// 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/cumprod_kernel.h" #include #include #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/complex_functors.h" #include "paddle/phi/kernels/funcs/cumprod.h" namespace phi { template void CumprodKernel(const Context& dev_ctx, const DenseTensor& input, int dim, DenseTensor* out) { const DenseTensor* x = &input; auto* x_data = x->data(); auto* out_data = dev_ctx.template Alloc(out); DDim shape = x->dims(); size_t outer_dim = 1; size_t mid_dim = 1; size_t inner_dim = 1; GetCumprodDimInfo(shape, dim, &outer_dim, &mid_dim, &inner_dim); if (shape.size() == 0) { phi::Copy(dev_ctx, input, dev_ctx.GetPlace(), false, out); return; } for (size_t i = 0; i < outer_dim; i++) { for (size_t j = 0; j < mid_dim; j++) { for (size_t k = 0; k < inner_dim; k++) { size_t pos = i * mid_dim * inner_dim + j * inner_dim + k; if (j == 0) { out_data[pos] = x_data[pos]; } else { out_data[pos] = out_data[pos - inner_dim] * x_data[pos]; } } } } } } // namespace phi PD_REGISTER_KERNEL(cumprod, CPU, ALL_LAYOUT, phi::CumprodKernel, float, double, int, int64_t, phi::dtype::complex, phi::dtype::complex) {}