wehub-resource-sync
135 lines
5.1 KiB
C++
135 lines
5.1 KiB
C++
// 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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// limitations under the License.
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#include "paddle/phi/kernels/compare_kernel.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/elementwise_base.h"
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#include "paddle/phi/kernels/impl/compare_kernel_impl.h"
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namespace phi {
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template <typename T,
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typename Context,
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typename Functor,
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typename InverseFunctor>
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inline void CompareKernelImpl(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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DenseTensor* out) {
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dev_ctx.template Alloc<bool>(out);
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if (x.dims().size() >= y.dims().size()) {
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funcs::ElementwiseCompute<Functor, T, bool>(
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dev_ctx, x, y, Functor(), out, axis);
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} else {
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funcs::ElementwiseCompute<InverseFunctor, T, bool>(
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dev_ctx, x, y, InverseFunctor(), out, axis);
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}
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}
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template <typename T,
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typename Context,
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typename Functor,
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typename InverseFunctor>
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inline void InplaceCompareKernelImpl(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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DenseTensor* out) {
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auto x_origin = x;
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out->set_type(DataType::BOOL);
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dev_ctx.template Alloc<bool>(out);
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if (x_origin.dims().size() >= y.dims().size()) {
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funcs::ElementwiseCompute<Functor, T, bool>(
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dev_ctx, x_origin, y, Functor(), out, axis);
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} else {
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funcs::ElementwiseCompute<InverseFunctor, T, bool>(
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dev_ctx, x_origin, y, InverseFunctor(), out, axis);
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}
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}
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template <typename T, typename Context, typename Functor>
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inline void CompareAllKernelImpl(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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bool* out_data = dev_ctx.template Alloc<bool>(out);
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if (x.dims() != y.dims()) {
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out_data[0] = false;
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} else if (x.numel() == 0) { // shape equal and numel is 0, return true
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out_data[0] = true;
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} else {
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DenseTensor tmp;
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tmp.Resize(x.dims());
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dev_ctx.template Alloc<bool>(&tmp);
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if (x.numel() == 1 && y.numel() == 1) {
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bool* tmp_data = tmp.data<bool>();
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tmp_data[0] = Functor()(x.data<T>()[0], y.data<T>()[0]);
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} else {
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funcs::ElementwiseCompute<Functor, T, bool>(
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dev_ctx, x, y, Functor(), &tmp, 0);
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}
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auto tmp_flat = EigenVector<bool>::Flatten(tmp);
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auto out_es = EigenScalar<bool>::From(*out);
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auto& place = *dev_ctx.eigen_device();
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auto reduce_dim = Eigen::array<int, 1>({{0}});
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out_es.device(place) = tmp_flat.all(reduce_dim);
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(equal_all,
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CPU,
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ALL_LAYOUT,
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phi::EqualAllKernel,
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bool,
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int,
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int64_t,
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float,
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double) {
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
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}
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#define PD_REGISTER_COMPLEX_COMPARE_KERNEL(name, func) \
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PD_REGISTER_KERNEL(name, \
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CPU, \
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ALL_LAYOUT, \
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phi::func##Kernel, \
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bool, \
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int, \
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uint8_t, \
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int8_t, \
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int16_t, \
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int64_t, \
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phi::complex64, \
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phi::complex128, \
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float, \
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double, \
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phi::float16, \
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phi::bfloat16) { \
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kernel->OutputAt(0).SetDataType(phi::DataType::BOOL); \
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}
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(less_than, LessThan)
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(less_equal, LessEqual)
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(greater_than, GreaterThan)
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(greater_equal, GreaterEqual)
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(equal, Equal)
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PD_REGISTER_COMPLEX_COMPARE_KERNEL(not_equal, NotEqual)
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