wehub-resource-sync
76 lines
2.7 KiB
C++
76 lines
2.7 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/enforce.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/full_kernel.h"
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#include "paddle/phi/kernels/softmax_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void KLDivLossKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& label,
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const std::string& reduction,
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bool log_target,
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DenseTensor* out) {
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using XPUType = typename XPUTypeTrait<T>::Type;
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dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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if (x.numel() == 0) {
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Full<T, Context>(dev_ctx, out->dims(), NAN, out);
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return;
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}
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int r = 0;
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if (log_target) {
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xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
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XPUType* label_exp = RAII_GUARD.alloc_l3_or_gm<XPUType>(label.numel());
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PADDLE_ENFORCE_XDNN_NOT_NULL(label_exp);
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r = xpu::exp(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(label.data<T>()),
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label_exp,
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label.numel());
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "exp");
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r = xpu::kldiv_loss(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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reinterpret_cast<const XPUType*>(label_exp),
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reinterpret_cast<XPUType*>(out->data<T>()),
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out->numel());
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "kldiv_loss");
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} else {
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r = xpu::kldiv_loss(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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reinterpret_cast<const XPUType*>(label.data<T>()),
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reinterpret_cast<XPUType*>(out->data<T>()),
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out->numel());
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "kldiv_loss");
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}
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if ("none" != reduction) {
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PADDLE_THROW(common::errors::Unavailable(
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"Not supported reduction [%s] in kldiv_loss", reduction));
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(kldiv_loss, XPU, ALL_LAYOUT, phi::KLDivLossKernel, float) {}
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