Add python wrapper for reduce_mean

doc/api/v2/fluid/layers.rst

@@ -318,3 +318,9 @@ reduce_sum
 ..  autofunction:: paddle.v2.fluid.layers.reduce_sum
     :noindex:
 
+
+reduce_mean
+---------
+..  autofunction:: paddle.v2.fluid.layers.reduce_mean
+    :noindex:
+

python/paddle/v2/fluid/layers/nn.py

@@ -13,7 +13,7 @@ __all__ = [
     'crf_decoding', 'cos_sim', 'cross_entropy', 'square_error_cost', 'accuracy',
     'chunk_eval', 'sequence_conv', 'conv2d', 'sequence_pool', 'pool2d',
     'batch_norm', 'beam_search_decode', 'conv2d_transpose', 'sequence_expand',
-    'lstm_unit', 'reduce_sum'
+    'lstm_unit', 'reduce_sum', 'reduce_mean'
 ]
 
 
@@ -979,3 +979,47 @@ def reduce_sum(input, dim=None, keep_dim=False):
             'reduce_all': True if dim == None else False
         })
     return out
+
+
+def reduce_mean(input, dim=None, keep_dim=False):
+    """
+    Computes the mean of tensor elements over the given dimension. 
+
+    Args:
+        input (Variable): The input variable which is a Tensor or LoDTensor.
+        dim (int|None): The dimension along which the mean is computed. If 
+            :attr:`None`, compute the mean over all elements of :attr:`input` 
+            and return a Tensor variable with a single element, otherwise 
+            must be in the range :math:`[-rank(input), rank(input))`. If 
+            :math:`dim < 0`, the dimension to reduce is :math:`rank + dim`.
+        keep_dim (bool): Whether to reserve the reduced dimension in the 
+            output Tensor. The result tensor will have one fewer dimension 
+            than the :attr:`input` unless :attr:`keep_dim` is true.
+
+    Returns:
+        Variable: The reduced Tensor variable.
+    
+    Examples:
+        .. code-block:: python
+
+            # x is a Tensor variable with following elements:
+            #    [[0.2, 0.3, 0.5, 0.9]
+            #     [0.1, 0.2, 0.6, 0.7]]
+            # Each example is followed by the correspending output tensor.
+            fluid.layers.reduce_mean(x)  # [0.4375]
+            fluid.layers.reduce_mean(x, dim=0)  # [0.15, 0.25, 0.55, 0.8]
+            fluid.layers.reduce_mean(x, dim=-1)  # [0.475, 0.4]
+            fluid.layers.reduce_mean(x, dim=1, keep_dim=True)  # [[0.475], [0.4]]
+    """
+    helper = LayerHelper('reduce_mean', **locals())
+    out = helper.create_tmp_variable(dtype=helper.input_dtype())
+    helper.append_op(
+        type='reduce_mean',
+        inputs={'X': input},
+        outputs={'Out': out},
+        attrs={
+            'dim': dim if dim != None else 0,
+            'keep_dim': keep_dim,
+            'reduce_all': True if dim == None else False
+        })
+    return out