diff --git a/cgmanifests/generate_cgmanifest.py b/cgmanifests/generate_cgmanifest.py index a9eaacc6f2938..81181d3ccfb20 100644 --- a/cgmanifests/generate_cgmanifest.py +++ b/cgmanifests/generate_cgmanifest.py @@ -90,55 +90,6 @@ def add_github_dep(name, parsed_url): git_deps[dep] = name -with open( - os.path.join(REPO_DIR, "tools", "ci_build", "github", "linux", "docker", "Dockerfile.manylinux2_28_cuda11"), -) as f: - for line in f: - if not line.strip(): - package_name = None - package_filename = None - package_url = None - if package_filename is None: - m = re.match(r"RUN\s+export\s+(.+?)_ROOT=(\S+).*", line) - if m is not None: - package_name = m.group(1) - package_filename = m.group(2) - else: - m = re.match(r"RUN\s+export\s+(.+?)_VERSION=(\S+).*", line) - if m is not None: - package_name = m.group(1) - package_filename = m.group(2) - elif package_url is None: - m = re.match(r"(.+?)_DOWNLOAD_URL=(\S+)", line) - if m is not None: - package_url = m.group(2) - if package_name == "LIBXCRYPT": - package_url = m.group(2) + "/v" + package_filename + ".tar.gz" - elif package_name == "CMAKE": - package_url = m.group(2) + "/v" + package_filename + "/cmake-" + package_filename + ".tar.gz" - else: - package_url = m.group(2) + "/" + package_filename + ".tar.gz" - parsed_url = urlparse(package_url) - if parsed_url.hostname == "github.com": - add_github_dep("manylinux dependency " + package_name, parsed_url) - else: - registration = { - "Component": { - "Type": "other", - "other": { - "Name": package_name.lower(), - "Version": package_filename.split("-")[-1], - "DownloadUrl": package_url, - }, - "comments": "manylinux dependency", - } - } - registrations.append(registration) - package_name = None - package_filename = None - package_url = None - - def normalize_path_separators(path): return path.replace(os.path.sep, "/") diff --git a/cgmanifests/generated/cgmanifest.json b/cgmanifests/generated/cgmanifest.json index 6f1ca84e1a304..08ca90d7c3b7f 100644 --- a/cgmanifests/generated/cgmanifest.json +++ b/cgmanifests/generated/cgmanifest.json @@ -2,112 +2,6 @@ "$schema": "https://json.schemastore.org/component-detection-manifest.json", "Version": 1, "Registrations": [ - { - "Component": { - "Type": "other", - "other": { - "Name": "autoconf", - "Version": "2.71", - "DownloadUrl": "http://ftp.gnu.org/gnu/autoconf/autoconf-2.71.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "Component": { - "Type": "other", - "other": { - "Name": "automake", - "Version": "1.16.5", - "DownloadUrl": "http://ftp.gnu.org/gnu/automake/automake-1.16.5.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "Component": { - "Type": "other", - "other": { - "Name": "libtool", - "Version": "2.4.7", - "DownloadUrl": "http://ftp.gnu.org/gnu/libtool/libtool-2.4.7.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "Component": { - "Type": "other", - "other": { - "Name": "git", - "Version": "2.36.2", - "DownloadUrl": "https://www.kernel.org/pub/software/scm/git/git-2.36.2.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "Component": { - "Type": "other", - "other": { - "Name": "sqlite_autoconf", - "Version": "3390200", - "DownloadUrl": "https://www.sqlite.org/2022/sqlite-autoconf-3390200.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "Component": { - "Type": "other", - "other": { - "Name": "openssl", - "Version": "1.1.1q", - "DownloadUrl": "https://www.openssl.org/source/openssl-1.1.1q.tar.gz" - }, - "comments": "manylinux dependency" - } - }, - { - "component": { - "type": "git", - "git": { - "commitHash": "50cf2b6dd4fdf04309445f2eec8de7051d953abf", - "repositoryUrl": "https://github.com/besser82/libxcrypt.git" - }, - "comments": "manylinux dependency LIBXCRYPT" - } - }, - { - "component": { - "type": "git", - "git": { - "commitHash": "a896e3d066448b3530dbcaa48869fafefd738f57", - "repositoryUrl": "https://github.com/emscripten-core/emsdk.git" - }, - "comments": "git submodule at cmake/external/emsdk" - } - }, - { - "component": { - "type": "git", - "git": { - "commitHash": "7a2ed51a6b682a83e345ff49fc4cfd7ca47550db", - "repositoryUrl": "https://github.com/google/libprotobuf-mutator.git" - }, - "comments": "git submodule at cmake/external/libprotobuf-mutator" - } - }, - { - "component": { - "type": "git", - "git": { - "commitHash": "e2525550194ce3d8a2c4a3af451c9d9b3ae6650e", - "repositoryUrl": "https://github.com/onnx/onnx.git" - }, - "comments": "git submodule at cmake/external/onnx" - } - }, { "component": { "type": "git", @@ -268,6 +162,16 @@ "comments": "mp11" } }, + { + "component": { + "type": "git", + "git": { + "commitHash": "fdefbe85ed9c362b95b9b401cd19db068a76141f", + "repositoryUrl": "https://github.com/onnx/onnx.git" + }, + "comments": "onnx" + } + }, { "component": { "type": "git", diff --git a/cmake/deps.txt b/cmake/deps.txt index 279b5ca649dba..7cf49f02333a4 100644 --- a/cmake/deps.txt +++ b/cmake/deps.txt @@ -24,7 +24,7 @@ microsoft_gsl;https://github.com/microsoft/GSL/archive/refs/tags/v4.0.0.zip;cf36 microsoft_wil;https://github.com/microsoft/wil/archive/refs/tags/v1.0.230629.1.zip;e4a542a323c070376f7c2d1973d0f7ddbc1d2fa5 mimalloc;https://github.com/microsoft/mimalloc/archive/refs/tags/v2.1.1.zip;d5ee7d34223d0567892db5179849939c8769dc41 