hedaoyuan
8 years ago
parent
3ce974b94e
commit
3c0aa0cc34
@ -0,0 +1,44 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#pragma once
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#include "ConvOp.h"
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namespace paddle {
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/*
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* imData = [input_channels, input_height, input_width]
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* colData = [input_channels, filter_height, filter_width,
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* output_height, output_width]
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*/
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template <DeviceType Device, class T>
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class Im2ColFunctor {
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public:
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void operator()(const T* imData,
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int inputChannels,
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int inputHeight,
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int inputWidth,
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int filterHeight,
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int filterWidth,
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int strideHeight,
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int strideWidth,
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int paddingHeight,
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int paddingWidth,
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int outputHeight,
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int outputWidth,
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T* colData);
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};
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} // namespace paddle
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@ -0,0 +1,93 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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 "ConvOp.h"
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#include "GemmConvOp.h"
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namespace paddle {
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template<class T>
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__global__
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void im2col(const T* data_im, int numOuts, int height, int width,
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int blockH, int blockW,
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int strideH, int strideW,
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int paddingH, int paddingW,
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int height_col, int width_col,
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T* data_col) {
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int index =
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(blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
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if (index < numOuts) {
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int w_out = index % width_col;
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index /= width_col;
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int h_out = index % height_col;
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int channel_in = index / height_col;
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int channel_out = channel_in * blockH * blockW;
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int h_in = h_out * strideH;
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int w_in = w_out * strideW;
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data_col += (channel_out * height_col + h_out) * width_col + w_out;
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for (int i = 0; i < blockH; ++i) {
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for (int j = 0; j < blockW; ++j) {
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int rIdx = int(h_in+i);
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int cIdx = int(w_in+j);
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if ((rIdx-(int)paddingH) >= (int)height ||
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(rIdx-(int)paddingH) < 0 ||
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(cIdx-(int)paddingW) >= (int)width ||
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(cIdx-(int)paddingW) < 0) {
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*data_col = 0;
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} else {
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rIdx = rIdx + channel_in*height - paddingH;
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cIdx = cIdx - paddingW;
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*data_col = data_im[rIdx* width + cIdx];
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}
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data_col += height_col * width_col;
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}
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}
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}
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}
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template <class T>
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class Im2ColFunctor<DEVICE_TYPE_GPU, T> {
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public:
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void operator()(const T* imData,
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int inputChannels,
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int inputHeight,
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int inputWidth,
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int filterHeight,
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int filterWidth,
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int strideHeight,
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int strideWidth,
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int paddingHeight,
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int paddingWidth,
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int outputHeight,
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int outputWidth,
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T* colData) {
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int numKernels = inputChannels * outputHeight * outputWidth;
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int blocks = (numKernels + 1024 -1) / 1024;
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int blockX = 512;
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int blockY = (blocks + 512 - 1) / 512;
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dim3 threads(1024, 1);
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dim3 grid(blockX, blockY);
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im2col<T><<< grid, threads, 0, STREAM_DEFAULT >>>
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(imData, numKernels, inputHeight, inputWidth, filterHeight, filterWidth,
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strideHeight, strideWidth, paddingHeight, paddingWidth,
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outputHeight, outputWidth, colData);
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CHECK_SYNC("Im2ColFunctor GPU failed");
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}
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};
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template class Im2ColFunctor<DEVICE_TYPE_GPU, float>;
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template class Im2ColFunctor<DEVICE_TYPE_GPU, double>;
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} // namespace paddle
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@ -0,0 +1,102 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#pragma once
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#include "paddle/math/MathFunctions.h"
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namespace paddle {
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// TODO(hedaoyuan): Since the hl_matrix_mul interface does not conform to the
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// cblas_dgemm interface's parameter format, it is necessary to introduce
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// GemmFunctor as a new interface. Later, when considering the implementation
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// of MatMulFunction, we need to consider the reconstruction of hl_matrix_mul
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// interface.
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template <DeviceType Device, class T>
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class GemmFunctor {
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public:
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void operator()(const int M,
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const int N,
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const int K,
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const T alpha,
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const T* A,
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const int lda,
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const T* B,
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const int ldb,
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const T beta,
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T* C,
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const int ldc);
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};
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template <class T>
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class GemmFunctor<DEVICE_TYPE_CPU, T> {
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public:
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void operator()(const int M,
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const int N,
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const int K,
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const T alpha,
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const T* A,
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const int lda,
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const T* B,
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const int ldb,
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const T beta,
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T* C,
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const int ldc) {
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gemm<T>(CblasNoTrans,
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CblasNoTrans,
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M,
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N,
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K,
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alpha,
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A,
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lda,
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B,
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ldb,
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beta,
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C,
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ldc);
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}
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};
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template <class T>
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class GemmFunctor<DEVICE_TYPE_GPU, T> {
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public:
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void operator()(const int M,
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const int N,
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const int K,
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const T alpha,
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const T* A,
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const int lda,
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const T* B,
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const int ldb,
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const T beta,
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T* C,
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const int ldc) {
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hl_matrix_mul((T*)A,
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HPPL_OP_N,
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(T*)B,
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HPPL_OP_N,
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C,
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M,
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N,
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K,
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alpha,
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beta,
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lda,
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ldb,
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ldc);
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}
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};
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} // namespace paddle
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