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92 lines
2.8 KiB
92 lines
2.8 KiB
/* Copyright (c) 2019 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/eigen.h"
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#include "paddle/fluid/operators/elementwise/elementwise_op.h"
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#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
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#include "paddle/fluid/operators/math/blas.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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struct FloorDivFunctor {
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inline HOSTDEVICE T operator()(T a, T b) const {
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#ifdef __CUDA_ARCH__
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if (b == 0) {
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printf("Error: Divide by zero encounter in floor_divide\n");
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asm("trap;");
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}
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#else
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if (b == 0)
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PADDLE_THROW(platform::errors::InvalidArgument(
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"Divide by zero encounter in floor_divide"));
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#endif
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return static_cast<T>(std::trunc(a / b));
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}
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};
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template <typename T>
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struct InverseFloorDivFunctor {
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inline HOSTDEVICE T operator()(T a, T b) const {
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#ifdef __CUDA_ARCH__
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if (a == 0) {
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printf("Error: Divide by zero encounter in floor_divide\n");
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asm("trap;");
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}
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#else
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if (a == 0)
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PADDLE_THROW(platform::errors::InvalidArgument(
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"Divide by zero encounter in floor_divide"));
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#endif
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return static_cast<T>(std::trunc(b / a));
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}
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};
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template <typename DeviceContext, typename T>
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void elementwise_floor_div(const framework::ExecutionContext &ctx,
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const framework::Tensor *x,
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const framework::Tensor *y, framework::Tensor *z) {
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int axis = ctx.Attr<int>("axis");
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auto x_dims = x->dims();
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auto y_dims = y->dims();
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if (x_dims.size() >= y_dims.size()) {
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ElementwiseComputeEx<FloorDivFunctor<T>, DeviceContext, T>(
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ctx, x, y, axis, FloorDivFunctor<T>(), z);
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} else {
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ElementwiseComputeEx<InverseFloorDivFunctor<T>, DeviceContext, T>(
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ctx, x, y, axis, InverseFloorDivFunctor<T>(), z);
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}
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}
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template <typename DeviceContext, typename T>
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class ElementwiseFloorDivKernel : 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 *x = ctx.Input<framework::LoDTensor>("X");
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auto *y = ctx.Input<framework::LoDTensor>("Y");
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auto *z = ctx.Output<framework::LoDTensor>("Out");
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z->mutable_data<T>(ctx.GetPlace());
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// dtype of x and y is int64 or int32
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elementwise_floor_div<DeviceContext, T>(ctx, x, y, z);
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}
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};
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} // namespace operators
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} // namespace paddle
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