// Copyright (c) 2023 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/prelu_kernel.h" #include "paddle/phi/backends/xpu/enforce_xpu.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void PReluKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& alpha, const std::string& data_format, const std::string& mode, DenseTensor* out) { using XPUType = typename XPUTypeTrait::Type; const T* x_ptr = x.data(); const T* alpha_ptr = alpha.data(); T* y_ptr = dev_ctx.template Alloc(out); if (out && out->numel() == 0) { return; } auto x_dim = x.dims(); auto x_rank = x_dim.size(); std::vector x_shape(x_rank); if (x_rank == 0) { x_shape = std::vector({1}); } else { x_shape = vectorize(x_dim); } // mode = 0: channel_nchw, xshape = {n, c, h, w}, alpha_shape = {c} // mode = 1, channel_nhwc, xshape = {n, h, w, c}, alpha_shape = {c} // mode = 2, elementwise, deprecated in Paddle 2.x // mode = 3, alpha_shape = {} or {1} int xpu_mode = 0; if (mode == "channel") { if (data_format == "NCHW") { xpu_mode = 0; if (x_rank == 2) { // special case for NC shape, use channel last mode xpu_mode = 1; } } else { // NHWC, channel last xpu_mode = 1; } } else if (mode == "element") { xpu_mode = 2; } else if (mode == "all") { xpu_mode = 3; } else { PADDLE_THROW(common::errors::InvalidArgument( "Expected mode of prelu kernel is 'channel' or 'all', But got " "unsupported mode: %s.", mode)); } int r = xpu::prelu(dev_ctx.x_context(), reinterpret_cast(x_ptr), reinterpret_cast(alpha_ptr), reinterpret_cast(y_ptr), x_shape, xpu_mode); PADDLE_ENFORCE_XDNN_SUCCESS(r, "prelu"); } } // namespace phi PD_REGISTER_KERNEL( prelu, XPU, ALL_LAYOUT, phi::PReluKernel, float, phi::float16) {}