x00, 0x00, 0x00, 0x00,
-      0x01, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00,
-      0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x04, 0x00, 0x08, 0x00,
-      0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-      0x54, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00,
-      0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01,
-      0x04, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x7a, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0xac, 0xff, 0xff, 0xff,
+      0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00,
+      0x0c, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00,
+      0x02, 0x00, 0x00, 0x00, 0x9c, 0xff, 0xff, 0xff, 0xd8, 0xff, 0xff, 0xff, 0x10, 0x00, 0x00, 0x00,
+      0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00,
+      0x3a, 0x55, 0x6e, 0x73, 0x71, 0x75, 0x65, 0x65, 0x7a, 0x65, 0x3a, 0x31, 0x31, 0x00, 0x00, 0x00,
+      0x08, 0x00, 0x0c, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
+      0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x54, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+      0x1c, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x07, 0x00,
+      0x06, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x04, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00,
   };
   // clang-format on
 
diff --git a/onnxruntime/core/graph/contrib_ops/bert_defs.cc b/onnxruntime/core/graph/contrib_ops/bert_defs.cc
index de0061417531a..deaa77a204a7f 100644
--- a/onnxruntime/core/graph/contrib_ops/bert_defs.cc
+++ b/onnxruntime/core/graph/contrib_ops/bert_defs.cc
@@ -1795,6 +1795,7 @@ ONNX_MS_OPERATOR_SET_SCHEMA(
         .Output(0, "Y", "output tensor", "T")
         .TypeConstraint("T", {"tensor(float)", "tensor(double)", "tensor(float16)", "tensor(bfloat16)"}, "Constrain input and output types to float or half tensors.")
         .TypeAndShapeInferenceFunction(ONNX_NAMESPACE::propagateShapeAndTypeFromFirstInput)
+        .SetNodeDeterminism(OpSchema::NodeDeterminism::Deterministic)
         .SetContextDependentFunctionBodyBuilder([](const FunctionBodyBuildContext& ctx, const OpSchema& schema, FunctionProto& functionProto) {
           // fastgelu(x) =
           auto* tp = ctx.getInputType(0);
diff --git a/onnxruntime/core/graph/contrib_ops/contrib_defs.cc b/onnxruntime/core/graph/contrib_ops/contrib_defs.cc
index dfee139743d89..cb562806faecf 100644
--- a/onnxruntime/core/graph/contrib_ops/contrib_defs.cc
+++ b/onnxruntime/core/graph/contrib_ops/contrib_defs.cc
@@ -559,6 +559,7 @@ ONNX_MS_OPERATOR_SET_SCHEMA(Gelu, 1,
                                     {"tensor(float16)", "tensor(float)", "tensor(double)", "tensor(bfloat16)"},
                                     "Constrain input and output types to float tensors.")
                                 .TypeAndShapeInferenceFunction(ONNX_NAMESPACE::propagateShapeAndTypeFromFirstInput)
+                                .SetNodeDeterminism(OpSchema::NodeDeterminism::Deterministic)
                                 .SetContextDependentFunctionBodyBuilder([](const FunctionBodyBuildContext& ctx, const OpSchema& schema, FunctionProto& functionProto) {
                                   // gelu(x) = x * Phi(x) = x * 1/2(1+erf(x/sqrt(2)))
                                   auto* tp = ctx.getInputType(0);
@@ -614,6 +615,7 @@ ONNX_MS_OPERATOR_SET_SCHEMA(
         .TypeConstraint("T", {"tensor(float16)", "tensor(float)", "tensor(double)", "tensor(bfloat16)"},
                         "Constrain input and output types to float tensors.")
         .TypeAndShapeInferenceFunction(ONNX_NAMESPACE::propagateShapeAndTypeFromFirstInput)
+        .SetNodeDeterminism(OpSchema::NodeDeterminism::Deterministic)
         .SetContextDependentFunctionBodyBuilder([](const FunctionBodyBuildContext& ctx, const OpSchema& schema,
                                                    FunctionProto& functionProto) {
           auto* tp = ctx.getInputType(0);
@@ -2997,6 +2999,7 @@ void RegisterContribSchemas() {
             saved_inv_std_dev_shape->mutable_dim(static_cast<int>(d))->set_dim_value(1);
         }
       })
+      .SetNodeDeterminism(OpSchema::NodeDeterminism::Deterministic)
       .SetContextDependentFunctionBodyBuilder(
           [](const FunctionBodyBuildContext& ctx, const OpSchema& schema, FunctionProto& functionProto) {
             // LayerNormalization <axis, epsilon, stash_type> (X, Scale, B) => (Y, Mean?, InvStdDev?)
diff --git a/onnxruntime/core/optimizer/layout_transformation/layout_transformation_potentially_added_ops.h b/onnxruntime/core/optimizer/layout_transformation/layout_transformation_potentially_added_ops.h
index d3ce7bf1a01b2..81eb9f59eeada 100644
--- a/onnxruntime/core/optimizer/layout_transformation/layout_transformation_potentially_added_ops.h
+++ b/onnxruntime/core/optimizer/layout_transformation/layout_transformation_potentially_added_ops.h
@@ -26,6 +26,7 @@ inline constexpr std::array kLayoutTransformationPotentiallyAddedOps = {
     OpIdentifierWithStringViews{kOnnxDomain, "DequantizeLinear", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "DequantizeLinear", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "DequantizeLinear", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "DequantizeLinear", 25},
     OpIdentifierWithStringViews{kOnnxDomain, "Gather", 1},
     OpIdentifierWithStringViews{kOnnxDomain, "Gather", 11},
     OpIdentifierWithStringViews{kOnnxDomain, "Gather", 13},
@@ -37,29 +38,34 @@ inline constexpr std::array kLayoutTransformationPotentiallyAddedOps = {
     OpIdentifierWithStringViews{kOnnxDomain, "Identity", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "Identity", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "Identity", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "Identity", 25},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 10},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 13},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 19},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "QuantizeLinear", 25},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 1},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 11},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 13},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "Squeeze", 25},
     OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 1},
     OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 13},
     OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "Transpose", 25},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 1},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 11},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 13},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 21},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 23},
     OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 24},
+    OpIdentifierWithStringViews{kOnnxDomain, "Unsqueeze", 25},
 
 #if !defined(DISABLE_CONTRIB_OPS)
     // kMSDomain ops
diff --git a/onnxruntime/core/optimizer/qdq_transformer/qdq_util.cc b/onnxruntime/core/optimizer/qdq_transformer/qdq_util.cc
index 5a328346b0c6d..2a07d79eca818 100644
--- a/onnxruntime/core/optimizer/qdq_transformer/qdq_util.cc
+++ b/onnxruntime/core/optimizer/qdq_transformer/qdq_util.cc
@@ -207,12 +207,12 @@ bool IsQOrDQScalePositiveConstantScalar(
 #if !defined(ORT_MINIMAL_BUILD) || defined(ORT_EXTENDED_MINIMAL_BUILD)
 
 bool MatchQNode(const Node& node) {
-  return graph_utils::IsSupportedOptypeVersionAndDomain(node, QOpName, {10, 13, 19, 21, 23, 24}) ||
+  return graph_utils::IsSupportedOptypeVersionAndDomain(node, QOpName, {10, 13, 19, 21, 23, 24, 25}) ||
          graph_utils::IsSupportedOptypeVersionAndDomain(node, QOpName, {1}, kMSDomain);
 }
 
 bool MatchDQNode(const Node& node) {
-  return graph_utils::IsSupportedOptypeVersionAndDomain(node, DQOpName, {10, 13, 19, 21, 23, 24}) ||
+  return graph_utils::IsSupportedOptypeVersionAndDomain(node, DQOpName, {10, 13, 19, 21, 23, 24, 25}) ||
          graph_utils::IsSupportedOptypeVersionAndDomain(node, DQOpName, {1}, kMSDomain);
 }
 
diff --git a/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h b/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h
index f815dadef9859..6ff4da05fbf57 100644
--- a/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h
+++ b/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h
@@ -466,7 +466,7 @@ class GraphRef {
 }  // namespace api
 
 constexpr int64_t kMinSupportedOpset = 7;
-constexpr int64_t kMaxSupportedOpset = 24;
+constexpr int64_t kMaxSupportedOpset = 25;
 
