wehub-resource-sync
56 lines
2.0 KiB
C++
56 lines
2.0 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/clip_by_norm_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/backends/xpu/xpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void ClipByNormKernel(const Context& dev_ctx,
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const DenseTensor& in,
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float max_norm,
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DenseTensor* output) {
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auto input = ∈
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dev_ctx.template Alloc<T>(output);
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PADDLE_ENFORCE_NOT_NULL(input,
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common::errors::InvalidArgument(
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"Input(X) of ClipByNormOp should not be null. "
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"Please check if it is created correctly."));
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const auto& x_dims = input->dims();
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std::vector<int64_t> xshape(x_dims.size());
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std::vector<int64_t> rdims(x_dims.size());
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for (int i = 0; i < x_dims.size(); i++) {
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xshape[i] = x_dims[i];
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rdims[i] = i;
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}
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int r = xpu::clip_by_norm<T>(dev_ctx.x_context(),
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input->data<T>(),
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output->data<T>(),
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max_norm,
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xshape,
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rdims);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "clip_by_norm");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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clip_by_norm, XPU, ALL_LAYOUT, phi::ClipByNormKernel, float) {}
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