// 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/one_hot_kernel.h" #include "paddle/phi/backends/xpu/enforce_xpu.h" #include "paddle/phi/backends/xpu/xpu_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/utils/data_type.h" namespace phi { template struct OneHotV2OpFunctor { const DenseTensor* in_; DenseTensor* out_; int depth_; const Context& ctx_; OneHotV2OpFunctor(const DenseTensor* in, DenseTensor* out, int depth, const Context& ctx) : in_(in), out_(out), depth_(depth), ctx_(ctx) {} template void apply() const { auto* p_in_data = in_->data(); auto numel = in_->numel(); auto* p_out_data = ctx_.template Alloc(out_); int r = xpu::one_hot( ctx_.x_context(), p_in_data, p_out_data, numel, depth_, 1.0, 0.0); PADDLE_ENFORCE_XDNN_SUCCESS(r, "one_hot"); } }; template void OneHotRawKernel(const Context& dev_ctx, const DenseTensor& x, const Scalar& depth, DataType dtype, bool allow_out_of_range, DenseTensor* out) { auto depth_v = depth.to(); auto out_dims = out->dims(); if (out_dims[out_dims.size() - 1] == -1) { out_dims[out_dims.size() - 1] = depth_v; out->Resize(out_dims); } phi::VisitDataType(dtype, OneHotV2OpFunctor(&x, out, depth_v, dev_ctx)); } } // namespace phi PD_REGISTER_KERNEL( one_hot_raw, XPU, ALL_LAYOUT, phi::OneHotRawKernel, int, int64_t) {}