 // enum of results that a CostCheckFn can return.
 enum class CostCheckResult {
diff --git a/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h b/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h
index 06ff502ff3d00..0714ad08fb5fc 100644
--- a/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h
+++ b/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h
@@ -46,7 +46,7 @@ class BaseOpBuilder : public IOpBuilder {
                                       const logging::Logger& logger) const;
 
   virtual int GetMinSupportedOpSet(const Node& /*node*/) const { return 1; }
-  virtual int GetMaxSupportedOpSet(const Node& /*node*/) const { return 24; }
+  virtual int GetMaxSupportedOpSet(const Node& /*node*/) const { return 25; }
 
   bool HasSupportedOpSet(const Node& node, const logging::Logger& logger) const;
   bool HasSupportedInputs(const Node& node, const OpBuilderInputParams& input_params,
diff --git a/onnxruntime/core/providers/cpu/controlflow/if.cc b/onnxruntime/core/providers/cpu/controlflow/if.cc
index c0774fe5f2039..d614b4258379d 100644
--- a/onnxruntime/core/providers/cpu/controlflow/if.cc
+++ b/onnxruntime/core/providers/cpu/controlflow/if.cc
@@ -135,10 +135,19 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()),
     If);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     If,
     24,
+    24,
+    KernelDefBuilder()
+        .TypeConstraint("B", DataTypeImpl::GetTensorType<bool>())
+        .TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()),
+    If);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    If,
+    25,
     KernelDefBuilder()
         .TypeConstraint("B", DataTypeImpl::GetTensorType<bool>())
         .TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()),
diff --git a/onnxruntime/core/providers/cpu/controlflow/loop.cc b/onnxruntime/core/providers/cpu/controlflow/loop.cc
index 019338457aa2f..1ea08e40bd292 100644
--- a/onnxruntime/core/providers/cpu/controlflow/loop.cc
+++ b/onnxruntime/core/providers/cpu/controlflow/loop.cc
@@ -164,10 +164,20 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()),
     Loop);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Loop,
     24,
+    24,
+    KernelDefBuilder()
+        .TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
+        .TypeConstraint("B", DataTypeImpl::GetTensorType<bool>())
+        .TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()),
+    Loop);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Loop,
+    25,
     KernelDefBuilder()
         .TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
         .TypeConstraint("B", DataTypeImpl::GetTensorType<bool>())
diff --git a/onnxruntime/core/providers/cpu/controlflow/scan_9.cc b/onnxruntime/core/providers/cpu/controlflow/scan_9.cc
index 5207f2096a332..2fdd7fc564fe4 100644
--- a/onnxruntime/core/providers/cpu/controlflow/scan_9.cc
+++ b/onnxruntime/core/providers/cpu/controlflow/scan_9.cc
@@ -554,9 +554,18 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(Scan,
                                        .TypeConstraint("V", DataTypeImpl::AllTensorTypesIRv9()),
                                    Scan<9>);
 
-// Opset 24
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(Scan,
+                                   24,
+                                   24,
+                                   KernelDefBuilder()
+                                       // 'I' is in the ONNX spec but is not actually used for any inputs or outputs
+                                       // .TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
+                                       .TypeConstraint("V", DataTypeImpl::AllTensorTypesIRv9()),
+                                   Scan<9>);
+
+// Opset 25
 ONNX_CPU_OPERATOR_KERNEL(Scan,
-                         24,
+                         25,
                          KernelDefBuilder()
                              // 'I' is in the ONNX spec but is not actually used for any inputs or outputs
                              // .TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
diff --git a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
index faadb48bb3ff0..db96089f7d053 100644
--- a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
+++ b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
@@ -1384,51 +1384,92 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain,
 // Opset 24
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, float, Attention);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, MLFloat16, Attention);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Cast);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, ConstantOfShape);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int32_t, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint8_t, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int8_t, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint16_t, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int16_t, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Int4x2, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, UInt4x2, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Cast);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, ConstantOfShape);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int32_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint8_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int8_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint16_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int16_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Int4x2, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, UInt4x2, DequantizeLinear);
 #if !defined(DISABLE_FLOAT8_TYPES)
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FN, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FNUZ, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2, DequantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2FNUZ, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FN, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FNUZ, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2FNUZ, DequantizeLinear);
 #endif
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint8_t, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int8_t, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint16_t, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int16_t, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Int4x2, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, UInt4x2, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint8_t, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int8_t, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint16_t, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int16_t, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Int4x2, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, UInt4x2, QuantizeLinear);
 #if !defined(DISABLE_FLOAT8_TYPES)
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FN, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FNUZ, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2, QuantizeLinear);
-class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2FNUZ, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FN, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FNUZ, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2, QuantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2FNUZ, QuantizeLinear);
 #endif
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Flatten);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Identity);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Pad);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, If);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Loop);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Reshape);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Shape);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Squeeze);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Transpose);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Unsqueeze);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Scan);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Size);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Flatten);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Identity);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Pad);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, If);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Loop);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Reshape);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Shape);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Squeeze);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Transpose);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Unsqueeze);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Scan);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Size);
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, SplitToSequence);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, float, TopK);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, double, TopK);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int64_t, TopK);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int32_t, TopK);
 
+// Opset 25
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Cast);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, ConstantOfShape);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int32_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint8_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int8_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint16_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int16_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Int4x2, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, UInt4x2, DequantizeLinear);
+#if !defined(DISABLE_FLOAT8_TYPES)
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FN, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FNUZ, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2FNUZ, DequantizeLinear);
+#endif
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint8_t, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int8_t, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint16_t, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int16_t, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Int4x2, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, UInt4x2, QuantizeLinear);
+#if !defined(DISABLE_FLOAT8_TYPES)
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FN, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FNUZ, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2, QuantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2FNUZ, QuantizeLinear);
+#endif
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Flatten);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Identity);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Pad);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, If);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Loop);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Reshape);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Shape);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Squeeze);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Transpose);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Unsqueeze);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Scan);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Size);
+
 // !!PLEASE READ BELOW!! Following that, add new entries above this comment
 