mp11;https://github.com/boostorg/mp11/archive/refs/tags/boost-1.82.0.zip;9bc9e01dffb64d9e0773b2e44d2f22c51aace063 -onnx;https://github.com/onnx/onnx/archive/e2525550194ce3d8a2c4a3af451c9d9b3ae6650e.zip;782f23d788185887f520a90535513e244218e928 +onnx;https://github.com/onnx/onnx/archive/14303de049144035dfd94ace5f7a3b44773b1aad.zip;250eab9690392b248d75b56e605fb49eca373442 #use the commit of supporting all the plugins and TRT 8.6-GA (https://github.com/onnx/onnx-tensorrt/commit/0462dc31ae78f48744b6141ae376df1f96d3f459) onnx_tensorrt;https://github.com/onnx/onnx-tensorrt/archive/0462dc31ae78f48744b6141ae376df1f96d3f459.zip;5ff086361956cceb81ed17453a1fd8db2aa4328d protobuf;https://github.com/protocolbuffers/protobuf/archive/refs/tags/v21.12.zip;7cf2733949036c7d52fda017badcab093fe73bfa @@ -44,4 +44,4 @@ tensorboard;https://github.com/tensorflow/tensorboard/archive/373eb09e4c5d2b3cc2 cutlass;https://github.com/NVIDIA/cutlass/archive/refs/tags/v3.0.0.zip;0f95b3c1fc1bd1175c4a90b2c9e39074d1bccefd utf8_range;https://github.com/protocolbuffers/utf8_range/archive/72c943dea2b9240cd09efde15191e144bc7c7d38.zip;9925739c9debc0efa2adcb194d371a35b6a03156 extensions;https://github.com/microsoft/onnxruntime-extensions/archive/94142d8391c9791ec71c38336436319a2d4ac7a0.zip;4365ac5140338b4cb75a39944a4be276e3829b3c -composable_kernel;https://github.com/ROCmSoftwarePlatform/composable_kernel/archive/d52ec01652b7d620386251db92455968d8d90bdc.zip;6b5ce8edf3625f8817086c194fbf94b664e1b0e0 \ No newline at end of file +composable_kernel;https://github.com/ROCmSoftwarePlatform/composable_kernel/archive/d52ec01652b7d620386251db92455968d8d90bdc.zip;6b5ce8edf3625f8817086c194fbf94b664e1b0e0 diff --git a/cmake/deps_update_and_upload.py b/cmake/deps_update_and_upload.py new file mode 100644 index 0000000000000..194d21435f0be --- /dev/null +++ b/cmake/deps_update_and_upload.py @@ -0,0 +1,56 @@ +# in case deps.txt is updated, run this file to update and upload the dependencies so that CI can use them. +# Before running the script, increase the version number found at: +# https://aiinfra.visualstudio.com/Lotus/_artifacts/feed/Lotus/UPack/onnxruntime_build_dependencies/versions +# Run without --do-upload once to verify downloading. Use --do-upload when you are ready to publish. +# python cmake/deps_update_and_upload.py --root-path C:/temp/onnxruntime_deps --version 1.0.82 --do-upload +# update version number in tools\ci_build\github\azure-pipelines\templates\download-deps.yml +import re +import subprocess +import os +import argparse +import tempfile + +parser = argparse.ArgumentParser(description="Update dependencies and publish to Azure Artifacts") +parser.add_argument( + "--root-path", type=str, default=tempfile.gettempdir(), help="Target root path for downloaded files" +) +parser.add_argument("--version", type=str, default="1.0.82", help="Package version to publish") +parser.add_argument("--do-upload", action="store_true", help="Upload the package to Azure Artifacts") +args = parser.parse_args() + +with open("cmake/deps.txt") as file: + text = file.read() + +lines = [line for line in text.split("\n") if not line.startswith("#") and ";" in line] + +root_path = args.root_path + +for line in lines: + url = re.sub("^[^;]+?;https://([^;]+?);.*", r"https://\1", line) + filename = re.sub("^[^;]+?;https://([^;]+?);.*", r"\1", line) + full_path = os.path.join(root_path, filename) + subprocess.run(["curl", "-sSL", "--create-dirs", "-o", full_path, url]) + +package_name = "onnxruntime_build_dependencies" +version = args.version + +# Check if the user is logged in to Azure +result = subprocess.run("az account show", shell=True, capture_output=True, text=True) +if "No subscriptions found" in result.stderr: + # Prompt the user to log in to Azure + print("You are not logged in to Azure. Please log in to continue.") + subprocess.run("az login", shell=True) + +# Publish the package to Azure Artifacts if --no-upload is not specified + +cmd = f'az artifacts universal publish --organization https://dev.azure.com/onnxruntime --feed onnxruntime --name {package_name} --version {version} --description "onnxruntime build time dependencies" --path {root_path}' +if args.do_upload: + subprocess.run(cmd, shell=True) +else: + print("would have run: " + cmd) + +cmd = f'az artifacts universal publish --organization https://dev.azure.com/aiinfra --feed Lotus --name {package_name} --version {version} --description "onnxruntime build time dependencies" --path {root_path}' +if args.do_upload: + subprocess.run(cmd, shell=True) +else: + print("would have run: " + cmd) diff --git a/cmake/patches/onnx/onnx.patch b/cmake/patches/onnx/onnx.patch index 155d153019f85..a2d7672a3d48d 100644 --- a/cmake/patches/onnx/onnx.patch +++ b/cmake/patches/onnx/onnx.patch @@ -64,16 +64,3 @@ index 0aab3e26..0f859267 100644 +#endif + #endif // ! ONNX_ONNX_PB_H -diff --git a/onnx/checker.cc b/onnx/checker.cc -index 8fdaf037..1beb1b88 100644 ---- a/onnx/checker.cc -+++ b/onnx/checker.cc -@@ -190,7 +190,7 @@ void check_tensor(const TensorProto& tensor, const CheckerContext& ctx) { - } - std::string data_path = path_join(ctx.get_model_dir(), relative_path); - // use stat64 to check whether the file exists --#ifdef __APPLE__ -+#if defined(__APPLE__) || defined(__wasm__) - struct stat buffer; // APPLE does not have stat64 - if (stat((data_path).c_str(), &buffer) != 0) { - #else diff --git a/docs/OperatorKernels.md b/docs/OperatorKernels.md index 33c187a28b62e..14b6b339c11f3 100644 --- a/docs/OperatorKernels.md +++ b/docs/OperatorKernels.md @@ -67,7 +67,8 @@ 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**
