wehub-resource-sync
69 lines
2.8 KiB
C++
69 lines
2.8 KiB
C++
// Copyright (c) 2022 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/momentum_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.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 MomentumDenseKernel(const Context& dev_ctx,
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const DenseTensor& param,
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const DenseTensor& grad,
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const DenseTensor& velocity,
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const DenseTensor& learning_rate,
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const optional<DenseTensor>& master_param,
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float mu,
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bool use_nesterov,
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const std::string& regularization_method,
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float regularization_coeff,
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bool multi_precision,
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float rescale_grad,
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DenseTensor* param_out,
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DenseTensor* velocity_out,
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DenseTensor* master_param_out) {
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using XPUType = typename XPUTypeTrait<T>::Type;
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dev_ctx.template Alloc<T>(param_out);
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dev_ctx.template Alloc<T>(velocity_out);
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auto* lr = learning_rate.data<float>();
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if (regularization_method != "l2_decay") {
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// only support l2_decay
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regularization_coeff = 0.0f;
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}
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// int momentum(Context* xpu_ctx, const T* param, const T* velocity, const T*
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// grad, T* param_out, T* velocity_out, int len, const float* lr, int
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// use_nesterov, float mu, float l2_weight_decay);
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int r = xpu::momentum(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(param.data<T>()),
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reinterpret_cast<const XPUType*>(velocity.data<T>()),
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reinterpret_cast<const XPUType*>(grad.data<T>()),
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reinterpret_cast<XPUType*>(param_out->data<T>()),
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reinterpret_cast<XPUType*>(velocity_out->data<T>()),
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param_out->numel(),
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lr,
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use_nesterov,
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static_cast<T>(mu),
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regularization_coeff);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "momentum");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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momentum, XPU, ALL_LAYOUT, phi::MomentumDenseKernel, float, phi::float16) {}
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