nhzlx
6 years ago
parent
463f88a75c
commit
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/inference/anakin/convert/affine_channel.h"
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#include <algorithm>
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#include <string>
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#include <vector>
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using anakin::graph::GraphGlobalMem;
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using anakin::AK_FLOAT;
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using anakin::Precision;
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using anakin::saber::NV;
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using anakin::saber::X86;
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using anakin::saber::Shape;
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using anakin::PBlock;
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using anakin::PTuple;
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namespace paddle {
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namespace inference {
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namespace anakin {
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void AffineChannelOpConverter::operator()(
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const framework::proto::OpDesc &op, const framework::BlockDesc &block_desc,
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const framework::Scope &scope, bool test_mode) {
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framework::OpDesc op_desc(op, nullptr);
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PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
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PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
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auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
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auto input_name = op_desc.Input("X").front();
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auto output_name = op_desc.Output("Out").front();
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// Copy the Scale to CPUPlace and get the pointer.
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auto *scale_v = scope.FindVar(op_desc.Input("Scale").front());
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PADDLE_ENFORCE_NOT_NULL(scale_v);
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auto *scale_t = scale_v->GetMutable<framework::LoDTensor>();
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std::unique_ptr<framework::LoDTensor> scale_tensor(
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new framework::LoDTensor());
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scale_tensor->Resize(scale_t->dims());
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TensorCopySync((*scale_t), platform::CPUPlace(), scale_tensor.get());
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// Copy the Bias to CPUPlace and get the pointer.
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auto *bias_v = scope.FindVar(op_desc.Input("Bias").front());
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PADDLE_ENFORCE_NOT_NULL(bias_v);
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auto *bias_t = bias_v->GetMutable<framework::LoDTensor>();
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std::unique_ptr<framework::LoDTensor> bias_tensor(new framework::LoDTensor());
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bias_tensor->Resize(bias_t->dims());
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TensorCopySync((*bias_t), platform::CPUPlace(), bias_tensor.get());
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engine_->AddOp(op_name, "AffineChannel", {input_name}, {output_name});
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// Generate the Scale parameter of Anakin.
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auto scale_shape = framework::vectorize2int(scale_t->dims());
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while (scale_shape.size() < 4) {
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scale_shape.insert(scale_shape.begin(), 1);
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}
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Shape anakin_scale_shape(scale_shape);
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auto *weight1 = GraphGlobalMem<NV>::Global().template new_block<AK_FLOAT>(
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anakin_scale_shape);
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float *scale_cpu_data =
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static_cast<float *>(weight1->h_tensor().mutable_data());
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std::copy_n(scale_tensor->data<float>(), scale_tensor->numel(),
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scale_cpu_data);
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weight1->d_tensor().set_shape(anakin_scale_shape);
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weight1->d_tensor().copy_from(weight1->h_tensor());
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engine_->AddOpAttr(op_name, "weight_1", *weight1);
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// Generate the Bias parameter of Anakin.