*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**
*out* output:**T2**|9+|**T1** = tensor(int64)
**T2** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| +|ConstantOfShape|*in* input:**T1**
*out* output:**T2**|20+|**T1** = tensor(int64)
**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)| +|||[9, 19]|**T1** = tensor(int64)
**T2** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| |Conv|*in* X:**T**
*in* W:**T**
*in* B:**T**
*out* Y:**T**|11+|**T** = tensor(float)| |||[1, 10]|**T** = tensor(float)| |ConvInteger|*in* x:**T1**
*in* w:**T2**
*in* x_zero_point:**T1**
*in* w_zero_point:**T2**
*out* y:**T3**|10+|**T1** = tensor(uint8)
**T2** = tensor(uint8)
**T3** = tensor(int32)| @@ -78,7 +79,7 @@ Do not modify directly.* |Crop|*in* input:**T**
*out* output:**T**|1+|**T** = tensor(float)| |CumSum|*in* x:**T**
*in* axis:**T2**
*out* y:**T**|14+|**T** = tensor(double), tensor(float), tensor(int32), tensor(int64)
**T2** = tensor(int32), tensor(int64)| |||[11, 13]|**T** = tensor(double), tensor(float), tensor(int32), tensor(int64)
**T2** = tensor(int32), tensor(int64)| -|DFT|*in* input:**T1**
*in* dft_length:**T2**
*out* output:**T1**|17+|**T1** = tensor(double), tensor(float)
**T2** = tensor(int32), tensor(int64)| +|DFT|*in* input:**T1**
*in* dft_length:**T2**
*in* axis:**tensor(int64)**
*out* output:**T1**

or

*in* input:**T1**
*in* dft_length:**T2**
*out* output:**T1**|17+|**T1** = tensor(double), tensor(float)
**T2** = tensor(int32), tensor(int64)| |DepthToSpace|*in* input:**T**
*out* output:**T**|13+|**T** = tensor(double), tensor(float)| |||[11, 12]|**T** = tensor(double), tensor(float)| |||[1, 10]|**T** = tensor(double), tensor(float)| @@ -935,7 +936,7 @@ Do not modify directly.* |Crop|*in* input:**T**
*out* output:**T**|1+|**T** = tensor(float), tensor(float16)| |CumSum|*in* x:**T**
*in* axis:**T2**
*out* y:**T**|14+|**T** = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| |||11+|**T** = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| -|DFT|*in* input:**T1**
*in* dft_length:**T2**
*out* output:**T1**|17+|**T1** = tensor(float), tensor(float16)
**T2** = tensor(int64)| +|DFT|*in* input:**T1**
*in* dft_length:**T2**
*in* axis:**tensor(int64)**
*out* output:**T1**

or

*in* input:**T1**
*in* dft_length:**T2**
*out* output:**T1**|17+|**T1** = tensor(float), tensor(float16)
**T2** = tensor(int64)| |DepthToSpace|*in* input:**T**
*out* output:**T**|13+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| |||11+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| |||1+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| diff --git a/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h b/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h index 40a03f24f7648..ec5c92f0c7b68 100644 --- a/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h +++ b/onnxruntime/core/optimizer/transpose_optimization/optimizer_api.h @@ -442,7 +442,7 @@ class GraphRef { } // namespace api constexpr int64_t kMinSupportedOpset = 7; -constexpr int64_t kMaxSupportedOpset = 19; +constexpr int64_t kMaxSupportedOpset = 20; // 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 b142db86a7902..b4132d3b770ec 100644 --- a/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h +++ b/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.h @@ -51,7 +51,7 @@ class BaseOpBuilder : public IOpBuilder { virtual bool HasSupportedInputsImpl(const Node& node, const logging::Logger& logger) const; virtual int GetMinSupportedOpSet(const Node& /* node */) const { return 1; } - virtual int GetMaxSupportedOpSet(const Node& /* node */) const { return 19; } + virtual int GetMaxSupportedOpSet(const Node& /* node */) const { return 20; } private: bool HasSupportedOpSet(const Node& node, const logging::Logger& logger) const; diff --git a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc index 18010960e11c8..3d03abf5b7ebc 100644 --- a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc +++ b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc @@ -273,7 +273,7 @@ class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDoma // Opset 9 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, 10, Compress); -class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, ConstantOfShape); +class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, 19, ConstantOfShape); class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, 12, MeanVarianceNormalization); class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, 12, float, Greater); class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 9, 12, double, Greater); @@ -958,6 +958,9 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 19, Scan); class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 19, Shape); +// Opset 20 +class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 