 /*  *** IMPORTANT! ***
@@ -3433,71 +3474,133 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
       // opset 24
       BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, float, Attention)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, MLFloat16, Attention)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Cast)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, ConstantOfShape)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint8_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Cast)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, ConstantOfShape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint8_t,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int8_t,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint16_t,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int16_t,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int32_t,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Int4x2,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, UInt4x2,
+                                                                            DequantizeLinear)>,
+#if !defined(DISABLE_FLOAT8_TYPES)
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FN,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FNUZ,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2,
+                                                                            DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2FNUZ,
+                                                                            DequantizeLinear)>,
+#endif
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint8_t,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int8_t,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, uint16_t,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, int16_t,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Int4x2,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, UInt4x2,
+                                                                            QuantizeLinear)>,
+#if !defined(DISABLE_FLOAT8_TYPES)
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FN,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E4M3FNUZ,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2,
+                                                                            QuantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Float8E5M2FNUZ,
+                                                                            QuantizeLinear)>,
+#endif
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Flatten)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Identity)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, If)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Loop)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Pad)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Reshape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Scan)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Shape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Size)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Squeeze)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Transpose)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, 24, Unsqueeze)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, float, TopK)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, double, TopK)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int64_t, TopK)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int32_t, TopK)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, SplitToSequence)>,
+
+      // opset 25
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Cast)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, ConstantOfShape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint8_t,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int8_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int8_t,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint16_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint16_t,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int16_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int16_t,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int32_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int32_t,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Int4x2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Int4x2,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, UInt4x2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, UInt4x2,
                                                                   DequantizeLinear)>,
 #if !defined(DISABLE_FLOAT8_TYPES)
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FN,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FN,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FNUZ,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FNUZ,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2,
                                                                   DequantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2FNUZ,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2FNUZ,
                                                                   DequantizeLinear)>,
 #endif
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint8_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint8_t,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int8_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int8_t,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, uint16_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, uint16_t,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int16_t,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, int16_t,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Int4x2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Int4x2,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, UInt4x2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, UInt4x2,
                                                                   QuantizeLinear)>,
 #if !defined(DISABLE_FLOAT8_TYPES)
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FN,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FN,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E4M3FNUZ,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E4M3FNUZ,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2,
                                                                   QuantizeLinear)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Float8E5M2FNUZ,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Float8E5M2FNUZ,
                                                                   QuantizeLinear)>,
 #endif
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Flatten)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Identity)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, If)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Loop)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Pad)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Reshape)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Scan)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Shape)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Size)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Squeeze)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Transpose)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, Unsqueeze)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, SplitToSequence)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, float, TopK)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, double, TopK)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int64_t, TopK)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 24, int32_t, TopK)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Flatten)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Identity)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, If)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Loop)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Pad)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Reshape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Scan)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Shape)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Size)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Squeeze)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Transpose)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 25, Unsqueeze)>,
   };
   for (auto& function_table_entry : function_table) {
     KernelCreateInfo info = function_table_entry();
diff --git a/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc b/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc
index c2a4bcef6aa83..b5a1f91e0f570 100644
--- a/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc
+++ b/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc
@@ -27,6 +27,10 @@ ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPE_LIST(
     kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 24, Output, 0,
     ConstantOfShapeDefaultOutputTypesOpset23);
 
+ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPE_LIST(
+    kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 25, Output, 0,
+    ConstantOfShapeDefaultOutputTypesOpset23);
+
 // pytorch converter uses ConstantOfShape with int64 to create Pad input
 // https://github.com/pytorch/pytorch/blob/044b519a80459f6787f6723c1c091a18b153d184/torch/onnx/symbolic_opset11.py#L449
 ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES_ALL_OPSETS(
@@ -58,6 +62,11 @@ using EnabledOutputTypesOpset23 =
 using EnabledOutputTypesOpset24 =
     ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST(
         kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 24, Output, 0);
+
+using EnabledOutputTypesOpset25 =
+    ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST(
+        kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 25, Output, 0);
+
 class ConstantOfShape final : public ConstantOfShapeBase<EnabledOutputTypes>, public OpKernel {
  public:
   explicit ConstantOfShape(const OpKernelInfo& info) : ConstantOfShapeBase(info), OpKernel(info) {}
@@ -142,12 +151,22 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
                         BuildKernelDefConstraintsFromTypeList<EnabledOutputTypesOpset23>()),
     ConstantOfShape);
 
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     ConstantOfShape,
     24,
+    24,
     KernelDefBuilder()
         .TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>())
         .TypeConstraint("T2",
                         BuildKernelDefConstraintsFromTypeList<EnabledOutputTypesOpset24>()),
     ConstantOfShape);
+
+ONNX_CPU_OPERATOR_KERNEL(
+    ConstantOfShape,
+    25,
+    KernelDefBuilder()
+        .TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>())
+        .TypeConstraint("T2",
+                        BuildKernelDefConstraintsFromTypeList<EnabledOutputTypesOpset25>()),
+    ConstantOfShape);
 }  // namespace onnxruntime
diff --git a/onnxruntime/core/providers/cpu/nn/flatten.cc b/onnxruntime/core/providers/cpu/nn/flatten.cc
index 1544052b64df2..790d44e8f89df 100644
--- a/onnxruntime/core/providers/cpu/nn/flatten.cc
+++ b/onnxruntime/core/providers/cpu/nn/flatten.cc
@@ -63,10 +63,19 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
     Flatten);
 
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
+    Flatten,
+    24,
+    24,
+    KernelDefBuilder()
+        .Alias(0, 0)
+        .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
+    Flatten);
+
 // Opset 24
 ONNX_CPU_OPERATOR_KERNEL(
     Flatten,
-    24,
+    25,
     KernelDefBuilder()
         .Alias(0, 0)
         .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
diff --git a/onnxruntime/core/providers/cpu/quantization/quantize_linear.cc b/onnxruntime/core/providers/cpu/quantization/quantize_linear.cc
index 57145ecbda3c5..0f93dd4f476ba 100644
--- a/onnxruntime/core/providers/cpu/quantization/quantize_linear.cc
+++ b/onnxruntime/core/providers/cpu/quantization/quantize_linear.cc
@@ -121,7 +121,7 @@ static void PrepareForQDQ(const TensorShape& input_shape,
 #define REGISTER_DEQUANTIZELINEAR(T)                                         \
   ONNX_CPU_OPERATOR_TYPED_KERNEL(                                            \
       DequantizeLinear,                                                      \
-      24,                                                                    \
+      25,                                                                    \
       T,                                                                     \
       KernelDefBuilder()                                                     \
           .TypeConstraint("T1", DataTypeImpl::GetTensorType<T>())            \
@@ -160,7 +160,7 @@ static void PrepareForQDQ(const TensorShape& input_shape,
           .TypeConstraint("T", DataTypeImpl::GetTensorType<T>()), \
       DequantizeLinear<T>);
 
-// Opset24
+// Opset25
 REGISTER_DEQUANTIZELINEAR(int8_t)
 REGISTER_DEQUANTIZELINEAR(uint8_t)
 REGISTER_DEQUANTIZELINEAR(int16_t)
@@ -175,6 +175,21 @@ REGISTER_DEQUANTIZELINEAR(Float8E5M2)
 REGISTER_DEQUANTIZELINEAR(Float8E5M2FNUZ)
 #endif
 
