From f0cd14828d22aa61bb23ec1dc3623021b08019ed Mon Sep 17 00:00:00 2001 From: Aaron Markham Date: Tue, 5 Mar 2019 22:34:45 -0800 Subject: [PATCH] fix render issue in NDArray linalg docs (#14258) * fix render issue in docs * nudge ci * update copyright year; mostly for bumping ci * bumping ci * delete whitespace --- src/operator/tensor/la_op.cc | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) diff --git a/src/operator/tensor/la_op.cc b/src/operator/tensor/la_op.cc index 252bdf8d9460..12cea91f5800 100644 --- a/src/operator/tensor/la_op.cc +++ b/src/operator/tensor/la_op.cc @@ -18,10 +18,11 @@ */ /*! - * Copyright (c) 2017 by Contributors + * Copyright (c) 2019 by Contributors * \file la_op.cc * \brief CPU implementation of Operators for advanced linear algebra. */ + #include "./la_op.h" #include "./la_op-inl.h" @@ -48,11 +49,12 @@ Here, *alpha* and *beta* are scalar parameters, and *op()* is either the identit matrix transposition (depending on *transpose_a*, *transpose_b*). If *n>2*, *gemm* is performed separately for a batch of matrices. The column indices of the matrices -are given by the last dimensions of the tensors, the row indices by the axis specified with the *axis* +are given by the last dimensions of the tensors, the row indices by the axis specified with the *axis* parameter. By default, the trailing two dimensions will be used for matrix encoding. For a non-default axis parameter, the operation performed is equivalent to a series of swapaxes/gemm/swapaxes -calls. For example let *A*, *B*, *C* be 5 dimensional tensors. Then gemm(*A*, *B*, *C*, axis=1) is equivalent to +calls. For example let *A*, *B*, *C* be 5 dimensional tensors. Then gemm(*A*, *B*, *C*, axis=1) is equivalent +to the following without the overhead of the additional swapaxis operations:: A1 = swapaxes(A, dim1=1, dim2=3) B1 = swapaxes(B, dim1=1, dim2=3) @@ -60,8 +62,6 @@ calls. For example let *A*, *B*, *C* be 5 dimensional tensors. Then gemm(*A*, *B C = gemm(A1, B1, C) C = swapaxis(C, dim1=1, dim2=3) -without the overhead of the additional swapaxis operations. - When the input data is of type float32 and the environment variables MXNET_CUDA_ALLOW_TENSOR_CORE and MXNET_CUDA_TENSOR_OP_MATH_ALLOW_CONVERSION are set to 1, this operator will try to use pseudo-float16 precision (float32 math with float16 I/O) precision in order to use @@ -126,19 +126,18 @@ Here *alpha* is a scalar parameter and *op()* is either the identity or the matr transposition (depending on *transpose_a*, *transpose_b*). If *n>2*, *gemm* is performed separately for a batch of matrices. The column indices of the matrices -are given by the last dimensions of the tensors, the row indices by the axis specified with the *axis* +are given by the last dimensions of the tensors, the row indices by the axis specified with the *axis* parameter. By default, the trailing two dimensions will be used for matrix encoding. For a non-default axis parameter, the operation performed is equivalent to a series of swapaxes/gemm/swapaxes calls. For example let *A*, *B* be 5 dimensional tensors. Then gemm(*A*, *B*, axis=1) is equivalent to +the following without the overhead of the additional swapaxis operations:: A1 = swapaxes(A, dim1=1, dim2=3) B1 = swapaxes(B, dim1=1, dim2=3) C = gemm2(A1, B1) C = swapaxis(C, dim1=1, dim2=3) -without the overhead of the additional swapaxis operations. - When the input data is of type float32 and the environment variables MXNET_CUDA_ALLOW_TENSOR_CORE and MXNET_CUDA_TENSOR_OP_MATH_ALLOW_CONVERSION are set to 1, this operator will try to use pseudo-float16 precision (float32 math with float16 I/O) precision in order to use @@ -317,7 +316,6 @@ If *n>2*, *trmm* is performed separately on the trailing two dimensions for all .. note:: The operator supports float32 and float64 data types only. - Examples:: // Single triangular matrix multiply