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118 lines
3.8 KiB
118 lines
3.8 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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#pragma once
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#include <cmath>
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#include <memory>
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#include <vector>
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/tensor_util.h"
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#include "paddle/fluid/platform/device_context.h"
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename DeviceContext, typename T>
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struct TransposeNormal {
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// for dims >= 7 situation
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void operator()(const DeviceContext& context, const framework::Tensor& in,
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framework::Tensor* out, const std::vector<int>& axis);
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};
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template <typename DeviceContext, typename T, int Rank>
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struct Transpose {
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void operator()(const DeviceContext& context, const framework::Tensor& in,
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framework::Tensor* out, const std::vector<int>& axis);
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};
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template <typename DeviceContext, typename T>
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struct SetConstant {
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void operator()(const DeviceContext& context, framework::Tensor* tensor,
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T num);
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};
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template <typename Place>
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void set_constant_with_place(const platform::DeviceContext& context,
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framework::Tensor* tensor, float value);
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void set_constant(const platform::DeviceContext& context,
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framework::Tensor* tensor, float value);
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template <typename DeviceContext, typename T>
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struct RowwiseAdd {
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void operator()(const DeviceContext& context, const framework::Tensor& input,
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const framework::Tensor& vec, framework::Tensor* output);
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};
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template <typename DeviceContext, typename T>
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struct ElementwiseAddTo {
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// dst = dst + src
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void operator()(DeviceContext* ctx, const framework::Tensor& src,
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framework::Tensor* dst);
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};
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template <typename DeviceContext, typename T>
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struct ColwiseSum {
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void operator()(const DeviceContext& context, const framework::Tensor& input,
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framework::Tensor* vec);
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};
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template <typename DeviceContext, typename T>
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struct RowwiseSum {
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void operator()(const DeviceContext& context, const framework::Tensor& input,
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framework::Tensor* vec);
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};
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template <typename DeviceContext, typename T>
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struct RowwiseMean {
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void operator()(const DeviceContext& context, const framework::Tensor& input,
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framework::Tensor* vec);
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};
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#ifdef PADDLE_WITH_XPU
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template <typename U>
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struct TensorSetConstantXPU {
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TensorSetConstantXPU(framework::Tensor* tensor, U 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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int dev_id = -1;
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xpu_current_device(&dev_id);
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if (dev_id >= 64) {
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// if dev_id >= 64, the device is a simulator device, -64 to get real
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// dev_id
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dev_id -= 64;
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}
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auto xpu = platform::XPUPlace(dev_id);
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auto* begin = tensor_->mutable_data<T>(xpu);
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int numel = tensor_->numel();
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std::unique_ptr<T[]> data_cpu(new T[numel]);
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std::fill(data_cpu.get(), data_cpu.get() + numel, static_cast<T>(value_));
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memory::Copy(xpu, begin, platform::CPUPlace(),
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static_cast<void*>(data_cpu.get()), numel * sizeof(T));
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}
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framework::Tensor* tensor_;
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U value_;
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};
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#endif
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} // namespace math
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} // namespace operators
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} // namespace paddle
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