+// opset24
+REGISTER_DEQUANTIZELINEAR_VERSIONED(int8_t, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(uint8_t, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(int16_t, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(uint16_t, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(int32_t, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(Int4x2, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(UInt4x2, 24, 24)
+#if !defined(DISABLE_FLOAT8_TYPES)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(Float8E4M3FN, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(Float8E4M3FNUZ, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(Float8E5M2, 24, 24)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(Float8E5M2FNUZ, 24, 24)
+#endif
+
 // Opset 23 added support for float4e2m1.
 // TODO: Add support for float4e2m1.
 REGISTER_DEQUANTIZELINEAR_VERSIONED(int8_t, 23, 23)
@@ -591,7 +606,7 @@ Status DequantizeLinear<T>::Compute(OpKernelContext* ctx) const {
 #define REGISTER_QUANTIZELINEAR(T)                                          \
   ONNX_CPU_OPERATOR_TYPED_KERNEL(                                           \
       QuantizeLinear,                                                       \
-      24,                                                                   \
+      25,                                                                   \
       T,                                                                    \
       KernelDefBuilder()                                                    \
           .TypeConstraint("T1", {DataTypeImpl::GetTensorType<float>(),      \
@@ -632,7 +647,7 @@ Status DequantizeLinear<T>::Compute(OpKernelContext* ctx) const {
           .TypeConstraint("T2", DataTypeImpl::GetTensorType<T>()),    \
       QuantizeLinear<T>);
 
-// Opset 24
+// Opset 25
 REGISTER_QUANTIZELINEAR(int8_t)
 REGISTER_QUANTIZELINEAR(uint8_t)
 REGISTER_QUANTIZELINEAR(int16_t)
@@ -646,6 +661,20 @@ REGISTER_QUANTIZELINEAR(Float8E5M2)
 REGISTER_QUANTIZELINEAR(Float8E5M2FNUZ)
 #endif
 
+// Opset 24
+REGISTER_QUANTIZELINEAR_VERSIONED(int8_t, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(uint8_t, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(int16_t, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(uint16_t, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(Int4x2, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(UInt4x2, 24, 24)
+#if !defined(DISABLE_FLOAT8_TYPES)
+REGISTER_QUANTIZELINEAR_VERSIONED(Float8E4M3FN, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(Float8E4M3FNUZ, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(Float8E5M2, 24, 24)
+REGISTER_QUANTIZELINEAR_VERSIONED(Float8E5M2FNUZ, 24, 24)
+#endif
+
 // Opset 23 added support for float4e2m1.
 REGISTER_QUANTIZELINEAR_VERSIONED(int8_t, 23, 23)
 REGISTER_QUANTIZELINEAR_VERSIONED(uint8_t, 23, 23)
diff --git a/onnxruntime/core/providers/cpu/tensor/cast_op.cc b/onnxruntime/core/providers/cpu/tensor/cast_op.cc
index 95422e0769641..767137a185cc2 100644
--- a/onnxruntime/core/providers/cpu/tensor/cast_op.cc
+++ b/onnxruntime/core/providers/cpu/tensor/cast_op.cc
@@ -731,9 +731,19 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .MayInplace(0, 0),  // allocation planner will check input and output sizes match before inplacing
     Cast);
 
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Cast,
     24,
+    24,
+    KernelDefBuilder()
+        .TypeConstraint("T1", BuildKernelDefConstraintsFromTypeList<EnabledSrcTypes>())
+        .TypeConstraint("T2", BuildKernelDefConstraintsFromTypeList<EnabledDstTypes>())
+        .MayInplace(0, 0),  // allocation planner will check input and output sizes match before inplacing
+    Cast);
+
+ONNX_CPU_OPERATOR_KERNEL(
+    Cast,
+    25,
     KernelDefBuilder()
         .TypeConstraint("T1", BuildKernelDefConstraintsFromTypeList<EnabledSrcTypes>())
         .TypeConstraint("T2", BuildKernelDefConstraintsFromTypeList<EnabledDstTypes>())
diff --git a/onnxruntime/core/providers/cpu/tensor/identity_op.cc b/onnxruntime/core/providers/cpu/tensor/identity_op.cc
index aff3947951f0c..a25321a63a273 100644
--- a/onnxruntime/core/providers/cpu/tensor/identity_op.cc
+++ b/onnxruntime/core/providers/cpu/tensor/identity_op.cc
@@ -74,10 +74,17 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     KernelDefBuilder().TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()).Alias(0, 0),
     IdentityOp<false>);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Identity,
     24,
+    24,
+    KernelDefBuilder().TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()).Alias(0, 0),
+    IdentityOp<false>);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Identity,
+    25,
     KernelDefBuilder().TypeConstraint("V", DataTypeImpl::AllTensorAndSequenceTensorAndOptionalTypesIRv9()).Alias(0, 0),
     IdentityOp<false>);
 
diff --git a/onnxruntime/core/providers/cpu/tensor/pad.cc b/onnxruntime/core/providers/cpu/tensor/pad.cc
index ab261bbb8cdb5..842518ab15627 100644
--- a/onnxruntime/core/providers/cpu/tensor/pad.cc
+++ b/onnxruntime/core/providers/cpu/tensor/pad.cc
@@ -134,6 +134,18 @@ ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(
     uint8_t,
     bool);
 
+ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(
+    kCpuExecutionProvider, kOnnxDomain, Pad, 25, Input, 0,
+    float,
+    double,
+    int32_t,
+    int64_t,
+    uint32_t,
+    uint64_t,
+    int8_t,
+    uint8_t,
+    bool);
+
 ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(
     kCpuExecutionProvider, kOnnxDomain, Pad, 11, Input, 0, int32_t, int64_t);
 ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(
@@ -148,6 +160,8 @@ ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(
     kCpuExecutionProvider, kOnnxDomain, Pad, 23, Input, 0, int32_t, int64_t);
 ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(
     kCpuExecutionProvider, kOnnxDomain, Pad, 24, Input, 0, int32_t, int64_t);
+ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(
+    kCpuExecutionProvider, kOnnxDomain, Pad, 25, Input, 0, int32_t, int64_t);
 
 }  // namespace op_kernel_type_control
 
@@ -169,6 +183,9 @@ using EnabledPad23Types = ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST(
 using EnabledPad24Types = ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST(
     kCpuExecutionProvider, kOnnxDomain, Pad, 24, Input, 0);
 
+using EnabledPad25Types = ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST(
+    kCpuExecutionProvider, kOnnxDomain, Pad, 25, Input, 0);
+
 using AllEnabledPadTypes =
     utils::TypeSetUnion<
         EnabledPad2Types,
@@ -240,15 +257,24 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
             BuildKernelDefConstraintsFromTypeList<EnabledPad23Types>()),
     Pad);
 
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Pad,
-    24,
+    24, 24,
     KernelDefBuilder()
         .TypeConstraint(
             "T",
             BuildKernelDefConstraintsFromTypeList<EnabledPad24Types>()),
     Pad);
 
+ONNX_CPU_OPERATOR_KERNEL(
+    Pad,
+    25,
+    KernelDefBuilder()
+        .TypeConstraint(
+            "T",
+            BuildKernelDefConstraintsFromTypeList<EnabledPad25Types>()),
+    Pad);
+
 using PadsVector = PadBase::PadsVector;
 
