mirror of
https://github.com/saymrwulf/onnxruntime.git
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bfloat16 and opset13 related fix (#4913)
* regsiter part of opset13 cpu kernels; fix a bug in func impl; adjust reshapefusion order * remove useless function Co-authored-by: Cheng Tang <chenta@microsoft.com>
This commit is contained in:
Tang, Cheng
GitHub
parent
970ddd56a7
commit
efdd96595f
6 changed files with 101 additions and 41 deletions
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@ -220,10 +220,6 @@ FunctionImpl::FunctionImpl(const onnxruntime::Graph& graph,
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ORT_ENFORCE(status.IsOK(), status.ErrorMessage());
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}
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static std::unordered_map<std::string, int> GetOpsetVersionMap(const ONNX_NAMESPACE::FunctionProto& onnx_func_proto) {
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return std::unordered_map<std::string, int>{{onnxruntime::kOnnxDomain, static_cast<int>(onnx_func_proto.since_version())}};
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}
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FunctionImpl::FunctionImpl(const onnxruntime::Graph& graph,
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const onnxruntime::NodeIndex& node_index,
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const ONNX_NAMESPACE::FunctionProto& onnx_func_proto,
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@ -232,7 +228,7 @@ FunctionImpl::FunctionImpl(const onnxruntime::Graph& graph,
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body_(onnx_func_proto.name(), false, onnxruntime::ModelMetaData(),
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graph.ModelPath().ToPathString(),
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IOnnxRuntimeOpSchemaRegistryList(),
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GetOpsetVersionMap(onnx_func_proto), {}, logger),
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graph.DomainToVersionMap(), {}, logger),
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onnx_func_proto_(onnx_func_proto) {
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// Make a copy of the FunctionProto.
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// All FunctionBody ops with the same op type seem to share the same FunctionProto struct within a model.
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@ -298,9 +294,6 @@ FunctionImpl::FunctionImpl(const onnxruntime::Graph& graph,
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op_schema_->Finalize();
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//construct body
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std::unordered_map<std::string, int> domain_to_version;
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//TODO: set correct domain and version
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domain_to_version[onnxruntime::kOnnxDomain] = static_cast<int>(onnx_func_proto_.since_version());
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auto& function_body_graph = body_.MainGraph();
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std::vector<const NodeArg*> graph_inputs(node_in_parent_graph->InputDefs().size(), nullptr),
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graph_outputs(node_in_parent_graph->OutputDefs().size(), nullptr);
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@ -49,6 +49,14 @@ template Status ElementWiseRangedTransform<float>::Create(const std::string& typ
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#define REGISTER_UNARY_ELEMENTWISE_KERNEL(x, sinceVersion) REGISTER_UNARY_ELEMENTWISE_KERNEL_ALIAS(x, x, sinceVersion)
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#define REGISTER_VERSIONED_UNARY_ELEMENTWISE_KERNEL_ALIAS(alias, x, sinceVersion, firstEnd, newVersion) \
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ONNX_CPU_OPERATOR_VERSIONED_KERNEL( \
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alias, sinceVersion, firstEnd, \
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KernelDefBuilder().MayInplace(0, 0).TypeConstraint("T", DataTypeImpl::GetTensorType<float>()), x<float>); \
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ONNX_CPU_OPERATOR_KERNEL( \
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alias, newVersion, \
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KernelDefBuilder().MayInplace(0, 0).TypeConstraint("T", DataTypeImpl::GetTensorType<float>()), x<float>);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(Elu, 6);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(HardSigmoid, 6);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(LeakyRelu, 6);
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@ -57,7 +65,7 @@ REGISTER_UNARY_ELEMENTWISE_KERNEL(Selu, 6);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(Sigmoid, 6);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(Softplus, 1);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(Softsign, 1);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(Tanh, 6);
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REGISTER_VERSIONED_UNARY_ELEMENTWISE_KERNEL_ALIAS(Tanh, Tanh, 6, 12, 13);
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REGISTER_UNARY_ELEMENTWISE_KERNEL(ThresholdedRelu, 10);
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namespace functors {
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@ -38,7 +38,8 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Sel
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Sigmoid);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Softplus);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Softsign);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Tanh);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, 12, Tanh);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Tanh);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9, PRelu);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, RandomNormal);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, RandomUniform);
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@ -198,18 +199,18 @@ class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDoma
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9, float, Upsample);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9, int32_t, Upsample);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9, uint8_t, Upsample);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, float, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, double, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int8_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int16_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int32_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int64_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint8_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint16_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint32_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint64_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, bool, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, MLFloat16, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, float, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, double, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int8_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int16_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int32_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int64_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint8_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint16_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint32_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint64_t, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, bool, Expand);
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class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, MLFloat16, Expand);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 8, Scan);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 10, If);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 10, Loop);
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@ -355,7 +356,7 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Ga
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Slice);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Split);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Squeeze);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Unsqueeze);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, 12, Unsqueeze);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Det);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, ScatterElements);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, NonMaxSuppression);
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@ -429,6 +430,21 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain,
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, GatherND);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, Einsum);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Sign);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Unsqueeze);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, float, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, double, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int16_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int32_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int64_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint8_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint16_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint32_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint64_t, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, bool, Expand);
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class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, MLFloat16, Expand);
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// REVIEW(codemzs): ConstEigenVectorArrayMap.cast<MLFLoat16) does not seem to be supported.
