wehub-resource-sync
136 lines
5.7 KiB
Plaintext
136 lines
5.7 KiB
Plaintext
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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// limitation
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#include "paddle/phi/kernels/logical_kernel.h"
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#ifdef PADDLE_WITH_XPU_KP
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#include "paddle/phi/backends/xpu/xpu_context.h"
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#else
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#endif
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/broadcast_function.h"
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#include "paddle/phi/kernels/funcs/logical_functor.h"
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namespace phi {
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template <typename T, typename Context, typename Functor>
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void LogicalKernelImpl(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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DenseTensor* out) {
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dev_ctx.template Alloc<bool>(out);
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Functor binary_func;
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std::vector<const DenseTensor*> ins = {&x, &y};
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std::vector<DenseTensor*> outs = {out};
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funcs::BroadcastKernel<bool>(dev_ctx, ins, &outs, binary_func);
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}
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template <typename T, typename Context, typename Functor>
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void InplaceLogicalKernelImpl(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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DenseTensor* out) {
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auto x_origin = x;
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dev_ctx.template Alloc<bool>(out);
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out->set_type(phi::DataType::BOOL);
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Functor binary_func;
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std::vector<const DenseTensor*> ins = {&x_origin, &y};
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std::vector<DenseTensor*> outs = {out};
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funcs::BroadcastKernel<bool>(dev_ctx, ins, &outs, binary_func);
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}
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#define DEFINE_LOGICAL_BINARY_KERNEL(type) \
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template <typename T, typename Context> \
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void Logical##type##Kernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& y, \
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DenseTensor* out) { \
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if (out->IsSharedWith(x)) { \
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InplaceLogicalKernelImpl<T, Context, funcs::Logical##type##Functor<T>>( \
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dev_ctx, x, y, out); \
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} else { \
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LogicalKernelImpl<T, Context, funcs::Logical##type##Functor<T>>( \
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dev_ctx, x, y, out); \
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} \
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}
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DEFINE_LOGICAL_BINARY_KERNEL(And)
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DEFINE_LOGICAL_BINARY_KERNEL(Or)
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DEFINE_LOGICAL_BINARY_KERNEL(Xor)
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#undef DEFINE_LOGICAL_BINARY_KERNEL
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template <typename T, typename Context>
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void LogicalNotKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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if (!out->IsSharedWith(x)) {
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dev_ctx.template Alloc<bool>(out);
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funcs::LogicalNotFunctor<T> unary_func;
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std::vector<const DenseTensor*> ins = {&x};
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std::vector<DenseTensor*> outs = {out};
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funcs::BroadcastKernel<bool>(dev_ctx, ins, &outs, unary_func);
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} else {
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auto x_origin = x;
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out->set_type(phi::DataType::BOOL);
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dev_ctx.template Alloc<bool>(out);
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funcs::LogicalNotFunctor<T> unary_func;
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std::vector<const DenseTensor*> ins = {&x_origin};
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std::vector<DenseTensor*> outs = {out};
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funcs::BroadcastKernel<bool>(dev_ctx, ins, &outs, unary_func);
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}
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}
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} // namespace phi
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#ifdef PADDLE_WITH_XPU_KP
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PD_REGISTER_KERNEL(logical_and, KPS, ALL_LAYOUT, phi::LogicalAndKernel, int) {
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
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}
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PD_REGISTER_KERNEL(logical_or, KPS, ALL_LAYOUT, phi::LogicalOrKernel, int) {
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
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}
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PD_REGISTER_KERNEL(logical_not, KPS, ALL_LAYOUT, phi::LogicalNotKernel, int) {
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
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}
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PD_REGISTER_KERNEL(logical_xor, KPS, ALL_LAYOUT, phi::LogicalXorKernel, int) {
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
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}
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#else
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#define REGISTER_LOGICAL_CUDA_KERNEL(logical_and, func_type) \
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PD_REGISTER_KERNEL(logical_and, \
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KPS, \
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ALL_LAYOUT, \
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phi::Logical##func_type##Kernel, \
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float, \
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phi::float16, \
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phi::bfloat16, \
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double, \
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bool, \
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int64_t, \
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int, \
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int8_t, \
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phi::complex64, \
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phi::complex128, \
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int16_t) { \
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL); \
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}
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REGISTER_LOGICAL_CUDA_KERNEL(logical_and, And)
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REGISTER_LOGICAL_CUDA_KERNEL(logical_or, Or)
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REGISTER_LOGICAL_CUDA_KERNEL(logical_not, Not)
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REGISTER_LOGICAL_CUDA_KERNEL(logical_xor, Xor)
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#endif
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