20, ConstantOfShape); + // !!PLEASE READ BELOW!! Following that, add new entries above this comment /* *** IMPORTANT! *** @@ -1332,7 +1335,7 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) { // Opset 9 BuildKernelCreateInfo, - BuildKernelCreateInfo, + BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, + + // Opset 20 + BuildKernelCreateInfo, }; for (auto& function_table_entry : function_table) { diff --git a/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc b/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc index 920db5ed34dd1..a93da12ccf595 100644 --- a/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc +++ b/onnxruntime/core/providers/cpu/generator/constant_of_shape.cc @@ -11,11 +11,16 @@ ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPE_LIST_ALL_OPSETS( kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, Output, 0, ConstantOfShapeDefaultOutputTypes); +ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPE_LIST( + kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 20, Output, 0, + ConstantOfShapeDefaultOutputTypesOpset20); + // 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( kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, Output, 0, int64_t); + } // namespace op_kernel_type_control namespace { @@ -24,6 +29,10 @@ using EnabledOutputTypes = ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST_ALL_OPSETS( kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, Output, 0); +using EnabledOutputTypesOpset20 = + ORT_OP_KERNEL_ARG_ENABLED_TYPE_LIST( + kCpuExecutionProvider, kOnnxDomain, ConstantOfShape, 20, Output, 0); + class ConstantOfShape final : public ConstantOfShapeBase, public OpKernel { public: explicit ConstantOfShape(const OpKernelInfo& info) : ConstantOfShapeBase(info), OpKernel(info) {} @@ -66,13 +75,22 @@ Status ConstantOfShape::Compute(OpKernelContext* ctx) const { } // namespace -ONNX_CPU_OPERATOR_KERNEL( +ONNX_CPU_OPERATOR_VERSIONED_KERNEL( ConstantOfShape, 9, + 19, KernelDefBuilder() .TypeConstraint("T1", DataTypeImpl::GetTensorType()) .TypeConstraint("T2", BuildKernelDefConstraintsFromTypeList()), ConstantOfShape); +ONNX_CPU_OPERATOR_KERNEL( + ConstantOfShape, + 20, + KernelDefBuilder() + .TypeConstraint("T1", DataTypeImpl::GetTensorType()) + .TypeConstraint("T2", + BuildKernelDefConstraintsFromTypeList()), + ConstantOfShape); } // namespace onnxruntime diff --git a/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.h b/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.h index d96ff06e3d6d8..9aa73c714daea 100644 --- a/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.h +++ b/onnxruntime/core/providers/cpu/generator/constant_of_shape_base.h @@ -23,6 +23,18 @@ using ConstantOfShapeDefaultOutputTypes = uint8_t, uint16_t, uint32_t, uint64_t, bool>; +using ConstantOfShapeDefaultOutputTypesOpset20 = + TypeList< + BFloat16, + MLFloat16, + float, double, +#if !defined(DISABLE_FLOAT8_TYPES) + Float8E4M3FN, Float8E4M3FNUZ, Float8E5M2, Float8E5M2FNUZ, +#endif + int8_t, int16_t, int32_t, int64_t, + uint8_t, uint16_t, uint32_t, uint64_t, + bool>; + template class ConstantOfShapeBase { protected: 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 301927d9c658f..01e4a3c60281f 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h +++ b/onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h @@ -46,7 +46,7 @@ class BaseOpBuilder : public IOpBuilder { // We still set the mininal 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 19; } + virtual int GetMaxSupportedOpSet(const Node& /* node */) const { return 20; } private: bool HasSupportedOpSet(const Node& node, const logging::Logger& logger) const; diff --git a/onnxruntime/test/framework/function_test.cc b/onnxruntime/test/framework/function_test.cc index e126979532644..6e745776ab6b0 100644 --- a/onnxruntime/test/framework/function_test.cc +++ b/onnxruntime/test/framework/function_test.cc @@ -6,6 +6,7 @@ #include "onnx/defs/parser.h" #include "core/common/span_utils.h" +#include "core/framework/float8.h" #include "core/graph/model.h" #include "core/providers/cpu/cpu_execution_provider.h" #include "core/session/inference_session.h" @@ -69,7 +70,9 @@ static void Check(const char* source, float threshold = 0.001f; for (size_t i = 0; i < size; ++i) { - ASSERT_NEAR(data[i], output_values[i], threshold) << "at position i:" << i; + if (!std::isnan(data[i]) && !std::isnan(output_values[i])) { + ASSERT_NEAR(data[i], output_values[i], threshold) << "at position i:" << i; + } } } @@ -389,25 +392,13 @@ TEST(FunctionTest, AttrSaturateNan) { > agraph (float[N] x) => (float[N] y) { - y0 = local.myfun (x) - y1 = local.myfun (x) - y = Add (y0, y1) - } - - < - opset_import: [ "" : 19 ], - domain: "local" - > - myfun (x) => (y) { - x2 = Constant () - x2_ = Cast(x2) - x3 = CastLike(x2, x2_) - x3_ = Cast(x3) - y = Add (x, x3_) + x_E4M3FNUZ = Cast(x) + x_E4M3FNUZ_2 = CastLike(x, x_E4M3FNUZ) # NaN when OOR + y = Cast(x_E4M3FNUZ_2) } )"; - Check(code, "x", {1.0, 2.0, 1e6}, "y", {243.0, 245.0, 2000241}); // std::numeric_limits::quiet_NaN()}); + Check(code, "x", {1.0, 2.0, 1e6}, "y", {1.0, 2.0, std::numeric_limits::quiet_NaN()}); } #endif diff --git a/onnxruntime/test/framework/inference_session_test.cc b/onnxruntime/test/framework/inference_session_test.cc