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// However these types work on GPU implementation.
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//class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, MLFloat16_MLFloat16, Dropout);
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@ -466,7 +482,8 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Sigmoid)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Softplus)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Softsign)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Tanh)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, 12, Tanh)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Tanh)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9,
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PRelu)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, RandomNormal)>,
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@ -713,29 +730,29 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
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int32_t, Upsample)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 7, 9,
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uint8_t, Upsample)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, float,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, float,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, double,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, double,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int8_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int8_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int16_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int16_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int32_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int32_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, int64_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, int64_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint8_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint8_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint16_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint16_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint32_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint32_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, uint64_t,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, uint64_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, bool,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, bool,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, MLFloat16,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 12, MLFloat16,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 8, 8, Scan)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 10, If)>,
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@ -939,7 +956,8 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Slice)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Split)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Squeeze)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Unsqueeze)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, 12,
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Unsqueeze)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Det)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, ScatterElements)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11,
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@ -1104,6 +1122,32 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
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ReduceMin)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, GatherND)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, Einsum)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Unsqueeze)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, float,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, double,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int16_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int32_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int64_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint8_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint16_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint32_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint64_t,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, bool,
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Expand)>,
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BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, MLFloat16,
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Expand)>,
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// REVIEW(codemzs): ConstEigenVectorArrayMap.cast<MLFLoat16) does not seem to be supported.
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// However these types work on GPU implementation.
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//BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 12, MLFloat16_MLFloat16, Dropout)>,
|
||||
|
|
|
|||
|
|
@ -1070,9 +1070,16 @@ Status Expand_8<T>::Compute(OpKernelContext* context) const {
|
|||
}
|
||||
|
||||
#define REG_EXPAND_KERNEL(TYPE) \
|
||||
ONNX_CPU_OPERATOR_TYPED_KERNEL( \
|
||||
ONNX_CPU_OPERATOR_VERSIONED_TYPED_KERNEL( \
|
||||
Expand, \
|
||||
8, \
|
||||
12, \
|
||||
TYPE, \
|
||||
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<TYPE>()), \
|
||||
Expand_8<TYPE>); \
|
||||
ONNX_CPU_OPERATOR_TYPED_KERNEL( \
|
||||
Expand, \
|
||||
13, \
|
||||
TYPE, \
|
||||
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<TYPE>()), \
|
||||
Expand_8<TYPE>);
|
||||
|
|
|
|||
|
|
@ -18,9 +18,18 @@ ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
|
|||
.TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
|
||||
Unsqueeze);
|
||||
|
||||
ONNX_CPU_OPERATOR_KERNEL(
|
||||
ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
|
||||
Unsqueeze,
|
||||
11,
|
||||
12,
|
||||
KernelDefBuilder()
|
||||
.Alias(0, 0)
|
||||
.TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
|
||||
Unsqueeze);
|
||||
|
||||
ONNX_CPU_OPERATOR_KERNEL(
|
||||
Unsqueeze,
|
||||
13,
|
||||
KernelDefBuilder()
|
||||
.Alias(0, 0)
|
||||
.TypeConstraint("T", DataTypeImpl::AllTensorTypes()),
|
||||
|
|
|
|||
|
|
@ -90,6 +90,7 @@ std::vector<std::unique_ptr<GraphTransformer>> GeneratePreTrainingTransformers(
|
|||
}
|
||||
|
||||
transformers.emplace_back(onnxruntime::make_unique<ConstantFolding>(execution_provider, compatible_eps, weights_to_train));
|
||||
transformers.emplace_back(onnxruntime::make_unique<ReshapeFusion>(compatible_eps));
|
||||
auto horizontal_parallel_size = training::DistributedRunContext::GroupSize(training::WorkerGroupType::HorizontalParallel);
|
||||
if (horizontal_parallel_size > 1) {
|
||||
LOGS_DEFAULT(WARNING) << horizontal_parallel_size << "-way horizontal model parallel is enabled";
|
||||
|
|
@ -101,8 +102,6 @@ std::vector<std::unique_ptr<GraphTransformer>> GeneratePreTrainingTransformers(
|
|||
} break;
|
||||
|
||||
case TransformerLevel::Level2: {
|
||||
// Put ReshapeFusion as level-2 optimization after all level-1 graph rewriters are run.
|
||||
transformers.emplace_back(onnxruntime::make_unique<ReshapeFusion>(compatible_eps));
|
||||
rule_transformer =
|
||||
onnxruntime::make_unique<RuleBasedGraphTransformer>(optimizer_utils::GenerateRuleBasedTransformerName(level),
|
||||
compatible_eps);
|
||||
|
|
|
|||
Loading…
Reference in a new issue