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Merge pull request #1516 from zhanghonggeng/ignore_test_1
support conv3d_transpose uniform & fix some tests
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| // Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| #include "paddle2onnx/mapper/nn/conv3d_transpose.h" | ||
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| namespace paddle2onnx { | ||
| REGISTER_PIR_MAPPER(conv3d_transpose, Conv3dTransposeMapper) | ||
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| int32_t Conv3dTransposeMapper::GetMinOpsetVersion(bool verbose) { | ||
| if (data_format_ != "NCHW" && data_format_ != "NHWC") { | ||
| Error() << "[ERROR] only support NCDHW or NDHWC format for " | ||
| "conv3d_transpose " | ||
| << std::endl; | ||
| return -1; | ||
| } | ||
| return 7; | ||
| } | ||
|
|
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| void Conv3dTransposeMapper::Opset7() { | ||
| auto kernel_info = GetInput("filter"); | ||
| auto input_info = GetInput("x"); | ||
| auto output_info = GetOutput("out"); | ||
|
|
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| auto input = helper_->AutoCast( | ||
| input_info[0].name, input_info[0].dtype, P2ODataType::FP32); | ||
| if (data_format_ == "NHWC") { | ||
| input = helper_->Transpose(input, {0, 4, 1, 2, 3}); // NDHWC -> NCDHW | ||
| } | ||
|
|
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| auto kernel = helper_->AutoCast( | ||
| kernel_info[0].name, kernel_info[0].dtype, P2ODataType::FP32); | ||
|
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| auto node = helper_->MakeNode("ConvTranspose", {input, kernel}); | ||
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| std::vector<int64_t> kernel_shape = {kernel_info[0].shape[2], | ||
| kernel_info[0].shape[3], | ||
| kernel_info[0].shape[4]}; | ||
| AddAttribute(node, "kernel_shape", kernel_shape); | ||
|
|
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| AddAttribute(node, "dilations", dilations_); | ||
| AddAttribute(node, "strides", strides_); | ||
| AddAttribute(node, "group", groups_); | ||
|
|
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| if (padding_algorithm_ == "SAME") { | ||
| AddAttribute(node, "auto_pad", "SAME_UPPER"); | ||
| } else if (padding_algorithm_ == "VALID") { | ||
| AddAttribute(node, "auto_pad", "VALID"); | ||
| } else { | ||
| std::vector<int64_t> paddings; | ||
| if (paddings_.size() == 3) { | ||
| paddings.insert(paddings.begin(), paddings_.begin(), paddings_.end()); | ||
| paddings.insert(paddings.begin(), paddings_.begin(), paddings_.end()); | ||
| } else { | ||
| std::vector<int64_t> index = {0, 2, 4, 1, 3, 5}; | ||
| for (auto& i : index) { | ||
| paddings.push_back(paddings_[i]); | ||
| } | ||
| } | ||
| AddAttribute(node, "pads", paddings); | ||
| } | ||
|
|
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| if (!output_padding_.empty()) { | ||
| AddAttribute(node, "output_padding", output_padding_); | ||
| } | ||
|
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| auto output = node->output(0); | ||
| if (data_format_ == "NHWC") { | ||
| output = helper_->Transpose(output, {0, 2, 3, 4, 1}); // NCDHW -> NDHWC | ||
| } | ||
| helper_->AutoCast( | ||
| output, output_info[0].name, P2ODataType::FP32, output_info[0].dtype); | ||
| } | ||
| } // namespace paddle2onnx |
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| @@ -0,0 +1,59 @@ | ||
| // Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| #pragma once | ||
| #include <string> | ||
| #include <vector> | ||
|
|
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| #include "paddle2onnx/mapper/mapper.h" | ||
|
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| namespace paddle2onnx { | ||
|
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| class Conv3dTransposeMapper : public Mapper { | ||
| public: | ||
| Conv3dTransposeMapper(const PaddlePirParser& p, | ||
| OnnxHelper* helper, | ||
| int64_t i, | ||
| bool c) | ||
| : Mapper(p, helper, i, c) { | ||
| GetAttr("groups", &groups_); | ||
| GetAttr("dilations", &dilations_); | ||