index 077c6ff58e2da..2298e4afa6de0 100644 --- a/onnxruntime/test/framework/inference_session_test.cc +++ b/onnxruntime/test/framework/inference_session_test.cc @@ -2056,7 +2056,7 @@ TEST(InferenceSessionTests, TestStrictShapeInference) { ASSERT_STATUS_OK(session_options.config_options.AddConfigEntry(kOrtSessionOptionsConfigStrictShapeTypeInference, "1")); tester.Run(session_options, OpTester::ExpectResult::kExpectFailure, - "Mismatch between number of source and target dimensions. Source=1 Target=2", + "Mismatch between number of inferred and declared dimensions. inferred=1 declared=2", excluded_provider_types); } diff --git a/onnxruntime/test/optimizer/graph_transform_test.cc b/onnxruntime/test/optimizer/graph_transform_test.cc index dce1f2d40e8b9..f6482fb865c9b 100755 --- a/onnxruntime/test/optimizer/graph_transform_test.cc +++ b/onnxruntime/test/optimizer/graph_transform_test.cc @@ -6280,7 +6280,7 @@ TEST_F(GraphTransformationTests, ConstantSharing_ShouldNotShareForGraphOutput) { TEST_F(GraphTransformationTests, GatherToSplitFusion) { auto build_test_case = [&](ModelTestBuilder& builder) { auto* data_arg = builder.MakeInput({{54}}); - auto* shape_arg = builder.MakeInput({{1}}); + auto* shape_arg = builder.MakeInput({{4}}); auto* reshape_out = builder.MakeIntermediate({{2, 3, 3, 3}}); auto* gather_index_1 = builder.MakeInitializer({}, {static_cast(0)}); auto* gather_index_2 = builder.MakeInitializer({}, {static_cast(1)}); @@ -6393,7 +6393,7 @@ TEST_F(GraphTransformationTests, GatherToSplitFusion) { TEST_F(GraphTransformationTests, GatherToSplitFusion_NoSqueeze) { auto build_test_case = [&](ModelTestBuilder& builder) { auto* data_arg = builder.MakeInput({{54}}); - auto* shape_arg = builder.MakeInput({{1}}); + auto* shape_arg = builder.MakeInput({{4}}); auto* reshape_out = builder.MakeIntermediate({{2, 3, 3, 3}}); auto* gather_index_1 = builder.MakeInitializer({1}, {static_cast(0)}); auto* gather_index_2 = builder.MakeInitializer({1}, {static_cast(1)}); diff --git a/onnxruntime/test/providers/cpu/controlflow/scan_test.cc b/onnxruntime/test/providers/cpu/controlflow/scan_test.cc index 6d8e05b93510a..8008fd129c19b 100644 --- a/onnxruntime/test/providers/cpu/controlflow/scan_test.cc +++ b/onnxruntime/test/providers/cpu/controlflow/scan_test.cc @@ -578,7 +578,7 @@ TEST(Scan9, DISABLED_BadShape) { ShortSequenceOneInBatchOneLoopStateVar( options, "Node:concat Output:concat_out_1 [ShapeInferenceError] Mismatch between number of source and target dimensions. " - "Source=2 Target=1"); + "inferred=2 declared=1"); } TEST(Scan8, ShortSequenceTwoInBatchOneLoopStateVar) { diff --git a/onnxruntime/test/providers/cpu/nn/conv_fp16_test.cc b/onnxruntime/test/providers/cpu/nn/conv_fp16_test.cc index c8343483b80a6..cb5fc8095982c 100644 --- a/onnxruntime/test/providers/cpu/nn/conv_fp16_test.cc +++ b/onnxruntime/test/providers/cpu/nn/conv_fp16_test.cc @@ -109,7 +109,7 @@ TEST(ConvFp16Test, Conv1D_Invalid_Input_Shape) { TestConvFp16Op(attrs, {X, dummy_vals}, {X_shape, dummy_shape}, dummy_vals, dummy_shape, false, OpTester::ExpectResult::kExpectFailure, "Node:node1 Output:Y [ShapeInferenceError] Can't merge shape info. " - "Both source and target dimension have values but they differ. Source=0 Target=2 Dimension=2", + "Both inferred and declared dimension have values but they differ. Inferred=0 Declared=2 Dimension=2", -1); // use latest opset for shape inferencing errors } @@ -132,7 +132,7 @@ TEST(ConvFp16Test, Conv2D_Invalid_Input_Shape) { TestConvFp16Op(attrs, {X, dummy_vals}, {X_shape, dummy_shape}, dummy_vals, dummy_shape, false, OpTester::ExpectResult::kExpectFailure, "Node:node1 Output:Y [ShapeInferenceError] Can't merge shape info. " - "Both source and target dimension have values but they differ. Source=1 Target=2 Dimension=0", + "Both inferred and declared dimension have values but they differ. Inferred=1 Declared=2 Dimension=0", -1); // use latest opset for shape inferencing errors } diff --git a/onnxruntime/test/providers/cpu/nn/conv_op_test.cc b/onnxruntime/test/providers/cpu/nn/conv_op_test.cc index e01fd8c78e55f..5103aed50b152 100644 --- a/onnxruntime/test/providers/cpu/nn/conv_op_test.cc +++ b/onnxruntime/test/providers/cpu/nn/conv_op_test.cc @@ -249,7 +249,7 @@ TEST(ConvTest, Conv1D_Invalid_Input_Shape) { TestConvOp(attrs, {X, dummy_vals}, {X_shape, dummy_shape}, dummy_vals, dummy_shape, false, OpTester::ExpectResult::kExpectFailure, "Node:node1 Output:Y [ShapeInferenceError] Can't merge shape info. " - "Both source and target dimension have values but they differ. Source=0 Target=2 Dimension=2", + "Both inferred and declared dimension have values but they differ. Inferred=0 Declared=2 Dimension=2", -1); // use latest opset for shape inferencing errors } @@ -272,7 +272,7 @@ TEST(ConvTest, Conv2D_Invalid_Input_Shape) { TestConvOp(attrs, {X, dummy_vals}, {X_shape, dummy_shape}, dummy_vals, dummy_shape, false, OpTester::ExpectResult::kExpectFailure, "Node:node1 Output:Y [ShapeInferenceError] Can't merge shape info. " - "Both source and target dimension have values but they differ. Source=1 Target=2 Dimension=0", + "Both inferred and declared dimension have values but they differ. Inferred=1 Declared=2 