This is an automated email from the ASF dual-hosted git repository.
roshrini pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new bedf18e beta doc fixes (#13860)
bedf18e is described below
commit bedf18e4618524ace798c1e7f40efe7dec277fc7
Author: Anirudh <[email protected]>
AuthorDate: Wed Jan 16 16:01:35 2019 -0800
beta doc fixes (#13860)
---
R-package/R/context.R | 2 +-
R-package/R/model.R | 2 +-
R-package/R/optimizer.R | 2 +-
R-package/R/rnn.graph.R | 2 +-
src/operator/optimizer_op.cc | 2 +-
src/operator/tensor/elemwise_unary_op_basic.cc | 2 +-
6 files changed, 6 insertions(+), 6 deletions(-)
diff --git a/R-package/R/context.R b/R-package/R/context.R
index 6bbb9aa..1c5a56e 100644
--- a/R-package/R/context.R
+++ b/R-package/R/context.R
@@ -22,7 +22,7 @@ init.context.default <- function() {
#' Set/Get default context for array creation.
#'
-#' @param new, optional takes \code{mx.cpu()} or \code{mx.gpu(id)}, new
default ctx.
+#' @param new optional takes \code{mx.cpu()} or \code{mx.gpu(id)}, new default
ctx.
#' @return The default context.
#'
#' @export
diff --git a/R-package/R/model.R b/R-package/R/model.R
index d71bc5c..51d1705 100644
--- a/R-package/R/model.R
+++ b/R-package/R/model.R
@@ -562,7 +562,7 @@ mx.model.FeedForward.create <-
#'
#' @param model The MXNet Model.
#' @param X The dataset to predict.
-#' @param ctx mx.cpu() or mx.gpu(i) The device used to generate the prediction.
+#' @param ctx mx.cpu() or mx.gpu(). The device used to generate the prediction.
#' @param array.batch.size The batch size used in batching. Only used when X
is R's array.
#' @param array.layout can be "auto", "colmajor", "rowmajor", (detault=auto)
#' The layout of array. "rowmajor" is only supported for two dimensional
array.
diff --git a/R-package/R/optimizer.R b/R-package/R/optimizer.R
index c0af11d..9a858d5 100644
--- a/R-package/R/optimizer.R
+++ b/R-package/R/optimizer.R
@@ -21,7 +21,7 @@
#' @param learning.rate float, default=0.01
#' The initial learning rate.
#' @param momentum float, default=0
-#' The momentumvalue
+#' The momentum value
#' @param wd float, default=0.0
#' L2 regularization coefficient add to all the weights.
#' @param rescale.grad float, default=1.0
diff --git a/R-package/R/rnn.graph.R b/R-package/R/rnn.graph.R
index 2ceefb5..1225fa5 100644
--- a/R-package/R/rnn.graph.R
+++ b/R-package/R/rnn.graph.R
@@ -195,7 +195,7 @@ gru.cell <- function(num_hidden, indata, prev.state, param,
seqidx, layeridx, dr
}
-#' unroll representation of RNN running on non CUDA device
+#' Unroll representation of RNN running on non CUDA device
#'
#' @param config Either seq-to-one or one-to-one
#' @param cell_type Type of RNN cell: either gru or lstm
diff --git a/src/operator/optimizer_op.cc b/src/operator/optimizer_op.cc
index 6c44f99..a52a6f3 100644
--- a/src/operator/optimizer_op.cc
+++ b/src/operator/optimizer_op.cc
@@ -316,7 +316,7 @@ inline bool SGDStorageType(const nnvm::NodeAttrs& attrs,
NNVM_REGISTER_OP(sgd_update)
MXNET_ADD_SPARSE_OP_ALIAS(sgd_update)
-.describe(R"code(Update function for Stochastic Gradient Descent (SDG)
optimizer.
+.describe(R"code(Update function for Stochastic Gradient Descent (SGD)
optimizer.
It updates the weights using::
diff --git a/src/operator/tensor/elemwise_unary_op_basic.cc
b/src/operator/tensor/elemwise_unary_op_basic.cc
index 7f69395..c0d420f 100644
--- a/src/operator/tensor/elemwise_unary_op_basic.cc
+++ b/src/operator/tensor/elemwise_unary_op_basic.cc
@@ -71,7 +71,7 @@ static bool IdentityAttrLikeRhsStorageType(const
nnvm::NodeAttrs& attrs,
// relu
MXNET_OPERATOR_REGISTER_UNARY_WITH_RSP_CSR(relu, cpu, mshadow_op::relu)
-.describe(R"code(Computes rectified linear.
+.describe(R"code(Computes rectified linear activation.
.. math::
max(features, 0)
