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145 lines
5.4 KiB
145 lines
5.4 KiB
/* Copyright (c) 2016 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 "paddle/fluid/operators/math/math_function.h"
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#include <vector>
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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/operators/math/math_function_impl.h"
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#include "paddle/fluid/platform/float16.h"
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namespace paddle {
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namespace operators {
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namespace math {
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using float16 = paddle::platform::float16;
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template struct SetConstant<platform::CPUDeviceContext, platform::float16>;
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template struct SetConstant<platform::CPUDeviceContext, float>;
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template struct SetConstant<platform::CPUDeviceContext, double>;
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template struct SetConstant<platform::CPUDeviceContext, int>;
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template struct SetConstant<platform::CPUDeviceContext, int64_t>;
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template struct SetConstant<platform::CPUDeviceContext, bool>;
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template struct SetConstant<platform::CPUDeviceContext, uint8_t>;
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#define DEFINE_CPU_TRANS(RANK) \
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template struct Transpose<platform::CPUDeviceContext, platform::float16, \
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RANK>; \
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template struct Transpose<platform::CPUDeviceContext, float, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, double, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, int, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, int64_t, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, bool, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, int16_t, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, uint8_t, RANK>; \
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template struct Transpose<platform::CPUDeviceContext, int8_t, RANK>;
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DEFINE_CPU_TRANS(1);
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DEFINE_CPU_TRANS(2);
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DEFINE_CPU_TRANS(3);
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DEFINE_CPU_TRANS(4);
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DEFINE_CPU_TRANS(5);
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DEFINE_CPU_TRANS(6);
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struct TensorSetConstantCPU {
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TensorSetConstantCPU(framework::Tensor* tensor, float value)
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: tensor_(tensor), value_(value) {}
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template <typename T>
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void apply() const {
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auto cpu = platform::CPUPlace();
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auto* begin = tensor_->mutable_data<T>(cpu);
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std::fill(begin, begin + tensor_->numel(), static_cast<T>(value_));
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}
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framework::Tensor* tensor_;
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float value_;
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};
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template <>
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void set_constant_with_place<platform::CPUPlace>(
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const platform::DeviceContext& context, framework::Tensor* tensor,
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float value) {
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framework::VisitDataType(framework::ToDataType(tensor->type()),
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TensorSetConstantCPU(tensor, value));
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}
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template <>
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void set_constant_with_place<platform::CUDAPinnedPlace>(
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const platform::DeviceContext& context, framework::Tensor* tensor,
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float value) {
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framework::VisitDataType(framework::ToDataType(tensor->type()),
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TensorSetConstantCPU(tensor, value));
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}
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struct TensorSetConstantWithPlace : public boost::static_visitor<void> {
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TensorSetConstantWithPlace(const platform::DeviceContext& context,
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framework::Tensor* tensor, float value)
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: context_(context), tensor_(tensor), value_(value) {}
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template <typename Place>
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void operator()(Place place) const {
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set_constant_with_place<Place>(context_, tensor_, value_);
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}
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const platform::DeviceContext& context_;
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framework::Tensor* tensor_;
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float value_;
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};
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void set_constant(const platform::DeviceContext& context,
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framework::Tensor* tensor, float value) {
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TensorSetConstantWithPlace func(context, tensor, value);
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#ifdef PADDLE_WITH_CUDA
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tensor->place().apply_visitor(func);
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#else
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func(platform::CPUPlace());
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#endif
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}
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template <typename T>
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struct RowwiseAdd<platform::CPUDeviceContext, T> {
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void operator()(const platform::CPUDeviceContext& context,
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const framework::Tensor& input,
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const framework::Tensor& vector, framework::Tensor* output) {
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auto in_dims = input.dims();
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auto size = input.numel() / in_dims[0];
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PADDLE_ENFORCE_EQ(vector.numel(), size);
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PADDLE_ENFORCE_EQ(output->dims(), in_dims);
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auto in = framework::EigenMatrix<T>::From(input);
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auto vec = framework::EigenVector<T>::Flatten(vector);
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auto out = framework::EigenMatrix<T>::From(*output);
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for (int64_t i = 0; i < in_dims[0]; ++i) {
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out.chip(i, 0) = in.chip(i, 0) + vec;
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}
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}
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};
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template struct RowwiseAdd<platform::CPUDeviceContext, float>;
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template struct RowwiseAdd<platform::CPUDeviceContext, double>;
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template struct ColwiseSum<platform::CPUDeviceContext, float>;
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template struct ColwiseSum<platform::CPUDeviceContext, double>;
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template struct ColwiseSum<platform::CPUDeviceContext, int>;
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template struct ColwiseSum<platform::CPUDeviceContext, int64_t>;
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template struct RowwiseSum<platform::CPUDeviceContext, float>;
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template struct RowwiseSum<platform::CPUDeviceContext, double>;
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template struct RowwiseMean<platform::CPUDeviceContext, float>;
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template struct RowwiseMean<platform::CPUDeviceContext, double>;
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} // namespace math
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} // namespace operators
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} // namespace paddle
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