 Status PadBase::HandleDimValueZero(const Mode& mode, const TensorShape& input_shape, const TensorShape& output_shape) {
diff --git a/onnxruntime/core/providers/cpu/tensor/reshape.cc b/onnxruntime/core/providers/cpu/tensor/reshape.cc
index 1c6815fa1a8f9..333b82494178f 100644
--- a/onnxruntime/core/providers/cpu/tensor/reshape.cc
+++ b/onnxruntime/core/providers/cpu/tensor/reshape.cc
@@ -75,10 +75,20 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("shape", DataTypeImpl::GetTensorType<int64_t>()),
     Reshape);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Reshape,
     24,
+    24,
+    KernelDefBuilder()
+        .Alias(0, 0)
+        .TypeConstraint("T", DataTypeImpl::AllTensorTypesIRv9())
+        .TypeConstraint("shape", DataTypeImpl::GetTensorType<int64_t>()),
+    Reshape);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Reshape,
+    25,
     KernelDefBuilder()
         .Alias(0, 0)
         .TypeConstraint("T", DataTypeImpl::AllTensorTypesIRv9())
diff --git a/onnxruntime/core/providers/cpu/tensor/shape_op.cc b/onnxruntime/core/providers/cpu/tensor/shape_op.cc
index 74ba61cc9aad8..f3f0b389b4732 100644
--- a/onnxruntime/core/providers/cpu/tensor/shape_op.cc
+++ b/onnxruntime/core/providers/cpu/tensor/shape_op.cc
@@ -48,10 +48,17 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     KernelDefBuilder().TypeConstraint("T", DataTypeImpl::AllTensorTypesIRv9()).TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>()),
     Shape);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Shape,
     24,
+    24,
+    KernelDefBuilder().TypeConstraint("T", DataTypeImpl::AllTensorTypesIRv9()).TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>()),
+    Shape);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Shape,
+    25,
     KernelDefBuilder().TypeConstraint("T", DataTypeImpl::AllTensorTypesIRv9()).TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>()),
     Shape);
 
diff --git a/onnxruntime/core/providers/cpu/tensor/size.cc b/onnxruntime/core/providers/cpu/tensor/size.cc
index 7dbc401207fb5..4e9a51a525252 100644
--- a/onnxruntime/core/providers/cpu/tensor/size.cc
+++ b/onnxruntime/core/providers/cpu/tensor/size.cc
@@ -127,10 +127,30 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>()),
     Size);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Size,
     24,
+    24,
+    KernelDefBuilder().TypeConstraint("T",
+                                      std::vector<MLDataType>({DataTypeImpl::GetTensorType<float>(),
+                                                               DataTypeImpl::GetTensorType<double>(),
+                                                               DataTypeImpl::GetTensorType<int8_t>(),
+                                                               DataTypeImpl::GetTensorType<int16_t>(),
+                                                               DataTypeImpl::GetTensorType<int32_t>(),
+                                                               DataTypeImpl::GetTensorType<int64_t>(),
+                                                               DataTypeImpl::GetTensorType<uint8_t>(),
+                                                               DataTypeImpl::GetTensorType<uint16_t>(),
+                                                               DataTypeImpl::GetTensorType<uint32_t>(),
+                                                               DataTypeImpl::GetTensorType<uint64_t>(),
+                                                               DataTypeImpl::GetTensorType<std::string>(),
+                                                               DataTypeImpl::GetTensorType<bool>()}))
+        .TypeConstraint("T1", DataTypeImpl::GetTensorType<int64_t>()),
+    Size);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Size,
+    25,
     KernelDefBuilder().TypeConstraint("T",
                                       std::vector<MLDataType>({DataTypeImpl::GetTensorType<float>(),
                                                                DataTypeImpl::GetTensorType<double>(),
diff --git a/onnxruntime/core/providers/cpu/tensor/squeeze.cc b/onnxruntime/core/providers/cpu/tensor/squeeze.cc
index 3824b8a7c3cfa..ddb0c9cb32388 100644
--- a/onnxruntime/core/providers/cpu/tensor/squeeze.cc
+++ b/onnxruntime/core/providers/cpu/tensor/squeeze.cc
@@ -56,10 +56,19 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .Alias(0, 0),
     Squeeze);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Squeeze,
     24,
+    24,
+    KernelDefBuilder()
+        .TypeConstraint("T", DataTypeImpl::AllTensorTypes())
+        .Alias(0, 0),
+    Squeeze);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Squeeze,
+    25,
     KernelDefBuilder()
         .TypeConstraint("T", DataTypeImpl::AllTensorTypes())
         .Alias(0, 0),
diff --git a/onnxruntime/core/providers/cpu/tensor/transpose.cc b/onnxruntime/core/providers/cpu/tensor/transpose.cc
index f3d91b244481b..1f29ccbd4d8f8 100644
--- a/onnxruntime/core/providers/cpu/tensor/transpose.cc
+++ b/onnxruntime/core/providers/cpu/tensor/transpose.cc
@@ -485,10 +485,17 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     KernelDefBuilder().TypeConstraint("T", BuildKernelDefConstraintsFromTypeList<EnabledDataTypesOpset21>()),
     Transpose);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Transpose,
     24,
+    24,
+    KernelDefBuilder().TypeConstraint("T", BuildKernelDefConstraintsFromTypeList<EnabledDataTypesOpset21>()),
+    Transpose);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Transpose,
+    25,
     KernelDefBuilder().TypeConstraint("T", BuildKernelDefConstraintsFromTypeList<EnabledDataTypesOpset21>()),
     Transpose);
 
diff --git a/onnxruntime/core/providers/cpu/tensor/unsqueeze.cc b/onnxruntime/core/providers/cpu/tensor/unsqueeze.cc
index bf3cff09a140f..1b6ee02061d34 100644
--- a/onnxruntime/core/providers/cpu/tensor/unsqueeze.cc
+++ b/onnxruntime/core/providers/cpu/tensor/unsqueeze.cc
@@ -59,10 +59,19 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
         .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
     Unsqueeze);
 
-// Opset 24
-ONNX_CPU_OPERATOR_KERNEL(
+ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
     Unsqueeze,
     24,
+    24,
+    KernelDefBuilder()
+        .Alias(0, 0)
+        .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
+    Unsqueeze);
+
+// Opset 25
+ONNX_CPU_OPERATOR_KERNEL(
+    Unsqueeze,
+    25,
     KernelDefBuilder()
         .Alias(0, 0)
         .TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
diff --git a/onnxruntime/core/providers/nnapi/nnapi_builtin/builders/impl/base_op_builder.h b/onnxruntime/core/providers/nnapi/nnapi_builtin/builders/impl/base_op_builder.h
index fafeba7bb49fa..ca6ffb388cdc6 100644
--- a/onnxruntime/core/providers/nnapi/nnapi_builtin/builders/impl/base_op_builder.h
+++ b/onnxruntime/core/providers/nnapi/nnapi_builtin/builders/impl/base_op_builder.h
@@ -72,7 +72,7 @@ class BaseOpBuilder : public IOpBuilder {
                                             const OpSupportCheckParams& params) const;
 
   virtual int GetMinSupportedOpSet(const NodeUnit& /* node_unit */) const { return 1; }
-  virtual int GetMaxSupportedOpSet(const NodeUnit& /* node_unit */) const { return 24; }
+  virtual int GetMaxSupportedOpSet(const NodeUnit& /* node_unit */) const { return 25; }
 
