diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index c4b984cd2390dac6933f180f7f248f46b36a09a9..b8faa53c62a3e555b89d51918810001b1a863fba 100644
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -68,7 +68,7 @@ paddle.fluid.initializer.MSRAInitializer.__init__ (ArgSpec(args=['self', 'unifor
 paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '6d0f3e22c90d9d500d36ff57daf056ee'))
 paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'a6d7011ca3d8c0d454dac3a56eae0c29'))
 paddle.fluid.initializer.NumpyArrayInitializer.__init__ (ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None)), ('document', '0fd03868c3c4f25d7f8d43daac69e6d3'))
+paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None)), ('document', '424e898365195e3ccbc2e7dc8b63605e'))
 paddle.fluid.layers.embedding (ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32')), ('document', '89c2c55a0b0656b106064048e068e77a'))
 paddle.fluid.layers.dynamic_lstm (ArgSpec(args=['input', 'size', 'h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'float32', None)), ('document', 'dfbb624f85015df29e994ca6999e8ff6'))
 paddle.fluid.layers.dynamic_lstmp (ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None)), ('document', 'b4b608b986eb9617aa0525e1be21d32d'))
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 8cf0a457fd35a02b28798a001cd0fb1d719c9224..9eca56e7e7862d6a27fa79e1b325717f2f278338 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -206,12 +206,12 @@ def fc(input,
 
     This function creates a fully connected layer in the network. It can take
     one or multiple tensors as its inputs(input can be a list of Variable, see
-    Args in detail). It creates a variable called weights foreach input tensor,
+    Args in detail). It creates a variable called weights for each input tensor,
     which represents a fully connected weight matrix from each input unit to
     each output unit. The fully connected layer multiplies each input tensor
     with its corresponding weight to produce an output Tensor with shape [M, `size`],
     where M is batch size. If multiple input tensors are given, the results of
-    multiple output tensors with shape [M, `size`] will be sumed up. If bias_attr
+    multiple output tensors with shape [M, `size`] will be summed up. If bias_attr
     is not None, a bias variable will be created and added to the output.
     Finally, if activation is not None, it will be applied to the output as well.