fix errors

paddle/fluid/operators/activation_op.cc

@@ -444,7 +444,7 @@ class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
     AddComment(R"DOC(
 Swish Activation Operator.
 
-$$out = \frac{x}{1 + e^{- \beta x}}$$
+$$out = \\frac{x}{1 + e^{- \beta x}}$$
 
 )DOC");
   }

paddle/fluid/operators/pool_op.cc

@@ -224,17 +224,17 @@ Example:
 
   For ceil_mode = false:
        $$
-       H_{out} = \frac{(H_{in} - ksize[0] + 2 * paddings[0])}{strides[0]} + 1
+       H_{out} = \\frac{(H_{in} - ksize[0] + 2 * paddings[0])}{strides[0]} + 1
        $$
        $$
-       W_{out} = \frac{(W_{in} - ksize[1] + 2 * paddings[1])}{strides[1]} + 1
+       W_{out} = \\frac{(W_{in} - ksize[1] + 2 * paddings[1])}{strides[1]} + 1
        $$
   For ceil_mode = true:
        $$
-       H_{out} = \frac{(H_{in} - ksize[0] + 2 * paddings[0] + strides[0] - 1)}{strides[0]} + 1
+       H_{out} = \\frac{(H_{in} - ksize[0] + 2 * paddings[0] + strides[0] - 1)}{strides[0]} + 1
        $$
        $$
-       W_{out} = \frac{(W_{in} - ksize[1] + 2 * paddings[1] + strides[1] - 1)}{strides[1]} + 1
+       W_{out} = \\frac{(W_{in} - ksize[1] + 2 * paddings[1] + strides[1] - 1)}{strides[1]} + 1
        $$
 
 )DOC");

python/paddle/fluid/layers/nn.py

@@ -1495,9 +1495,9 @@ def pool2d(input,
 
     Args:
         input (Variable): The input tensor of pooling operator. The format of 
-        input tensor is NCHW, where N is batch size, C is the number of 
-        channels, H is the height of the feature, and W is the width of 
-        the feature.
+                          input tensor is NCHW, where N is batch size, C is 
+                          the number of channels, H is the height of the 
+                          feature, and W is the width of the feature.
         pool_size (int): The side length of pooling windows. All pooling 
                          windows are squares with pool_size on a side.
         pool_type: ${pooling_type_comment}

python/paddle/fluid/layers/tensor.py

@@ -146,7 +146,8 @@ def concat(input, axis=0, name=None):
 
     Examples:
         .. code-block:: python
-          out = fluid.layers.concat(input=[Efirst, Esecond, Ethird, Efourth])
+        
+           out = fluid.layers.concat(input=[Efirst, Esecond, Ethird, Efourth])
     """
     helper = LayerHelper('concat', **locals())
     out = helper.create_tmp_variable(dtype=helper.input_dtype())