// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "paddle/phi/kernels/compare_kernel.h" #include "paddle/phi/core/dense_tensor.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/elementwise_base.h" #include "paddle/phi/kernels/impl/compare_kernel_impl.h" namespace phi { template inline void CompareKernelImpl(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out) { dev_ctx.template Alloc(out); if (x.dims().size() >= y.dims().size()) { funcs::ElementwiseCompute( dev_ctx, x, y, Functor(), out, axis); } else { funcs::ElementwiseCompute( dev_ctx, x, y, InverseFunctor(), out, axis); } } template inline void InplaceCompareKernelImpl(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out) { auto x_origin = x; out->set_type(DataType::BOOL); dev_ctx.template Alloc(out); if (x_origin.dims().size() >= y.dims().size()) { funcs::ElementwiseCompute( dev_ctx, x_origin, y, Functor(), out, axis); } else { funcs::ElementwiseCompute( dev_ctx, x_origin, y, InverseFunctor(), out, axis); } } template inline void CompareAllKernelImpl(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out) { bool* out_data = dev_ctx.template Alloc(out); if (x.dims() != y.dims()) { out_data[0] = false; } else if (x.numel() == 0) { // shape equal and numel is 0, return true out_data[0] = true; } else { DenseTensor tmp; tmp.Resize(x.dims()); dev_ctx.template Alloc(&tmp); if (x.numel() == 1 && y.numel() == 1) { bool* tmp_data = tmp.data(); tmp_data[0] = Functor()(x.data()[0], y.data()[0]); } else { funcs::ElementwiseCompute( dev_ctx, x, y, Functor(), &tmp, 0); } auto tmp_flat = EigenVector::Flatten(tmp); auto out_es = EigenScalar::From(*out); auto& place = *dev_ctx.eigen_device(); auto reduce_dim = Eigen::array({{0}}); out_es.device(place) = tmp_flat.all(reduce_dim); } } } // namespace phi PD_REGISTER_KERNEL(equal_all, CPU, ALL_LAYOUT, phi::EqualAllKernel, bool, int, int64_t, float, double) { kernel->OutputAt(0).SetDataType(phi::DataType::BOOL); } #define PD_REGISTER_COMPLEX_COMPARE_KERNEL(name, func) \ PD_REGISTER_KERNEL(name, \ CPU, \ ALL_LAYOUT, \ phi::func##Kernel, \ bool, \ int, \ uint8_t, \ int8_t, \ int16_t, \ int64_t, \ phi::complex64, \ phi::complex128, \ float, \ double, \ phi::float16, \ phi::bfloat16) { \ kernel->OutputAt(0).SetDataType(phi::DataType::BOOL); \ } PD_REGISTER_COMPLEX_COMPARE_KERNEL(less_than, LessThan) PD_REGISTER_COMPLEX_COMPARE_KERNEL(less_equal, LessEqual) PD_REGISTER_COMPLEX_COMPARE_KERNEL(greater_than, GreaterThan) PD_REGISTER_COMPLEX_COMPARE_KERNEL(greater_equal, GreaterEqual) PD_REGISTER_COMPLEX_COMPARE_KERNEL(equal, Equal) PD_REGISTER_COMPLEX_COMPARE_KERNEL(not_equal, NotEqual)