Dimension=0", -1); // use latest opset for shape inferencing errors } diff --git a/onnxruntime/test/providers/cpu/nn/tfidfvectorizer_test.cc b/onnxruntime/test/providers/cpu/nn/tfidfvectorizer_test.cc index a22253dbb74d4..379b892f39135 100644 --- a/onnxruntime/test/providers/cpu/nn/tfidfvectorizer_test.cc +++ b/onnxruntime/test/providers/cpu/nn/tfidfvectorizer_test.cc @@ -91,7 +91,7 @@ TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip0_Empty_Dim1Fail) { test.Run(OpTester::ExpectResult::kExpectFailure, "Can't merge shape info. " - "Both source and target dimension have values but they differ. Source=7 Target=0 Dimension=0"); + "Both inferred and declared dimension have values but they differ. Inferred=7 Declared=0 Dimension=0"); } TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip0_Empty_Dim1Success) { @@ -136,7 +136,7 @@ TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip0_Empty_Dim2) { test.AddOutput("Y", out_dims, output); test.Run(OpTester::ExpectResult::kExpectFailure, - "Mismatch between number of source and target dimensions. Source=2 Target=1"); + "Mismatch between number of inferred and declared dimensions. inferred=2 declared=1"); } TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip01_Empty_Dim2) { @@ -159,7 +159,7 @@ TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip01_Empty_Dim2) { test.AddOutput("Y", out_dims, output); test.Run(OpTester::ExpectResult::kExpectFailure, - "Mismatch between number of source and target dimensions. Source=2 Target=1"); + "Mismatch between number of inferred and declared dimensions. inferred=2 declared=1"); } TEST(TfIdfVectorizerTest, Int32_TF_onlyBigrams_Skip0_Empty_Dim2N) { diff --git a/onnxruntime/test/providers/cpu/tensor/transpose_test.cc b/onnxruntime/test/providers/cpu/tensor/transpose_test.cc index c334e0c5ddcb6..0e7ac5ed2b2f0 100644 --- a/onnxruntime/test/providers/cpu/tensor/transpose_test.cc +++ b/onnxruntime/test/providers/cpu/tensor/transpose_test.cc @@ -37,7 +37,7 @@ TEST(TransposeOpTest, PermRankDoesNotMatchTensorRank) { // This failure comes from shape inference, because in this case it knows the input dims. // But in the real world, the model can supply different input dims at runtime. test.Run(OpTester::ExpectResult::kExpectFailure, - "Node:node1 Output:Y [ShapeInferenceError] Mismatch between number of source and target dimensions. Source=3 Target=4"); + "Node:node1 Output:Y [ShapeInferenceError] Mismatch between number of inferred and declared dimensions. inferred=3 declared=4"); } // Some of the tests can't run on TensorrtExecutionProvider because of errors. diff --git a/onnxruntime/test/python/quantization/op_test_utils.py b/onnxruntime/test/python/quantization/op_test_utils.py index e94ac5c961583..f26b6297cdbda 100644 --- a/onnxruntime/test/python/quantization/op_test_utils.py +++ b/onnxruntime/test/python/quantization/op_test_utils.py @@ -279,6 +279,9 @@ def check_model_correctness( ops_set = set(node.op_type for node in model_onnx.graph.node) check_reference_evaluator = not (ops_set & {"EmbedLayerNormalization", "Conv", "Attention", "Transpose"}) + with open(model_path_to_check, "rb") as f: + model_check = onnx.load(f) + if check_reference_evaluator and onnx_recent_enough: ref = ReferenceEvaluator(model_path_origin) ref_origin_results = ref.run(None, inputs) @@ -289,7 +292,7 @@ def check_model_correctness( output, rtol=rtol, atol=atol, - err_msg=f"Model {model_path_to_check!r} failed for providers={providers!r}.", + err_msg=f"Model {model_path_origin!r} failed for providers={providers!r}.", ) # Verifies the shapes in the quantized model. @@ -301,40 +304,52 @@ def check_model_correctness( expected_shapes[init.name] = tuple(init.dims) checked = 0 f8_quantization = False - with open(model_path_to_check, "rb") as f: - model_check = onnx.load(f) - for init in model_check.graph.initializer: - if init.name.endswith("_quantized"): - name = init.name.replace("_quantized", "") - expected = expected_shapes[name] - shape = tuple(init.dims) - if not dynamic and expected != shape: - raise AssertionError( - f"Shape mismatch for initializer {init.name!r} from {init.name!r}, " - f"shape={shape} != {expected} (expected)." - ) - else: - checked += 1 - if "zero_point" in init.name: - dt = init.data_type - f8_quantization = f8_quantization or dt in ( - TensorProto.FLOAT8E4M3FN, - TensorProto.FLOAT8E4M3FNUZ, - TensorProto.FLOAT8E5M2, - TensorProto.FLOAT8E5M2FNUZ, + for init in model_check.graph.initializer: + if init.name.endswith("_quantized"): + name = init.name.replace("_quantized", "") + expected = expected_shapes[name] + shape = tuple(init.dims) + if not dynamic and expected != shape: + raise AssertionError( + f"Shape mismatch for initializer {init.name!r} from {init.name!r}, " + f"shape={shape} != {expected} (expected)." ) - if checked == 0: - raise AssertionError( - f"Unable to check expected shape, expected_shapes={expected_shapes}, " - f"names={[init.name for init in model_check.graph.initializer]}." + else: + checked += 1 + if "zero_point" in init.name: + dt = init.data_type + f8_quantization = f8_quantization or dt in ( + TensorProto.FLOAT8E4M3FN, + TensorProto.FLOAT8E4M3FNUZ, + TensorProto.FLOAT8E5M2, + TensorProto.FLOAT8E5M2FNUZ, ) + if checked == 0: + raise AssertionError( + f"Unable to check expected shape, expected_shapes={expected_shapes}, " + f"names={[init.name for init in model_check.graph.initializer]}." + ) if f8_quantization: check_sign_f8_quantization(model_path_origin, model_path_to_check) # Verifies the expected outputs. if check_reference_evaluator and onnx_recent_enough: + reference_new_ops = [QGemm] + has_missing_reference_ops = any( + node.domain not in ["", "ai.onnx"] + and not any( + node.domain == new_node.op_domain and node.op_type == new_node.