| GetAttr("strides", &strides_); | ||
| GetAttr("paddings", &paddings_); | ||
| GetAttr("padding_algorithm", &padding_algorithm_); | ||
| GetAttr("data_format", &data_format_); | ||
|
|
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| if (HasAttr("output_padding")) { | ||
| GetAttr("output_padding", &output_padding_); | ||
| } | ||
| if (HasAttr("output_size")) { | ||
| GetAttr("output_size", &output_size_); | ||
| } | ||
| } | ||
|
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| int32_t GetMinOpsetVersion(bool verbose) override; | ||
| void Opset7() override; | ||
|
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| private: | ||
| std::vector<int64_t> dilations_; | ||
| std::vector<int64_t> strides_; | ||
| std::vector<int64_t> paddings_; | ||
| std::vector<int64_t> output_padding_; | ||
| std::vector<int64_t> output_size_; | ||
| std::string padding_algorithm_; | ||
| std::string data_format_; | ||
| int64_t groups_; | ||
| }; | ||
|
|
||
| } // namespace paddle2onnx |
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| @@ -0,0 +1,55 @@ | ||
| // Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
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| #include "paddle2onnx/mapper/tensor/uniform.h" | ||
|
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| namespace paddle2onnx { | ||
| REGISTER_PIR_MAPPER(uniform, UniformMapper) | ||
|
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| int32_t UniformMapper::GetMinOpsetVersion(bool verbose) { return 7; } | ||
|
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| void UniformMapper::Opset7() { | ||
| auto output_info = GetOutput("out"); | ||
| auto shape_info = GetInput("shape"); | ||
| auto min_info = GetInput("min"); | ||
| auto max_info = GetInput("max"); | ||
|
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| if (min_info[0].Rank() != 0 || max_info[0].Rank() != 0) { | ||
| Error() << "[ERROR] min/max must be scalar tensors for op " | ||
| "uniform " | ||
| << std::endl; | ||
| } | ||
| std::vector<float> min_val{0.0f}, max_val{1.0f}; | ||
| bool is_min_const = | ||
| helper_->TryGetTensorValue<float>(min_info[0].name, &min_val); | ||
| bool is_max_const = | ||
| helper_->TryGetTensorValue<float>(max_info[0].name, &max_val); | ||
|
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| std::vector<int64_t> shape_values; | ||
| helper_->TryGetTensorValue<int64_t>(shape_info[0].name, &shape_values); | ||
|
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| auto onnx_dtype = GetOnnxDtype(dtype_); | ||
|
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| auto random_node = | ||
| helper_->MakeNode("RandomUniform", {}, {output_info[0].name}); | ||
|
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| AddAttribute(random_node, "shape", shape_values); | ||
| AddAttribute(random_node, "low", min_val[0]); | ||
| AddAttribute(random_node, "high", max_val[0]); | ||
| AddAttribute(random_node, "dtype", static_cast<int64_t>(onnx_dtype)); | ||
| if (seed_ != 0) { | ||
| AddAttribute(random_node, "seed", static_cast<float>(seed_)); | ||
| } | ||
| } | ||
| } // namespace paddle2onnx |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,39 @@ | ||
| // Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| #pragma once | ||
| #include <string> | ||
| #include <vector> | ||
|
|
||
| #include "paddle2onnx/mapper/mapper.h" | ||
|
|
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| namespace paddle2onnx { | ||
|
|
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| class UniformMapper : public Mapper { | ||
| public: | ||
| UniformMapper(const PaddlePirParser& p, OnnxHelper* helper, int64_t i, bool c) | ||
| : Mapper(p, helper, i, c) { | ||
| GetAttr("dtype", &dtype_); | ||
| GetAttr("seed", &seed_); | ||
| } | ||
|
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| int32_t GetMinOpsetVersion(bool verbose) override; | ||
| void Opset7() override; | ||
|
|
||
| private: | ||
| int64_t dtype_; | ||
| int64_t seed_; | ||
| }; | ||
|
|
||
| } // namespace paddle2onnx |
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