mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-26 19:52:38 +00:00
cf19c3697d
### Description
Run clang-format in CI. Formatted all c/c++, objective-c/c++ files.
Excluded
```
'onnxruntime/core/mlas/**',
'onnxruntime/contrib_ops/cuda/bert/tensorrt_fused_multihead_attention/**',
```
because they contain assembly or is data heavy
### Motivation and Context
Coding style consistency
87 lines
2.6 KiB
C++
87 lines
2.6 KiB
C++
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#include "core/graph/model.h"
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namespace onnxruntime {
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namespace test {
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namespace modelbuilder {
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// Shape: a wrapper to build a TensorShapeProto
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struct Shape {
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ONNX_NAMESPACE::TensorShapeProto value;
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// construct a shape with given constant dimensions
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Shape(std::initializer_list<int> dims) {
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for (auto d : dims) {
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auto dim = value.add_dim();
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dim->set_dim_value(d);
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}
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}
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// construct a shape with given symbolic dimensions
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Shape(std::initializer_list<std::string> dims) {
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for (auto d : dims) {
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auto dim = value.add_dim();
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dim->set_dim_param(d);
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}
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}
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};
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// Type: a wrapper to build a TypeProto
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struct Type {
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ONNX_NAMESPACE::TypeProto value;
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// construct a float-tensor-type
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Type() {
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value.mutable_tensor_type()->set_elem_type(ONNX_NAMESPACE::TensorProto_DataType_FLOAT);
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}
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// construct a float-tensor-type with given constant dimensions
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Type(std::initializer_list<int> dims) {
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value.mutable_tensor_type()->set_elem_type(ONNX_NAMESPACE::TensorProto_DataType_FLOAT);
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auto p_shape = value.mutable_tensor_type()->mutable_shape();
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for (auto d : dims) {
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auto dim = p_shape->add_dim();
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dim->set_dim_value(d);
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}
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}
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// construct a float-tensor-type with given symbolic dimensions
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Type(std::initializer_list<std::string> symbolic_dims) {
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value.mutable_tensor_type()->set_elem_type(ONNX_NAMESPACE::TensorProto_DataType_FLOAT);
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auto p_shape = value.mutable_tensor_type()->mutable_shape();
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for (auto d : symbolic_dims) {
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auto dim = p_shape->add_dim();
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dim->set_dim_param(d);
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}
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}
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static Type MakeSequence(const ONNX_NAMESPACE::TypeProto& element_proto) {
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ONNX_NAMESPACE::TypeProto proto;
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proto.mutable_sequence_type()->mutable_elem_type()->CopyFrom(element_proto);
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return Type(std::move(proto));
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}
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static Type MakeMap(ONNX_NAMESPACE::TensorProto_DataType dtype, const ONNX_NAMESPACE::TypeProto& value_proto) {
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ONNX_NAMESPACE::TypeProto proto;
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auto& mut_map = *proto.mutable_map_type();
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mut_map.set_key_type(static_cast<int32_t>(dtype));
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mut_map.mutable_value_type()->CopyFrom(value_proto);
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return Type(std::move(proto));
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}
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static Type MakeOptional(const ONNX_NAMESPACE::TypeProto& contained_proto) {
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ONNX_NAMESPACE::TypeProto proto;
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proto.mutable_optional_type()->mutable_elem_type()->CopyFrom(contained_proto);
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return Type(std::move(proto));
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}
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private:
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explicit Type(ONNX_NAMESPACE::TypeProto type_proto) : value(std::move(type_proto)) {}
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};
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} // namespace modelbuilder
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} // namespace test
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} // namespace onnxruntime
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