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Optimize ERF with MKL math function #5
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f0c7264
mkl_func test with erf&log op, build success~
pengxin99 9311777
fix lint and build issues
TaoLv a79f7db
Try to add support to sparse array
juliusshufan 015fd0a
fix build
TaoLv 495ce36
Merge branch 'master' of https://github.com/apache/incubator-mxnet in…
TaoLv 672be6a
add functions
TaoLv c69a25c
Fix review comments
juliusshufan 2c5c20c
remove unecessary code
juliusshufan b1b6355
Update test case
juliusshufan f96c34a
minor fix
juliusshufan 06c51e9
move the position of MKL_Compute
juliusshufan acd7b56
Merge pull request #6 from juliusshufan/erf
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you under the Apache License, Version 2.0 (the | ||
| * "License"); you may not use this file except in compliance | ||
| * with the License. You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, | ||
| * software distributed under the License is distributed on an | ||
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| * KIND, either express or implied. See the License for the | ||
| * specific language governing permissions and limitations | ||
| * under the License. | ||
| */ | ||
|
|
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| /*! | ||
| * Copyright (c) 2018 by Contributors | ||
| * \file mkl_functions-inl.h | ||
| * \brief | ||
| * \author | ||
| */ | ||
| #ifndef MXNET_OPERATOR_MKL_FUNCTIONS_INL_H_ | ||
| #define MXNET_OPERATOR_MKL_FUNCTIONS_INL_H_ | ||
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| #if MSHADOW_USE_MKL == 1 | ||
| #include "mkl.h" | ||
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| namespace mxnet { | ||
| namespace op { | ||
| namespace mkl_func { | ||
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| MSHADOW_XINLINE | ||
| static bool check_size(const size_t n) { | ||
| const size_t MKL_INT_MAX = (sizeof(MKL_INT) == sizeof(int)) ? INT_MAX : LLONG_MAX; | ||
| return (n <= MKL_INT_MAX); | ||
| } | ||
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| MSHADOW_XINLINE | ||
| static bool check_type(const int t) { | ||
| return (t == mshadow::kFloat32 || t == mshadow::kFloat64); | ||
| } | ||
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| #define MXNET_MKL_UNARY_MATH_FUNC(name, func) \ | ||
| struct name { \ | ||
| MSHADOW_XINLINE static void Vectorize(const index_t n, const float *src, float *dst) { \ | ||
| vs##func(static_cast<MKL_INT>(n), src, dst); \ | ||
| } \ | ||
| MSHADOW_XINLINE static void Vectorize(const index_t n, const double *src, double *dst) { \ | ||
| vd##func(static_cast<MKL_INT>(n), src, dst); \ | ||
| } \ | ||
| }; | ||
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| #define MXNET_MKL_BINARY_MATH_FUNC(name, func) \ | ||
| struct name { \ | ||
| MSHADOW_XINLINE static void Vectorize(const index_t n, \ | ||
| const float *a, \ | ||
| const float *b, \ | ||
| float *c) { \ | ||
| vs##func(static_cast<MKL_INT>(n), a, b, c); \ | ||
| } \ | ||
| MSHADOW_XINLINE static void Vectorize(const index_t n, \ | ||
| const double *a, \ | ||
| const double *b, \ | ||
| double *c) { \ | ||
| vd##func(static_cast<MKL_INT>(n), a, b, c); \ | ||
| } \ | ||
| }; | ||
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| MXNET_MKL_UNARY_MATH_FUNC(erf, Erf); | ||
| MXNET_MKL_UNARY_MATH_FUNC(exp, Exp); | ||
| MXNET_MKL_UNARY_MATH_FUNC(exp2, Exp2); | ||
| MXNET_MKL_UNARY_MATH_FUNC(exp10, Exp10); | ||
| MXNET_MKL_UNARY_MATH_FUNC(expm1, Expm1); | ||
| MXNET_MKL_UNARY_MATH_FUNC(log, Ln); | ||
| MXNET_MKL_UNARY_MATH_FUNC(log2, Log2); | ||
| MXNET_MKL_UNARY_MATH_FUNC(log10, Log10); | ||
| MXNET_MKL_UNARY_MATH_FUNC(log1p, Log1p); | ||
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| MXNET_MKL_UNARY_MATH_FUNC(sin, Sin); | ||
| MXNET_MKL_UNARY_MATH_FUNC(cos, Cos); | ||
| MXNET_MKL_UNARY_MATH_FUNC(tan, Tan); | ||
| MXNET_MKL_UNARY_MATH_FUNC(asin, Asin); | ||
| MXNET_MKL_UNARY_MATH_FUNC(acos, Acos); | ||
| MXNET_MKL_UNARY_MATH_FUNC(atan, Atan); | ||
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| MXNET_MKL_UNARY_MATH_FUNC(sinh, Sinh); | ||
| MXNET_MKL_UNARY_MATH_FUNC(cosh, Cosh); | ||
| MXNET_MKL_UNARY_MATH_FUNC(tanh, Tanh); | ||
| MXNET_MKL_UNARY_MATH_FUNC(asinh, Asinh); | ||
| MXNET_MKL_UNARY_MATH_FUNC(acosh, Acosh); | ||
| MXNET_MKL_UNARY_MATH_FUNC(atanh, Atanh); | ||
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| MXNET_MKL_UNARY_MATH_FUNC(sqrt, Sqrt); | ||
| MXNET_MKL_UNARY_MATH_FUNC(abs, Abs); | ||
| MXNET_MKL_UNARY_MATH_FUNC(cbrt, Cbrt); | ||
| MXNET_MKL_UNARY_MATH_FUNC(round, Round); | ||
| MXNET_MKL_UNARY_MATH_FUNC(ceil, Ceil); | ||
| MXNET_MKL_UNARY_MATH_FUNC(floor, Floor); | ||
| MXNET_MKL_UNARY_MATH_FUNC(trunc, Trunc); | ||
