From 47591f923873bad36ad2769e6b5d7d84d5a74a20 Mon Sep 17 00:00:00 2001
From: Anirudh Acharya <aanirud@amazon.com>
Date: Fri, 11 Jan 2019 20:45:18 -0800
Subject: [PATCH] beta doc fixes

---
 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 6bbb9aa6a926..1c5a56ed919e 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 d71bc5cae67d..51d1705ba5f0 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 c0af11dc922a..9a858d5a6c56 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 2ceefb57d352..1225fa511b51 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 6c44f99c1443..a52a6f32907c 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 7f69395d1c87..c0d420f9599b 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)