// 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/clip_kernel.h" #include "glog/logging.h" #include "paddle/phi/backends/xpu/enforce_xpu.h" #include "paddle/phi/backends/xpu/xpu_context.h" #include "paddle/phi/backends/xpu/xpu_header.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void ClipKernel(const Context& dev_ctx, const DenseTensor& x, const Scalar& min, const Scalar& max, DenseTensor* out) { auto max_ = max.to(); auto min_ = min.to(); PADDLE_ENFORCE_LE( min_, max_, errors::InvalidArgument("max should be greater than or equal to min. " "But received min = %f, max = %f", static_cast(min_), static_cast(max_))); dev_ctx.template Alloc(out); if (out && out->numel() == 0) return; using XPUDataType = typename XPUTypeTrait::Type; auto x_data = reinterpret_cast(x.data()); auto out_data = reinterpret_cast(out->data()); int r = xpu::clamp(dev_ctx.x_context(), x_data, out_data, x.numel(), static_cast(min_), static_cast(max_)); PADDLE_ENFORCE_XDNN_SUCCESS(r, "clamp"); } } // namespace phi PD_REGISTER_KERNEL(clip, XPU, ALL_LAYOUT, phi::ClipKernel, float, phi::float16, phi::bfloat16, int64_t, int) {}