1. support channel last in BatchNorm*d (#27875) 2. fix a bug in batch_norm_op cuda kernel by extracting ResizeToChannelFist(Last), TransToChannelFirst(Last) to operators/layer_utils.hswt-req
Feiyu Chan
4 years ago
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GitHub
parent
947b75284f
commit
2e845182d9
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// Copyright (c) 2020 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 <algorithm>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename DeviceContext, typename T>
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inline void ResizeToChannelFirst(const framework::ExecutionContext& context,
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const Tensor* input,
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Tensor* transformed_input) {
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int dim = input->dims().size() - 2;
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if (dim == 3) {
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// input
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[4];
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in_dims_vec[2] = input->dims()[1];
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in_dims_vec[3] = input->dims()[2];
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in_dims_vec[4] = input->dims()[3];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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} else if (dim == 2) {
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// input
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[3];
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in_dims_vec[2] = input->dims()[1];
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in_dims_vec[3] = input->dims()[2];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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} else if (dim == 1) {
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[2];
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in_dims_vec[2] = input->dims()[1];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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}
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}
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template <typename DeviceContext, typename T>
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inline void ResizeToChannelLast(const framework::ExecutionContext& context,
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const Tensor* input,
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Tensor* transformed_input) {
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int dim = input->dims().size() - 2;
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if (dim == 3) {
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// input
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[2];
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in_dims_vec[2] = input->dims()[3];
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in_dims_vec[3] = input->dims()[4];
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in_dims_vec[4] = input->dims()[1];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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} else if (dim == 2) {
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// input
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[2];
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in_dims_vec[2] = input->dims()[3];
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in_dims_vec[3] = input->dims()[1];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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} else if (dim == 1) {
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transformed_input->Resize(input->dims());
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auto in_dims_vec = framework::vectorize(input->dims());
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in_dims_vec[1] = input->dims()[2];
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in_dims_vec[2] = input->dims()[1];
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transformed_input->Resize(framework::make_ddim(in_dims_vec));
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transformed_input->mutable_data<T>(context.GetPlace());
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}
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}
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template <typename DeviceContext, typename T>
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inline void TransToChannelFirst(const framework::ExecutionContext& context,
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const Tensor* input,
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Tensor* transformed_input) {
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VLOG(5) << "Why am I called?";
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int dim = input->dims().size() - 2;
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if (dim == 3) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 4, 1, 2, 3};
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math::Transpose<DeviceContext, T, 5> trans5;
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trans5(dev_ctx, *input, transformed_input, axis);
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} else if (dim == 2) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 3, 1, 2};
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math::Transpose<DeviceContext, T, 4> trans4;
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trans4(dev_ctx, *input, transformed_input, axis);
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} else if (dim == 1) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 2, 1};
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math::Transpose<DeviceContext, T, 3> trans3;
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trans3(dev_ctx, *input, transformed_input, axis);
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}
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}
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template <typename DeviceContext, typename T>
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inline void TransToChannelLast(const framework::ExecutionContext& context,
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const Tensor* input, Tensor* transformed_input) {
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int dim = input->dims().size() - 2;
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if (dim == 3) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 2, 3, 4, 1};
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math::Transpose<DeviceContext, T, 5> trans5;
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trans5(dev_ctx, *input, transformed_input, axis);
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} else if (dim == 2) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 2, 3, 1};
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math::Transpose<DeviceContext, T, 4> trans4;
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trans4(dev_ctx, *input, transformed_input, axis);
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} else if (dim == 1) {
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auto& dev_ctx = context.template device_context<DeviceContext>();
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std::vector<int> axis{0, 2, 1};
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math::Transpose<DeviceContext, T, 3> trans3;
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trans3(dev_ctx, *input, transformed_input, axis);
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}
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}
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} // namespace operators
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} // namespace paddle
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