// Copyright (c) 2018 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. #ifdef PADDLE_WITH_XPU #include #include #include "paddle/fluid/operators/one_hot_op.h" namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; using Tensor = framework::Tensor; template class OneHotV2XPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* in = context.Input("X"); auto* out = context.Output("Out"); int depth = context.Attr("depth"); if (context.HasInput("depth_tensor")) { auto* depth_tensor = context.Input("depth_tensor"); auto* depth_data = depth_tensor->data(); if (platform::is_xpu_place(depth_tensor->place())) { xpu_memcpy(static_cast(&depth), static_cast(depth_data), sizeof(int32_t), XPU_DEVICE_TO_HOST); } else { depth = depth_data[0]; } auto out_dims = out->dims(); out_dims[out_dims.size() - 1] = depth; out->Resize(out_dims); } auto& dev_ctx = context.template device_context(); int len = in->numel(); int ret = xpu::one_hot(dev_ctx.x_context(), in->data(), out->mutable_data(context.GetPlace()), len, depth, 1.0, 0.0); PADDLE_ENFORCE_EQ(ret, XPU_SUCCESS, platform::errors::External( "XPU one_hot kernel return wrong value[%d %s]", ret, XPUAPIErrorMsg[ret])); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_XPU_KERNEL( one_hot_v2, ops::OneHotV2XPUKernel, ops::OneHotV2XPUKernel); #endif