   // Check if this node_unit's type is supported
   // SingleNode type NodeUnit is supported
diff --git a/onnxruntime/core/providers/vsinpu/builders/impl/base_op_builder.h b/onnxruntime/core/providers/vsinpu/builders/impl/base_op_builder.h
index 56fc43ad4384d..719a806376222 100644
--- a/onnxruntime/core/providers/vsinpu/builders/impl/base_op_builder.h
+++ b/onnxruntime/core/providers/vsinpu/builders/impl/base_op_builder.h
@@ -49,7 +49,7 @@ class BaseOpBuilder : public IOpBuilder {
   virtual bool IsQuantizedOp(const NodeUnit& /* node_unit */) const { return false; }
 
   virtual int GetMinSupportedOpSet(const NodeUnit& /* node_unit */) const { return 1; }
-  virtual int GetMaxSupportedOpSet(const NodeUnit& /* node_unit */) const { return 24; }
+  virtual int GetMaxSupportedOpSet(const NodeUnit& /* node_unit */) const { return 25; }
 
   virtual bool HasSupportedInputOutputsImpl(
       const InitializedTensorSet& initializers, const NodeUnit& node_unit) const;
diff --git a/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h b/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h
index d45cd93e9982d..a765cd9cbca85 100644
--- a/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h
+++ b/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h
@@ -52,7 +52,7 @@ class BaseOpBuilder : public IOpBuilder {
   // We still set the minimal supported opset to 1 as we couldn't
   // get the model opset version at this stage.
   virtual int GetMinSupportedOpSet(const Node& /* node */) const { return 1; }
-  virtual int GetMaxSupportedOpSet(const Node& /* node */) const { return 24; }
+  virtual int GetMaxSupportedOpSet(const Node& /* node */) const { return 25; }
 
  private:
   bool HasSupportedOpSet(const Node& node, const logging::Logger& logger) const;
diff --git a/onnxruntime/test/onnx/TestCase.cc b/onnxruntime/test/onnx/TestCase.cc
index cbb25bb9b629e..23c860953c52f 100644
--- a/onnxruntime/test/onnx/TestCase.cc
+++ b/onnxruntime/test/onnx/TestCase.cc
@@ -1451,6 +1451,10 @@ std::unique_ptr<std::set<BrokenTest>> GetBrokenTests(const std::string& provider
     broken_tests->insert({"attention_4d_with_past_and_present_qk_matmul_bias_3d_mask_causal", "unknown version"});
     broken_tests->insert({"attention_4d_with_past_and_present_qk_matmul_bias_4d_mask_causal", "unknown version"});
     broken_tests->insert({"attention_4d_diff_heads_mask4d_padded_kv", "need nonpad_kv_seqlen "});
+    // Fails since ONNX==1.20.0
+    broken_tests->insert({"attention_4d_with_past_and_present_qk_matmul_bias_3d_mask_causal_expanded", "unknown version"});
+    broken_tests->insert({"attention_4d_with_past_and_present_qk_matmul_bias_4d_mask_causal_expanded", "unknown version"});
+    broken_tests->insert({"convinteger_with_padding", "unknown version"});
   }
 
 #ifdef DISABLE_CONTRIB_OPS
diff --git a/onnxruntime/test/python/quantization/test_qdq.py b/onnxruntime/test/python/quantization/test_qdq.py
index 178cb9d876fcf..f54b40bb98b56 100644
--- a/onnxruntime/test/python/quantization/test_qdq.py
+++ b/onnxruntime/test/python/quantization/test_qdq.py
@@ -28,6 +28,28 @@
 from onnxruntime.quantization.quant_utils import quantize_nparray
 
 
+# TODO(titaiwang and justinchuby): What is the recommendation here after onnx deleted this function?
+def _unpack_single_4bitx2(x: np.ndarray | np.dtype | float, signed: bool) -> tuple[np.ndarray, np.ndarray]:
+    def unpack_signed(x):
+        return np.where((x >> 3) == 0, x, x | 0xF0)
+
+    """Unpack a single byte 4bitx2 to two 4 bit elements
+    Args:
+        x: Input data
+        signed: boolean, whether to interpret as signed int4.
+    Returns:
+        A tuple of ndarrays containing int4 elements (sign-extended to int8/uint8)
+    """
+    if not isinstance(x, np.ndarray):
+        x = np.asarray(x)
+    x_low = x & 0x0F
+    x_high = x >> 4
+    x_low = unpack_signed(x_low) if signed else x_low
+    x_high = unpack_signed(x_high) if signed else x_high
+    dtype = np.int8 if signed else np.uint8
+    return (x_low.astype(dtype), x_high.astype(dtype))
+
+
 class TestQDQFormat(unittest.TestCase):
     def input_feeds(self, n, name2shape, np_float_type=np.float32):
         input_data_list = []
@@ -1653,7 +1675,7 @@ def test_int4_qdq_conv(self):
             float_data = weight_data.flatten().tolist()
             for index, float_val in enumerate(float_data):
                 expected_int4_val = np.clip(np.float32(float_val / scale_val).round() + zp_val, -8, 7)
-                int4_pair = onnx.subbyte.unpack_single_4bitx2(weight_quant_init.raw_data[index >> 1], True)
+                int4_pair = _unpack_single_4bitx2(weight_quant_init.raw_data[index >> 1], True)
                 int4_val = int4_pair[index & 0x1]
 
                 self.assertEqual(np.float32(int4_val), expected_int4_val)
diff --git a/onnxruntime/test/python/quantization/test_quant_util.py b/onnxruntime/test/python/quantization/test_quant_util.py
index 519e6de078335..468f97c980ad8 100644
--- a/onnxruntime/test/python/quantization/test_quant_util.py
+++ b/onnxruntime/test/python/quantization/test_quant_util.py
@@ -128,7 +128,8 @@ def test_pack_bytes_to_4bit(self):
                 src_int = src_float.astype(numpy.int8 if signed else numpy.uint8)
 
                 actual_packed_vals = bytes(pack_bytes_to_4bit(src_int.tobytes()))
-                expected_packed_vals = onnx.helper.pack_float32_to_4bit(src_float, signed).tobytes()
+                src_4bit = src_float.astype(int4 if signed else uint4)
+                expected_packed_vals = bytes(pack_bytes_to_4bit(src_4bit.tobytes()))
                 self.assertEqual(actual_packed_vals, expected_packed_vals)
 
