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102 lines
3.4 KiB
102 lines
3.4 KiB
/* Copyright (c) 2020 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 "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/platform/for_range.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class TrilTriuCompute {
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public:
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HOSTDEVICE TrilTriuCompute(const T* in, const int diagonal, const bool lower,
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const int64_t H, const int64_t W, T* out)
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: in_(in), diagonal_(diagonal), lower_(lower), H_(H), W_(W), out_(out) {}
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HOSTDEVICE void operator()(int64_t idx) {
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const int64_t row = (idx / W_) % H_;
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const int64_t col = idx % W_;
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const bool mask =
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lower_ ? (col - row > diagonal_) : (col - row < diagonal_);
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out_[idx] = mask ? static_cast<T>(0) : in_[idx];
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}
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private:
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const T* in_;
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const int diagonal_;
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const bool lower_;
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const int64_t H_;
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const int64_t W_;
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T* out_;
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};
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template <typename DeviceContext, typename T>
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class TrilTriuOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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const auto* x = context.Input<framework::Tensor>("X");
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const auto* x_data = x->data<T>();
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auto* out = context.Output<framework::Tensor>("Out");
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auto* out_data = out->mutable_data<T>(context.GetPlace());
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const int diagonal = context.Attr<int>("diagonal");
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const bool lower = context.Attr<bool>("lower");
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const auto& dims = x->dims();
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const auto H = dims[dims.size() - 2];
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const auto W = dims[dims.size() - 1];
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platform::ForRange<DeviceContext> for_range(
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context.template device_context<DeviceContext>(),
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static_cast<size_t>(x->numel()));
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paddle::operators::TrilTriuCompute<T> tril_triu_computer(
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x_data, diagonal, lower, H, W, out_data);
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for_range(tril_triu_computer);
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}
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};
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template <typename DeviceContext, typename T>
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class TrilTriuGradOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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const auto* d_out =
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context.Input<framework::Tensor>(framework::GradVarName("Out"));
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const auto* dout_data = d_out->data<T>();
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auto* d_x = context.Output<framework::Tensor>(framework::GradVarName("X"));
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auto* dx_data = d_x->mutable_data<T>(context.GetPlace());
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const int diagonal = context.Attr<int>("diagonal");
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const bool lower = context.Attr<bool>("lower");
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const auto& dims = d_out->dims();
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const auto H = dims[dims.size() - 2];
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const auto W = dims[dims.size() - 1];
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platform::ForRange<DeviceContext> for_range(
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context.template device_context<DeviceContext>(),
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static_cast<size_t>(d_out->numel()));
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paddle::operators::TrilTriuCompute<T> tril_triu_grad_computer(
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dout_data, diagonal, lower, H, W, dx_data);
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for_range(tril_triu_grad_computer);
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}
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};
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} // namespace operators
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} // namespace paddle
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