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77 lines
3.1 KiB
77 lines
3.1 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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#ifdef PADDLE_WITH_XPU
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#include "paddle/fluid/operators/log_loss_op.h"
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#include <memory>
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T, typename AttrType = T>
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class LogLossXPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* predict = ctx.Input<Tensor>("Predicted");
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auto* labels = ctx.Input<Tensor>("Labels");
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auto* loss = ctx.Output<Tensor>("Loss");
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auto epsilon = static_cast<T>(ctx.Attr<AttrType>("epsilon"));
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loss->mutable_data<T>(ctx.GetPlace());
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int n = predict->numel();
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auto& dev_ctx = ctx.template device_context<DeviceContext>();
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int r =
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xpu::log_loss_fwd(dev_ctx.x_context(), n, epsilon, predict->data<T>(),
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labels->data<T>(), loss->data<T>());
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PADDLE_ENFORCE_EQ(
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r, xpu::Error_t::SUCCESS,
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platform::errors::External(
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"XPU log_loss kernel return wrong value[%d], please check whether "
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"Baidu Kunlun Card is properly installed.",
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r));
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}
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};
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template <typename DeviceContext, typename T, typename AttrType = T>
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class LogLossGradXPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* predict = ctx.Input<Tensor>("Predicted");
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auto* labels = ctx.Input<Tensor>("Labels");
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auto* dloss = ctx.Input<Tensor>(framework::GradVarName("Loss"));
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auto* dpred = ctx.Output<Tensor>(framework::GradVarName("Predicted"));
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if (!dpred) {
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return;
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}
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auto epsilon = static_cast<T>(ctx.Attr<AttrType>("epsilon"));
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dpred->mutable_data<T>(ctx.GetPlace());
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int n = predict->numel();
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auto& dev_ctx = ctx.template device_context<DeviceContext>();
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int r = xpu::log_loss_bwd(dev_ctx.x_context(), n, epsilon,
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predict->data<T>(), labels->data<T>(),
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dloss->data<T>(), dpred->data<T>());
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PADDLE_ENFORCE_EQ(
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r, xpu::Error_t::SUCCESS,
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platform::errors::External(
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"XPU log_loss kernel return wrong value[%d], please check whether "
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"Baidu Kunlun Card is properly installed.",
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r));
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_XPU_KERNEL(
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log_loss, ops::LogLossXPUKernel<paddle::platform::XPUDeviceContext, float>);
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REGISTER_OP_XPU_KERNEL(
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log_loss_grad,
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ops::LogLossGradXPUKernel<paddle::platform::XPUDeviceContext, float>);
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#endif
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