wehub-resource-sync
59 lines
2.0 KiB
C++
59 lines
2.0 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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#pragma once
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#include <vector>
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/kernels/empty_kernel.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace phi {
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template <typename T, typename Context>
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void WarprnntGradKernel(const Context& dev_ctx,
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const DenseTensor& input UNUSED,
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const DenseTensor& input_lengths UNUSED,
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const DenseTensor& warprnntgrad,
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const DenseTensor& loss_grad,
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int blank UNUSED,
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float fastemit_lambda UNUSED,
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DenseTensor* input_grad) {
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dev_ctx.template Alloc<T>(input_grad);
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int64_t B = warprnntgrad.dims()[0];
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int64_t Tmax = warprnntgrad.dims()[1];
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int64_t Umax = warprnntgrad.dims()[2];
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int64_t D = warprnntgrad.dims()[3];
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// (B,)
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auto loss_grad_e = EigenTensor<T, 1>::From(loss_grad);
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// (B, T, U, D)
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auto warprnntgrad_e = EigenTensor<T, 4>::From(warprnntgrad);
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auto acts_grad_e = EigenTensor<T, 4>::From(*input_grad);
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Eigen::DSizes<int64_t, 4> grad_shape(B, 1, 1, 1);
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Eigen::DSizes<int64_t, 4> bcast(1, Tmax, Umax, D);
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auto acts_g =
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warprnntgrad_e * loss_grad_e.reshape(grad_shape).broadcast(bcast).eval();
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auto* place = dev_ctx.eigen_device();
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acts_grad_e.device(*place) = acts_g;
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}
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} // namespace phi
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