__name__ + for new_node in reference_new_ops + ) + for node in model_check.graph.node + ) + if has_missing_reference_ops: + # We need to skip the test if the model contains ops that are not supported. + testcase.skipTest( + f"Model {model_path_to_check!r} contains ops that are not supported by the reference evaluator." + ) # Needs pv.Version(onnx.__version__) >= pv.Version("1.16.0") - ref = ReferenceEvaluator(model_path_to_check, new_ops=[QGemm]) + ref = ReferenceEvaluator(model_check, new_ops=reference_new_ops) target_results = ref.run(None, inputs) testcase.assertEqual(len(origin_results), len(target_results), "result count are different") for idx, ref_output in enumerate(origin_results): diff --git a/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc b/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc index 71a10f646a7c6..67391cb1a8219 100644 --- a/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc +++ b/onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc @@ -233,7 +233,64 @@ "^test_resize_upsample_sizes_nearest_cuda", "^test_resize_upsample_sizes_nearest_floor_align_corners_cuda", "^test_resize_upsample_sizes_nearest_not_larger_cuda", - "^test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cuda" + "^test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cuda", + // onnx 1.15 (opset 20) new and updated op tests + "^test_ai_onnx_ml_label_encoder_string_int", + "^test_ai_onnx_ml_label_encoder_string_int_no_default", + "^test_ai_onnx_ml_label_encoder_tensor_mapping", + "^test_ai_onnx_ml_label_encoder_tensor_value_only_mapping", + "^test_gridsample_aligncorners_true", + "^test_gridsample_bicubic_align_corners_0_additional_1", + "^test_gridsample_bicubic_align_corners_1_additional_1", + "^test_gridsample_bicubic", + "^test_gridsample_bilinear_align_corners_0_additional_1", + "^test_gridsample_bilinear_align_corners_1_additional_1", + "^test_gridsample_bilinear", + "^test_gridsample_border_padding", + "^test_gridsample", + "^test_gridsample_nearest_align_corners_0_additional_1", + "^test_gridsample_nearest_align_corners_1_additional_1", + "^test_gridsample_nearest", + "^test_gridsample_reflection_padding", + "^test_gridsample_volumetric_bilinear_align_corners_0", + "^test_gridsample_volumetric_bilinear_align_corners_1", + "^test_gridsample_volumetric_nearest_align_corners_0", + "^test_gridsample_volumetric_nearest_align_corners_1", + "^test_gridsample_zeros_padding", + "^test_image_decoder_decode_bmp_rgb", + "^test_image_decoder_decode_jpeg2k_rgb", + "^test_image_decoder_decode_jpeg_bgr", + "^test_image_decoder_decode_jpeg_grayscale", + "^test_image_decoder_decode_jpeg_rgb", + "^test_image_decoder_decode_png_rgb", + "^test_image_decoder_decode_pnm_rgb", + "^test_image_decoder_decode_tiff_rgb", + "^test_image_decoder_decode_webp_rgb", + "^test_regex_full_match_basic", + "^test_regex_full_match_email_domain", + "^test_regex_full_match_empty", + "^test_string_concat_broadcasting", + "^test_string_concat", + "^test_string_concat_empty_string", + "^test_string_concat_utf8", + "^test_string_concat_zero_dimensional", + "^test_string_split_basic", + "^test_string_split_consecutive_delimiters", + "^test_string_split_empty_string_delimiter", + "^test_string_split_empty_tensor", + "^test_string_split_maxsplit", + "^test_string_split_no_delimiter", + "^test_dft_axis", + "^test_dft", + "^test_dft_inverse", + "^test_isinf", + "^test_isinf_float16", + "^test_isinf_negative", + "^test_isinf_positive", + "^test_isnan", + "^test_isnan_float16", + "^test_reduce_max_bool_inputs", + "^test_reduce_min_bool_inputs" ], "current_failing_tests_x86": [ "^test_vgg19", @@ -316,7 +373,24 @@ "^test_layer_normalization_4d_axis_negative_1_expanded_ver18_cpu", "^test_layer_normalization_4d_axis_negative_2_expanded_ver18_cpu", "^test_layer_normalization_4d_axis_negative_3_expanded_ver18_cpu", - "^test_layer_normalization_default_axis_expanded_ver18_cpu" + "^test_layer_normalization_default_axis_expanded_ver18_cpu", + // onnx 1.15 (opset 20) new and updated op tests (test_affine_grid_???