     def test_quantize_data_4bit(self):
diff --git a/onnxruntime/test/python/requirements.txt b/onnxruntime/test/python/requirements.txt
index 86645f42e3625..8ddba809b9228 100644
--- a/onnxruntime/test/python/requirements.txt
+++ b/onnxruntime/test/python/requirements.txt
@@ -1,3 +1,3 @@
-onnx==1.18.0
+onnx==1.20.1
 pytest
 onnx-ir
diff --git a/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc b/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc
index b0f1d5e626ec8..60d28c491dfd1 100644
--- a/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc
+++ b/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc
@@ -46,6 +46,11 @@
         "^test_castlike_no_saturate_FLOAT_to_FLOAT8*",  // ORT does not support ml_dtypes
         "^test_castlike_UINT4_to*",  // ORT does not support ml_dtypes
         "^test_castlike_INT4_to*",  // ORT does not support ml_dtypes
+        "^test_castlike_INT2_to*",  // ORT does not support int2
+        "^test_castlike_UINT2_to*",  // ORT does not support uint2
+        "^test_cast_INT2_to*",  // ORT does not support int2
+        "^test_cast_UINT2_to*",  // ORT does not support uint2
+        "^test_convinteger_with_padding*",  // ORT does not support per-channel quantization for ConvInteger
         "^test_cast_e8m0_*",  // ORT does not support float8e8m0
         "^test_batchnorm_epsilon_training_mode",
         "^test_batchnorm_example_training_mode",
@@ -721,7 +726,10 @@
         "^test_center_crop_pad_crop_negative_axes_hwc*", // failed due to new types or shape infer with negative axis for CenterCropPad.
         "^test_center_crop_pad_crop_negative_axes_hwc_expanded*", // failed due to new types or shape infer with negative axis for CenterCropPad.
         "^test_reduce_max_empty_set",
-        "^test_reduce_min_empty_set"
+        "^test_reduce_min_empty_set",
+        "^test_matmul_1d_3d_cpu",
+        "^test_matmul_4d_1d_cpu",
+        "^test_matmul_1d_1d_cpu"
     ],
     "current_failing_tests_pure_DML": [
         "^test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_cpu",
diff --git a/tools/ci_build/build.py b/tools/ci_build/build.py
index 43444fcc55478..e7e5cbe5ea031 100644
--- a/tools/ci_build/build.py
+++ b/tools/ci_build/build.py
@@ -624,21 +624,24 @@ def generate_build_tree(
                 not args.disable_wasm_exception_catching,
                 args.minimal_build is not None,
                 args.enable_address_sanitizer,
+                args.use_full_protobuf,
             )
         elif args.android:
-            generate_android_triplets(build_dir, configs, args.android_cpp_shared, args.android_api)
+            generate_android_triplets(
+                build_dir, configs, args.android_cpp_shared, args.android_api, args.use_full_protobuf
+            )
         elif is_windows():
-            generate_windows_triplets(build_dir, configs, args.msvc_toolset)
+            generate_windows_triplets(build_dir, configs, args.msvc_toolset, args.use_full_protobuf)
         elif is_macOS():
             osx_target = args.apple_deploy_target
             if args.apple_deploy_target is None:
                 osx_target = os.environ.get("MACOSX_DEPLOYMENT_TARGET")
             if osx_target is not None:
                 log.info(f"Setting VCPKG_OSX_DEPLOYMENT_TARGET to {osx_target}")
-            generate_macos_triplets(build_dir, configs, osx_target)
+            generate_macos_triplets(build_dir, configs, osx_target, args.use_full_protobuf)
         else:
             # Linux, *BSD, AIX or other platforms
-            generate_linux_triplets(build_dir, configs)
+            generate_linux_triplets(build_dir, configs, args.use_full_protobuf)
         add_default_definition(cmake_extra_defines, "CMAKE_TOOLCHAIN_FILE", str(vcpkg_toolchain_path))
 
         # Choose the cmake triplet
diff --git a/tools/ci_build/github/linux/docker/inference/aarch64/python/cpu/scripts/requirements.txt b/tools/ci_build/github/linux/docker/inference/aarch64/python/cpu/scripts/requirements.txt
index ea5c38a410948..42bee7a892b11 100644
--- a/tools/ci_build/github/linux/docker/inference/aarch64/python/cpu/scripts/requirements.txt
+++ b/tools/ci_build/github/linux/docker/inference/aarch64/python/cpu/scripts/requirements.txt
@@ -7,4 +7,4 @@ wheel
 protobuf==4.25.8
 sympy==1.14
 flatbuffers
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
diff --git a/tools/ci_build/github/linux/docker/scripts/lort/requirements.txt b/tools/ci_build/github/linux/docker/scripts/lort/requirements.txt
index aa8c3556fe9e7..c5fc16837e093 100644
--- a/tools/ci_build/github/linux/docker/scripts/lort/requirements.txt
+++ b/tools/ci_build/github/linux/docker/scripts/lort/requirements.txt
@@ -3,7 +3,7 @@ beartype==0.15.0
 flatbuffers
 cerberus
 h5py
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
 # Python dependencies required for pytorch development
 astunparse
 expecttest!=0.2.0
diff --git a/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt b/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
index f6c93e427b968..8f5d0776501c0 100644
--- a/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
+++ b/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
@@ -10,4 +10,4 @@ flatbuffers
 neural-compressor>=2.2.1
 triton==3.2.0; python_version < "3.14"
 triton==3.5.0; python_version >= "3.14"
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
diff --git a/tools/ci_build/github/linux/docker/scripts/requirements.txt b/tools/ci_build/github/linux/docker/scripts/requirements.txt
index 672efe7a3eaf7..85a9c6391af80 100644
--- a/tools/ci_build/github/linux/docker/scripts/requirements.txt
+++ b/tools/ci_build/github/linux/docker/scripts/requirements.txt
@@ -12,4 +12,4 @@ protobuf==6.33.0
 packaging
 onnxscript==0.5.3; python_version < "3.14"
 onnx-ir==0.1.10; python_version < "3.14"
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
diff --git a/tools/ci_build/github/linux/python/requirements.txt b/tools/ci_build/github/linux/python/requirements.txt
index 7134b64cafb0a..6a474973d4f0c 100644
--- a/tools/ci_build/github/linux/python/requirements.txt
+++ b/tools/ci_build/github/linux/python/requirements.txt
@@ -12,4 +12,4 @@ onnxscript==0.5.3; python_version < "3.14"
 onnx-ir==0.1.10; python_version < "3.14"
 jinja2
 markupsafe
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
diff --git a/tools/ci_build/github/windows/python/requirements.txt b/tools/ci_build/github/windows/python/requirements.txt
index 04b16225e4307..4e24bf7cbfa97 100644
--- a/tools/ci_build/github/windows/python/requirements.txt
+++ b/tools/ci_build/github/windows/python/requirements.txt
@@ -15,4 +15,4 @@ markupsafe
 semver
 packaging
 coloredlogs
-onnx==1.19.1; python_version < "3.14"
+onnx==1.20.1; python_version < "3.14"
diff --git a/tools/python/util/vcpkg_helpers.py b/tools/python/util/vcpkg_helpers.py
index 182d757907ab2..34477dc38e38d 100644
--- a/tools/python/util/vcpkg_helpers.py
+++ b/tools/python/util/vcpkg_helpers.py
@@ -9,7 +9,9 @@
 
 
 # This is a way to add customizations to the official VCPKG ports.
-def add_port_configs(f, has_exception: bool, is_emscripten: bool, enable_minimal_build: bool) -> None:
+def add_port_configs(
+    f, has_exception: bool, is_emscripten: bool, enable_minimal_build: bool, use_full_protobuf: bool = False
+) -> None:
     """
     Add port-specific configurations to the triplet file.
 
@@ -18,6 +20,7 @@ def add_port_configs(f, has_exception: bool, is_emscripten: bool, enable_minimal
         has_exception (bool): Flag indicating if exceptions are enabled.
         is_emscripten (bool): Flag indicating if the target is Emscripten.
         enable_minimal_build (bool): Flag indicating if ONNX minimal build is enabled.
+        use_full_protobuf (bool): Flag indicating if full protobuf should be used (vs lite). Default is False.
     """
     f.write(
         r"""if(PORT MATCHES "benchmark")
@@ -89,8 +92,8 @@ def add_port_configs(f, has_exception: bool, is_emscripten: bool, enable_minimal
     )"""
         )
 
