Fix Sphinx errors

python/mxnet/gluon/contrib/rnn/conv_rnn_cell.py

@@ -255,7 +255,7 @@ class Conv1DRNNCell(_ConvRNNCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_rnn_'
+    prefix : str, default ``'conv_rnn_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -322,7 +322,7 @@ class Conv2DRNNCell(_ConvRNNCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_rnn_'
+    prefix : str, default ``'conv_rnn_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -389,7 +389,7 @@ class Conv3DRNNCell(_ConvRNNCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_rnn_'
+    prefix : str, default ``'conv_rnn_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -519,7 +519,7 @@ class Conv1DLSTMCell(_ConvLSTMCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_lstm_'
+    prefix : str, default ``'conv_lstm_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -596,7 +596,7 @@ class Conv2DLSTMCell(_ConvLSTMCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_lstm_'
+    prefix : str, default ``'conv_lstm_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -673,7 +673,7 @@ class Conv3DLSTMCell(_ConvLSTMCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_lstm_'
+    prefix : str, default ``'conv_lstm_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -803,7 +803,7 @@ class Conv1DGRUCell(_ConvGRUCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_gru_'
+    prefix : str, default ``'conv_gru_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -875,7 +875,7 @@ class Conv2DGRUCell(_ConvGRUCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_gru_'
+    prefix : str, default ``'conv_gru_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.
@@ -947,7 +947,7 @@ class Conv3DGRUCell(_ConvGRUCell):
         If argument type is string, it's equivalent to nn.Activation(act_type=str). See
         :func:`~mxnet.ndarray.Activation` for available choices.
         Alternatively, other activation blocks such as nn.LeakyReLU can be used.
-    prefix : str, default 'conv_gru_'
+    prefix : str, default ``'conv_gru_``'
         Prefix for name of layers (and name of weight if params is None).
     params : RNNParams, default None
         Container for weight sharing between cells. Created if None.

python/mxnet/io/io.py

@@ -490,8 +490,8 @@ class NDArrayIter(DataIter):
     """Returns an iterator for ``mx.nd.NDArray``, ``numpy.ndarray``, ``h5py.Dataset``
     ``mx.nd.sparse.CSRNDArray`` or ``scipy.sparse.csr_matrix``.
 
-    Example usage:
-    ----------
+    Examples
+    --------
     >>> data = np.arange(40).reshape((10,2,2))
     >>> labels = np.ones([10, 1])
     >>> dataiter = mx.io.NDArrayIter(data, labels, 3, True, last_batch_handle='discard')

python/mxnet/test_utils.py

@@ -1844,6 +1844,7 @@ def var_check(generator, sigma, nsamples=1000000):
 
 def chi_square_check(generator, buckets, probs, nsamples=1000000):
     """Run the chi-square test for the generator. The generator can be both continuous and discrete.
+
     If the generator is continuous, the buckets should contain tuples of (range_min, range_max) and
      the probs should be the corresponding ideal probability within the specific ranges.
     Otherwise, the buckets should be the possible output of the discrete distribution and the probs