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| MXNET_MKL_UNARY_MATH_FUNC(lgamma, LGamma); | ||
| MXNET_MKL_UNARY_MATH_FUNC(tgamma, TGamma); | ||
| MXNET_MKL_UNARY_MATH_FUNC(square, Sqr); | ||
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| MXNET_MKL_BINARY_MATH_FUNC(add, Add); | ||
| MXNET_MKL_BINARY_MATH_FUNC(sub, Sub); | ||
| MXNET_MKL_BINARY_MATH_FUNC(mul, Mul); | ||
| MXNET_MKL_BINARY_MATH_FUNC(pow, Pow); | ||
| MXNET_MKL_BINARY_MATH_FUNC(hypot, Hypot); | ||
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| template <typename DType> | ||
| MSHADOW_XINLINE static void sub_(index_t n, DType *in, DType b, DType *dst) { | ||
| for (index_t i = 0; i < n; i++) | ||
| dst[i] = in[i] - b; | ||
| } | ||
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| template <typename DType> | ||
| MSHADOW_XINLINE static void div_(index_t n, DType *in, DType b, DType *dst) { | ||
| for (index_t i = 0; i < n; i++) | ||
| dst[i] = in[i] / b; | ||
| } | ||
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| template <typename DType> | ||
| MSHADOW_XINLINE static void sum_(index_t n, DType *in, DType *dst) { | ||
| // dst[0] = cblas_sasum(n, in, 1); | ||
| DType sum = 0.0f; | ||
| for (index_t i = 0; i < n; i++) | ||
| sum += in[i]; | ||
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| dst[0] = sum; | ||
| } | ||
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| template <typename DType> | ||
| MSHADOW_XINLINE static void max_(int n, DType * __restrict__ in, DType *dst) { | ||
| dst[0] = in[0]; | ||
| for (int i = 1; i < n; i++) | ||
| dst[0] = (dst[0] < in[i]) ? in[i] : dst[0]; | ||
| } | ||
|
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| // LayerNorm on the last dimension | ||
| template <typename DType> | ||
| MSHADOW_XINLINE static void LayerNormLastDim(const index_t m, | ||
| const index_t n, | ||
| const DType *a, | ||
| const DType *b, | ||
| const DType *ws, | ||
| const DType *gamma, | ||
| const DType *beta, | ||
| const DType *mean, | ||
| const DType *var, | ||
| const DType eps) { | ||
| #pragma omp parallel for | ||
| for (index_t i = 0; i < m; i++) { | ||
| DType* in_offset = a + i * n; | ||
| DType* out_offset = b + i * n; | ||
| DType* ws_offset = ws + i * n; | ||
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| sum_(n, in_offset, &(mean[i])); | ||
| mean[i] /= n; | ||
| sub_(n, in_offset, mean[i], out_offset); | ||
| square(n, out_offset, ws_offset); | ||
| sum_(n, ws_offset, &(var[i])); | ||
| var[i] = sqrt(var[i] / n + eps); | ||
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| mul(n, out_offset, gamma, out_offset); | ||
| div_(n, out_offset, var[i], out_offset); | ||
| add(n, out_offset, beta, out_offset); | ||
| } | ||
| } | ||
|
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| // softmax on the last dimension | ||
| template <typename DType> | ||
| MSHADOW_XINLINE static void SoftmaxLastDim(const index_t m, | ||
| const index_t n, | ||
| const DType *a, | ||
| const DType *b) { | ||
| #pragma omp paralle for | ||
| for (index_t i = 0; i < m; i++) { | ||
| DType* in_offset = a + i * n; | ||
| DType* out_offset = b + i * n; | ||
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| exp(n, in_offset, out_offset); | ||
| float sum = 0.0f; | ||
| sum_(n, out_offset, &sum); | ||
| div_(n, out_offset, sum, out_offset); | ||
| } | ||
| } | ||
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| template <typename DType> | ||
| MSHADOW_XINLINE static void LogSoftmaxLastDim(const index_t m, | ||
| const index_t n, | ||
| const DType *a, | ||
| const DType *b) { | ||
| #pragma parallel for | ||
| for (index_t i = 0; i < m; i++) { | ||
| DType* in_offset = a + i * n; | ||
| DType* out_offset = b + i * n; | ||
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| DType b, logsum; | ||
| max_(n, in_offset, &b); | ||
| sub_(n, in_offset, b, out_offset); | ||
| exp(n, out_offset, out_offset); | ||
| sum_(n, out_offset, &logsum); | ||
| logsum = b + logf(logsum); | ||
| sub_(n, in_offset, logsum, out_offset); | ||
| } | ||
| } | ||
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| } // namespace mkl_func | ||
| } // namespace op | ||
| } // namespace mxnet | ||
| #endif // MSHADOW_USE_MKL == 1 | ||
| #endif // MXNET_OPERATOR_MKL_FUNCTIONS_INL_H_ |
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I have not set USE_MKL before. Just curious: is blas=MKL also tested in mxnet CI?
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MSHADOW_USE_MKLis widely used in mshadow and mxnet to indicate MKL is used as BLAS library. Yes,USE_BLAS=mklis built and tested in CI:https://github.com/apache/incubator-mxnet/blob/master/ci/docker/runtime_functions.sh#L375
https://github.com/apache/incubator-mxnet/blob/master/ci/docker/runtime_functions.sh#L553