-    if is_emscripten:
-        # Uses ONNX_USE_LITE_PROTO=ON for WebAssembly build.
+    # Uses ONNX_USE_LITE_PROTO=ON for WebAssembly build.
+    if not use_full_protobuf or is_emscripten:
         f.write(
             r"""
     list(APPEND VCPKG_CMAKE_CONFIGURE_OPTIONS
@@ -147,6 +150,7 @@ def generate_triplet_for_android(
     enable_minimal_build: bool,
     use_cpp_shared: bool,
     android_api_level: int,
+    use_full_protobuf: bool,
 ) -> None:
     """
     Generate triplet file for Android platform.
@@ -160,6 +164,7 @@ def generate_triplet_for_android(
         enable_minimal_build (bool): Flag indicating if ONNX minimal build is enabled.
         use_cpp_shared(bool): The type of C++ Runtime to use. If it is false, use "c++_static" which is the default for most CMake projects. Otherwise set the runtime to c++_shared.
         android_api_level(int): android_api_level
+        use_full_protobuf(bool): Flag indicating if full protobuf should be used (vs lite).
     """
     folder_name_parts = []
     if enable_asan:
@@ -267,15 +272,20 @@ def generate_triplet_for_android(
                 f.write(f'set(VCPKG_LINKER_FLAGS "{" ".join(ldflags)}")\n')
             f.write("list(APPEND VCPKG_CMAKE_CONFIGURE_OPTIONS -DCMAKE_CXX_STANDARD=17)\n")
             add_build_type(f, config)
-            add_port_configs(f, enable_exception, False, enable_minimal_build)  # Pass enable_minimal_build
+            add_port_configs(
+                f, enable_exception, False, enable_minimal_build, use_full_protobuf=use_full_protobuf
+            )  # Pass enable_minimal_build
 
 
-def generate_android_triplets(build_dir: str, configs: set[str], use_cpp_shared: bool, android_api_level: int) -> None:
+def generate_android_triplets(
+    build_dir: str, configs: set[str], use_cpp_shared: bool, android_api_level: int, use_full_protobuf: bool
+) -> None:
     """
     Generate triplet files for POSIX platforms (Linux, macOS, Android).
 
     Args:
         build_dir (str): The directory to save the generated triplet files.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     target_abis = ["x64", "arm64", "arm-neon", "x86"]
     for enable_asan in [True, False]:
@@ -295,6 +305,7 @@ def generate_android_triplets(build_dir: str, configs: set[str], use_cpp_shared:
                             enable_minimal_build,
                             use_cpp_shared,
                             android_api_level,
+                            use_full_protobuf=use_full_protobuf,
                         )
 
 
@@ -310,6 +321,7 @@ def generate_triplet_for_posix_platform(
     crt_linkage: str,
     target_abi: str,
     osx_deployment_target: str,
+    use_full_protobuf: bool,
 ) -> None:
     """
     Generate triplet file for POSIX platforms (Linux, macOS).
@@ -325,6 +337,7 @@ def generate_triplet_for_posix_platform(
         crt_linkage (str): The CRT linkage type ("static" or "dynamic").
         target_abi (str): The target ABI, which maps to the VCPKG_TARGET_ARCHITECTURE variable. Valid options include x86, x64, arm, arm64, arm64ec, s390x, ppc64le, riscv32, riscv64, loongarch32, loongarch64, mips64.
         osx_deployment_target (str, optional): The macOS deployment target version. The parameter sets the minimum macOS version for compiled binaries. It also changes what versions of the macOS platform SDK CMake will search for. See the CMake documentation for CMAKE_OSX_DEPLOYMENT_TARGET for more information.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     folder_name_parts = []
     if enable_asan:
@@ -453,7 +466,9 @@ def generate_triplet_for_posix_platform(
             else:
                 f.write("list(APPEND VCPKG_CMAKE_CONFIGURE_OPTIONS -DCMAKE_CXX_STANDARD=17)\n")
             add_build_type(f, config)
-            add_port_configs(f, enable_exception, False, enable_minimal_build)  # Pass enable_minimal_build
+            add_port_configs(
+                f, enable_exception, False, enable_minimal_build, use_full_protobuf=use_full_protobuf
+            )  # Pass enable_minimal_build
 
 
 def generate_vcpkg_triplets_for_emscripten(
@@ -466,6 +481,7 @@ def generate_vcpkg_triplets_for_emscripten(
     enable_wasm_exception_catching: bool,  # Controls -sDISABLE_EXCEPTION_CATCHING=...
     enable_minimal_onnx_build: bool,  # Controls ONNX port setting AND C++ exceptions (-fno-exceptions)
     enable_asan: bool,
+    use_full_protobuf: bool,
 ) -> None:
     """
     Generate triplet files for Emscripten (WASM) for wasm32 and wasm64.
@@ -501,6 +517,7 @@ def generate_vcpkg_triplets_for_emscripten(
                                         Also implicitly controls C++ exceptions for
                                         dependencies (True => -fno-exceptions).
         enable_asan (bool): Flag indicating if AddressSanitizer is enabled for dependencies.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     # Always place generated files in the 'default' folder for Emscripten
     folder_name = "default"
@@ -617,16 +634,18 @@ def generate_vcpkg_triplets_for_emscripten(
                     has_exception=cpp_exceptions_enabled,  # Derived value
                     is_emscripten=True,
                     enable_minimal_build=enable_minimal_onnx_build,
+                    use_full_protobuf=use_full_protobuf,
                 )  # Original parameter
 
 
-def generate_windows_triplets(build_dir: str, configs: set[str], toolset_version: str) -> None:
+def generate_windows_triplets(build_dir: str, configs: set[str], toolset_version: str, use_full_protobuf: bool) -> None:
     """
     Generate triplet files for Windows platforms.
 
     Args:
         build_dir (str): The directory to save the generated triplet files.
         toolset_version (str, optional): The version of the platform toolset.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     # Below are all the CPU ARCHs we support on Windows.
     # ARM64 is for ARM64 processes that contains traditional ARM64 code.
@@ -711,16 +730,22 @@ def generate_windows_triplets(build_dir: str, configs: set[str], toolset_version
                                             f.write(f'set(VCPKG_LINKER_FLAGS "{" ".join(ldflags)}")\n')
                                         add_build_type(f, config)
                                         add_port_configs(
-                                            f, enable_exception, False, enable_minimal_build
+                                            f,
+                                            enable_exception,
+                                            False,
+                                            enable_minimal_build,
+                                            use_full_protobuf=use_full_protobuf,
                                         )  # Pass enable_minimal_build
 
 
-def generate_linux_triplets(build_dir: str, configs: set[str]) -> None:
+def generate_linux_triplets(build_dir: str, configs: set[str], use_full_protobuf: bool) -> None:
     """
     Generate triplet files for Linux platforms.
 
     Args:
         build_dir (str): The directory to save the generated triplet files.
+        configs (set[str]): The set of build configurations.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     target_abis = ["x86", "x64", "arm", "arm64", "s390x", "ppc64le", "riscv64", "loongarch64", "mips64"]
     for enable_rtti in [True, False]:
@@ -745,16 +770,20 @@ def generate_linux_triplets(build_dir: str, configs: set[str]) -> None:
                                 "dynamic",
                                 target_abi,
                                 None,
+                                use_full_protobuf=use_full_protobuf,
                             )
 
 
-def generate_macos_triplets(build_dir: str, configs: set[str], osx_deployment_target: str) -> None:
+def generate_macos_triplets(
+    build_dir: str, configs: set[str], osx_deployment_target: str, use_full_protobuf: bool
+) -> None:
     """
     Generate triplet files for macOS platforms.
 
     Args:
         build_dir (str): The directory to save the generated triplet files.
         osx_deployment_target (str, optional): The macOS deployment target version.
+        use_full_protobuf (bool): Flag indicating if full Protobuf is used.
     """
     target_abis = ["x64", "arm64", "universal2"]
     for enable_rtti in [True, False]:
@@ -780,4 +809,5 @@ def generate_macos_triplets(build_dir: str, configs: set[str], osx_deployment_ta
                                 "dynamic",
                                 target_abi,
                                 osx_deployment_target,
+                                use_full_protobuf=use_full_protobuf,
                             )