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auto bias_shape = framework::vectorize2int(bias_t->dims());
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while (bias_shape.size() < 4) {
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bias_shape.insert(bias_shape.begin(), 1);
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}
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Shape anakin_bias_shape(bias_shape);
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auto *weight2 = GraphGlobalMem<NV>::Global().template new_block<AK_FLOAT>(
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anakin_bias_shape);
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float *bias_cpu_data =
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static_cast<float *>(weight2->h_tensor().mutable_data());
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std::copy_n(bias_tensor->data<float>(), bias_tensor->numel(), bias_cpu_data);
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weight2->d_tensor().set_shape(anakin_bias_shape);
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weight2->d_tensor().copy_from(weight2->h_tensor());
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engine_->AddOpAttr(op_name, "weight_2", *weight2);
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}
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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REGISTER_ANAKIN_OP_CONVERTER(affine_channel, AffineChannelOpConverter);
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <memory>
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#include "paddle/fluid/inference/anakin/convert/op_converter.h"
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namespace paddle {
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namespace inference {
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namespace anakin {
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class AffineChannelOpConverter : public AnakinOpConverter {
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public:
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AffineChannelOpConverter() = default;
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virtual void operator()(const framework::proto::OpDesc &op,
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const framework::BlockDesc &block_desc,
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const framework::Scope &scope,
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bool test_mode) override;
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virtual ~AffineChannelOpConverter() {}
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private:
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};
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/inference/anakin/convert/roi_align.h"
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#include <algorithm>
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#include <map>
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using anakin::graph::GraphGlobalMem;
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using anakin::AK_FLOAT;
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using anakin::saber::NV;
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using anakin::saber::Shape;
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namespace paddle {
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namespace inference {
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namespace anakin {
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void RoiAlignOpConverter::operator()(const framework::proto::OpDesc &op,
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const framework::BlockDesc &block_desc,
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const framework::Scope &scope,
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bool test_mode) {
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framework::OpDesc op_desc(op, nullptr);
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PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
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PADDLE_ENFORCE_EQ(op_desc.Input("ROIs").size(), 1);
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PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
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auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
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auto input_x_name = op_desc.Input("X").front();
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auto input_rois_name = op_desc.Input("ROIs").front();
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auto output_name = op_desc.Output("Out").front();
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auto spatial_scale = boost::get<float>(op_desc.GetAttr("spatial_scale"));
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auto pooled_height = boost::get<int>(op_desc.GetAttr("pooled_height"));
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auto pooled_width = boost::get<int>(op_desc.GetAttr("pooled_width"));
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auto sampling_ratio = boost::get<int>(op_desc.GetAttr("sampling_ratio"));
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engine_->AddOp(op_name, "RoiAlign", {input_x_name, input_rois_name},
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{output_name});
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engine_->AddOpAttr(op_name, "spatial_scale", spatial_scale);
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engine_->AddOpAttr(op_name, "pooled_height", pooled_height);
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engine_->AddOpAttr(op_name, "pooled_width", pooled_width);
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engine_->AddOpAttr(op_name, "sampling_ratio", sampling_ratio);
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}
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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REGISTER_ANAKIN_OP_CONVERTER(roi_align, RoiAlignOpConverter);
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <map>
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#include <string>
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#include "paddle/fluid/inference/anakin/convert/op_converter.h"
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namespace paddle {
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namespace inference {
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namespace anakin {
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class RoiAlignOpConverter : public AnakinOpConverter {
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public:
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RoiAlignOpConverter() = default;
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virtual void operator()(const framework::proto::OpDesc &op,
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const framework::BlockDesc &block_desc,
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const framework::Scope &scope,
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bool test_mode) override;
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virtual ~RoiAlignOpConverter() {}
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};
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <gtest/gtest.h>
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#include "paddle/fluid/inference/anakin/convert/affine_channel.h"
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#include "paddle/fluid/inference/anakin/convert/op_converter.h"
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#include "paddle/fluid/inference/anakin/convert/ut_helper.h"
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namespace paddle {
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namespace inference {
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namespace anakin {
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TEST(affine_channel, native) {
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// Declare the difference between the inputs.
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std::unordered_set<std::string> parameters({"scale", "bias"});
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framework::Scope scope;
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AnakinConvertValidation validator(parameters, &scope);
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validator.DeclInputVar("x", {1, 3, 5, 2});
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validator.DeclOutputVar("out", {1, 3, 5, 2});
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validator.DeclParamVar("scale", {1, 3, 1, 1});
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validator.DeclParamVar("bias", {1, 3, 1, 1});
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// Prepare Op descriptions.
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framework::OpDesc desc;
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desc.SetType("affine_channel");
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desc.SetInput("X", {"x"});
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desc.SetInput("Bias", {"bias"});
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desc.SetInput("Scale", {"scale"});
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desc.SetOutput("Out", {"out"});
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// Layout must be explicitly specified here as NCHW.
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desc.SetAttr("data_layout", std::string("NCHW"));
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validator.SetOp(*desc.Proto());
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validator.Execute(1);
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}
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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USE_OP(affine_channel);
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USE_ANAKIN_CONVERTER(affine_channel);
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