improve layers.fc api doc test=develop

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', '1929058262994f212620599c63aea6bd'))
+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.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'))
@@ -511,17 +511,3 @@ paddle.fluid.unique_name.guard (ArgSpec(args=['new_generator'], varargs=None, ke
 paddle.fluid.recordio_writer.convert_reader_to_recordio_file (ArgSpec(args=['filename', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None)), ('document', '65c7523e86f0c50bb729b01667f36310'))
 paddle.fluid.recordio_writer.convert_reader_to_recordio_files (ArgSpec(args=['filename', 'batch_per_file', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None)), ('document', 'bc643f0f5f1b9db57ff0d8a57d379bd7'))
 paddle.fluid.Scope Scope() -> paddle.fluid.core._Scope
-paddle.reader.map_readers (ArgSpec(args=['func'], varargs='readers', keywords=None, defaults=None), ('document', '77cbadb09df588e21e5cc0819b69c87d'))
-paddle.reader.buffered (ArgSpec(args=['reader', 'size'], varargs=None, keywords=None, defaults=None), ('document', '0d6186f109feceb99f60ec50a0a624cb'))
-paddle.reader.compose (ArgSpec(args=[], varargs='readers', keywords='kwargs', defaults=None), ('document', '884291104e1c3f37f33aae44b7deeb0d'))
-paddle.reader.chain (ArgSpec(args=[], varargs='readers', keywords=None, defaults=None), ('document', 'd22c34e379a53901ae67a6bca7f4def4'))
-paddle.reader.shuffle (ArgSpec(args=['reader', 'buf_size'], varargs=None, keywords=None, defaults=None), ('document', 'e42ea6fee23ce26b23cb142cd1d6522d'))
-paddle.reader.firstn (ArgSpec(args=['reader', 'n'], varargs=None, keywords=None, defaults=None), ('document', 'c5bb8f7dd4f917f1569a368aab5b8aad'))
-paddle.reader.xmap_readers (ArgSpec(args=['mapper', 'reader', 'process_num', 'buffer_size', 'order'], varargs=None, keywords=None, defaults=(False,)), ('document', '283bc0b8a0e26ae186b8b9bee4aec560'))
-paddle.reader.PipeReader.__init__ (ArgSpec(args=['self', 'command', 'bufsize', 'file_type'], varargs=None, keywords=None, defaults=(8192, 'plain')), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.reader.PipeReader.get_line (ArgSpec(args=['self', 'cut_lines', 'line_break'], varargs=None, keywords=None, defaults=(True, '\n')), ('document', '5f80a7ed70052f01665e4c74acccfa69'))
-paddle.reader.multiprocess_reader (ArgSpec(args=['readers', 'use_pipe', 'queue_size'], varargs=None, keywords=None, defaults=(True, 1000)), ('document', '7d8b3a96e592107c893d5d51ce968ba0'))
-paddle.reader.Fake.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.reader.creator.np_array (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '28d457fbc9a71efa4ac91a3be179cada'))
-paddle.reader.creator.text_file (ArgSpec(args=['path'], varargs=None, keywords=None, defaults=None), ('document', '44fe286ab6175a5464d3a961a68c266a'))
-paddle.reader.creator.recordio (ArgSpec(args=['paths', 'buf_size'], varargs=None, keywords=None, defaults=(100,)), ('document', '11b3704ea42cfd537953387a7e58dae8'))

python/paddle/fluid/layers/nn.py

@@ -205,16 +205,23 @@ def fc(input,
     **Fully Connected Layer**
 
     This function creates a fully connected layer in the network. It can take
-    multiple tensors as its inputs. 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 coresponding weight to produce an output Tensor.
-    If multiple input tensors are given, the results of multiple multiplications
-    will be sumed 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.
+    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,
+    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
+    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.
+
+    When the input is single tensor:
 
-    This process can be formulated as follows:
+    .. math::
+
+        Out = Act({XW + b})
+
+    When the input are multiple tensors:
 
     .. math::
 
@@ -222,13 +229,31 @@ def fc(input,
 
     In the above equation:
 
-    * :math:`N`: Number of the input.
-    * :math:`X_i`: The input tensor.
-    * :math:`W`: The weights created by this layer.
+    * :math:`N`: Number of the input. N equals to len(input) if input is list of Variable.
+    * :math:`X_i`: The i-th input tensor.
+    * :math:`W_i`: The i-th weights matrix corresponding i-th input tensor.
     * :math:`b`: The bias parameter created by this layer (if needed).
     * :math:`Act`: The activation function.
     * :math:`Out`: The output tensor.
 
+    See below for an example.
+
+    .. code-block:: text
+
+        Given:
+            data_1.data = [[[0.1, 0.2],
+                           [0.3, 0.4]]]
+            data_1.shape = (1, 2, 2) # 1 is batch_size
+
+            data_2 = [[[0.1, 0.2, 0.3]]]
+            data_2.shape = (1, 1, 3)
+
+            out = fluid.layers.fc(input=[data_1, data_2], size=2)
+
+        Then:
+            out.data = [[0.18669507, 0.1893476]]
+            out.shape = (1, 2)
+
     Args:
         input (Variable|list of Variable): The input tensor(s) of this layer, and the dimension of
             the input tensor(s) is at least 2.
@@ -260,8 +285,14 @@ def fc(input,
     Examples:
         .. code-block:: python
 
+          # when input is single tensor
           data = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
           fc = fluid.layers.fc(input=data, size=1000, act="tanh")
+
+          # when input are multiple tensors
+          data_1 = fluid.layers.data(name="data_1", shape=[32, 32], dtype="float32")
+          data_2 = fluid.layers.data(name="data_2", shape=[24, 36], dtype="float32")
+          fc = fluid.layers.fc(input=[data_1, data_2], size=1000, act="tanh")
     """
 
     helper = LayerHelper("fc", **locals())