_expanded utilizes ConstantOfShape so it needs to be skipped as well) + // https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1139541&view=logs&j=249e9d58-0012-5814-27cf-6a201adbd9cf&t=bb33e81f-0527-50e0-0fd2-e94f509f0a82 + // only supported with cpu provider + "^test_affine_grid_2d", + "^test_affine_grid_2d_align_corners", + "^test_affine_grid_2d_align_corners_expanded", + "^test_affine_grid_2d_expanded", + "^test_affine_grid_3d", + "^test_affine_grid_3d_align_corners", + "^test_affine_grid_3d_align_corners_expanded", + "^test_affine_grid_3d_expanded", + "^test_constantofshape_float_ones", + "^test_constantofshape_int_shape_zero", + "^test_constantofshape_int_zeros", + // https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1141563&view=logs&j=a018b46d-e41a-509d-6581-c95fdaa42fcd&t=d61c1d37-f101-5d28-982f-e5931b720302 + "^test_gelu_tanh_2_cpu", + "^test_gelu_tanh_2_expanded_cpu" ], "current_failing_tests_NNAPI": [ "^test_maxpool_2d_uint8", @@ -569,7 +643,22 @@ "^test_sequence_map_identity_1_sequence_cpu", "^test_sequence_map_identity_1_sequence_expanded_cpu", "^test_sequence_map_identity_2_sequences_cpu", - "^test_sequence_map_identity_2_sequences_expanded_cpu" + "^test_sequence_map_identity_2_sequences_expanded_cpu", + // onnx 1.15 (opset 20) new and updated op tests (test_affine_grid_???_expanded utilizes ConstantOfShape so it needs to be skipped as well) + // https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1139542&view=logs&j=3032dfba-5baf-5872-0871-2e69cb7f4b6a&t=f0d05deb-fc26-5aaf-e43e-7db2764c07da + // only supported with cpu provider + "^test_affine_grid_2d", + "^test_affine_grid_2d_align_corners", + "^test_affine_grid_2d_align_corners_expanded", + "^test_affine_grid_2d_expanded", + "^test_affine_grid_3d", + "^test_affine_grid_3d_align_corners", + "^test_affine_grid_3d_align_corners_expanded", + "^test_affine_grid_3d_expanded", + "^test_constantofshape_float_ones", + "^test_constantofshape_int_shape_zero", + "^test_constantofshape_int_zeros" + ], // ORT first supported opset 7, so models with nodes that require versions prior to opset 7 are not supported "tests_with_pre_opset7_dependencies": [ diff --git a/onnxruntime/test/testdata/onnx_backend_test_series_overrides.jsonc b/onnxruntime/test/testdata/onnx_backend_test_series_overrides.jsonc index caeea0a758ad9..07385ac9ade05 100644 --- a/onnxruntime/test/testdata/onnx_backend_test_series_overrides.jsonc +++ b/onnxruntime/test/testdata/onnx_backend_test_series_overrides.jsonc @@ -7,6 +7,9 @@ "test_dft": 1e-3, "test_dft_axis": 1e-3, "test_dft_inverse": 1e-3, + "test_dft_opset19": 1e-3, + "test_dft_axis_opset19": 1e-3, + "test_dft_inverse_opset19": 1e-3, "test_stft": 1e-4, "test_stft_with_window": 1e-4 }, diff --git a/orttraining/orttraining/core/graph/training_op_defs.cc b/orttraining/orttraining/core/graph/training_op_defs.cc index 91b1df7b7cf2d..86d3cdee9ba98 100644 --- a/orttraining/orttraining/core/graph/training_op_defs.cc +++ b/orttraining/orttraining/core/graph/training_op_defs.cc @@ -4171,7 +4171,7 @@ Return true if all elements are true and false otherwise. "T", OpSchema::Variadic, /*is_homogeneous*/ false, /*min_arity*/ 1) - .TypeConstraint("T", OpSchema::all_tensor_types_with_bfloat(), + .TypeConstraint("T", OpSchema::all_tensor_types_ir4(), "Allow inputs and outputs to be any kind of tensor."); #endif // ENABLE_TRITON diff --git a/requirements-dev.txt b/requirements-dev.txt index 73e04e6b37c0b..1b5ca65cf8037 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -17,4 +17,4 @@ scikit-learn scipy sympy wheel -setuptools>=41.4.0 +setuptools>=61.0.0 diff --git a/requirements-training.txt b/requirements-training.txt index 4b1be6cef9b7c..dbfd7305d1bec 100644 --- a/requirements-training.txt +++ b/requirements-training.txt @@ -6,4 +6,4 @@ onnx packaging protobuf sympy -setuptools>=41.4.0 +setuptools>=61.0.0 diff --git a/tools/ci_build/github/azure-pipelines/templates/download-deps.yml b/tools/ci_build/github/azure-pipelines/templates/download-deps.yml index f17bc8de5739b..cf73691a5eecc 100644 --- a/tools/ci_build/github/azure-pipelines/templates/download-deps.yml +++ b/tools/ci_build/github/azure-pipelines/templates/download-deps.yml @@ -11,7 +11,7 @@ steps: packageType: upack feed: '/7424c8e4-5c62-490e-95c4-79446f31017c' definition: '517c4f6f-5437-4392-a70d-4f15ec5be2f0' - version: 1.0.81 + version: 1.0.90 downloadPath: $(Build.BinariesDirectory)/deps # The private ADO project @@ -22,7 +22,7 @@ steps: packageType: upack feed: '/4c7631f5-24c0-4307-8822-1aa8f180c325' definition: 'fd9dd5ad-b73e-4678-890e-edcf680dbc1a' - version: 1.0.81 + version: 1.0.90 downloadPath: $(Build.BinariesDirectory)/deps # You can add more ADO accounts at here. diff --git a/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-prebuild-steps.yml b/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-prebuild-steps.yml index 8868e671a5fa5..1ba907fe30df6 100644 --- a/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-prebuild-steps.yml +++ b/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-prebuild-steps.yml @@ -31,7 +31,7 @@ steps: architecture: ${{parameters.BuildArch}} - script: | - python -m pip install -q setuptools wheel numpy flatbuffers + python -m pip install --upgrade "setuptools>=61.0.0" wheel numpy flatbuffers workingDirectory: '$(Build.BinariesDirectory)' displayName: 'Install python modules' 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 6b8003c01c24d..9eef51862c326 100644 --- a/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt +++ b/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt @@ -4,7 +4,7 @@ mypy pytest setuptools>=41.4.0 wheel -git+http://github.com/onnx/onnx.git@e2525550194ce3d8a2c4a3af451c9d9b3ae6650e#egg=onnx +git+http://github.com/onnx/onnx.git@ac3e58759463ff3a3089e3cd64fddbfad0f6724d#egg=onnx protobuf==3.20.2 sympy==1.12 flatbuffers