fix random docs (apache#8676)

rahul003 · Nov 19, 2017 · a8f79bc · a8f79bc
1 parent bdd14a8
commit a8f79bc
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Showing 3 changed files with 21 additions and 23 deletions.
diff --git a/docs/api/python/ndarray/ndarray.md b/docs/api/python/ndarray/ndarray.md
@@ -559,13 +559,13 @@ The `ndarray` package provides several classes:
 .. autosummary::
     :nosignatures:
 
-    sample_uniform
-    sample_normal
-    sample_gamma
-    sample_exponential
-    sample_poisson
-    sample_negative_binomial
-    sample_generalized_negative_binomial
+    mxnet.nd.random.uniform
+    mxnet.nd.random.normal
+    mxnet.nd.random.gamma
+    mxnet.nd.random.exponential
+    mxnet.nd.random.poisson
+    mxnet.nd.random.negative_binomial
+    mxnet.nd.random.generalized_negative_binomial
     mxnet.random.seed
 ```
 
@@ -580,7 +580,6 @@ The `ndarray` package provides several classes:
     argsort
     argmax
     argmin
-    argmax_channel
 ```
 
 ### Sequence operation

diff --git a/docs/api/python/symbol/symbol.md b/docs/api/python/symbol/symbol.md
@@ -558,13 +558,13 @@ Composite multiple symbols into a new one by an operator.
 .. autosummary::
     :nosignatures:
 
-    sample_uniform
-    sample_normal
-    sample_gamma
-    sample_exponential
-    sample_poisson
-    sample_negative_binomial
-    sample_generalized_negative_binomial
+    mxnet.sym.random.uniform
+    mxnet.sym.random.normal
+    mxnet.sym.random.gamma
+    mxnet.sym.random.exponential
+    mxnet.sym.random.poisson
+    mxnet.sym.random.negative_binomial
+    mxnet.sym.random.generalized_negative_binomial
     mxnet.random.seed
 ```
 
@@ -579,7 +579,6 @@ Composite multiple symbols into a new one by an operator.
     argsort
     argmax
     argmin
-    argmax_channel
 ```
 
 ### Sequence operation

diff --git a/python/mxnet/gluon/rnn/rnn_layer.py b/python/mxnet/gluon/rnn/rnn_layer.py
@@ -299,11 +299,11 @@ class RNN(_RNNLayer):
     --------
     >>> layer = mx.gluon.rnn.RNN(100, 3)
     >>> layer.initialize()
-    >>> input = mx.nd.random_uniform(shape=(5, 3, 10))
+    >>> input = mx.nd.random.uniform(shape=(5, 3, 10))
     >>> # by default zeros are used as begin state
     >>> output = layer(input)
     >>> # manually specify begin state.
-    >>> h0 = mx.nd.random_uniform(shape=(3, 3, 100))
+    >>> h0 = mx.nd.random.uniform(shape=(3, 3, 100))
     >>> output, hn = layer(input, h0)
     """
     def __init__(self, hidden_size, num_layers=1, activation='relu',
@@ -399,12 +399,12 @@ class LSTM(_RNNLayer):
     --------
     >>> layer = mx.gluon.rnn.LSTM(100, 3)
     >>> layer.initialize()
-    >>> input = mx.nd.random_uniform(shape=(5, 3, 10))
+    >>> input = mx.nd.random.uniform(shape=(5, 3, 10))
     >>> # by default zeros are used as begin state
     >>> output = layer(input)
     >>> # manually specify begin state.
-    >>> h0 = mx.nd.random_uniform(shape=(3, 3, 100))
-    >>> c0 = mx.nd.random_uniform(shape=(3, 3, 100))
+    >>> h0 = mx.nd.random.uniform(shape=(3, 3, 100))
+    >>> c0 = mx.nd.random.uniform(shape=(3, 3, 100))
     >>> output, hn = layer(input, [h0, c0])
     """
     def __init__(self, hidden_size, num_layers=1, layout='TNC',
@@ -496,11 +496,11 @@ class GRU(_RNNLayer):
     --------
     >>> layer = mx.gluon.rnn.GRU(100, 3)
     >>> layer.initialize()
-    >>> input = mx.nd.random_uniform(shape=(5, 3, 10))
+    >>> input = mx.nd.random.uniform(shape=(5, 3, 10))
     >>> # by default zeros are used as begin state
     >>> output = layer(input)
     >>> # manually specify begin state.
-    >>> h0 = mx.nd.random_uniform(shape=(3, 3, 100))
+    >>> h0 = mx.nd.random.uniform(shape=(3, 3, 100))
     >>> output, hn = layer(input, h0)
     """
     def __init__(self, hidden_size, num_layers=1, layout='TNC',