follow comment

test=develop

paddle/fluid/API.spec

@@ -61,11 +61,11 @@ paddle.fluid.layers.cos_sim ArgSpec(args=['X', 'Y'], varargs=None, keywords=None
 paddle.fluid.layers.cross_entropy ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100))
 paddle.fluid.layers.square_error_cost ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.chunk_eval ArgSpec(args=['input', 'label', 'chunk_scheme', 'num_chunk_types', 'excluded_chunk_types'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.layers.sequence_conv ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'bias_attr', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(3, 1, None, None, None, None))
+paddle.fluid.layers.sequence_conv ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'bias_attr', 'param_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(3, 1, None, None, None, None, None))
 paddle.fluid.layers.conv2d ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None))
 paddle.fluid.layers.conv3d ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None))
 paddle.fluid.layers.sequence_pool ArgSpec(args=['input', 'pool_type'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.layers.sequence_softmax ArgSpec(args=['input', 'use_cudnn'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.layers.sequence_softmax ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None))
 paddle.fluid.layers.softmax ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(True, None))
 paddle.fluid.layers.pool2d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None))
 paddle.fluid.layers.pool3d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None))

python/paddle/fluid/layers/nn.py

@@ -1265,7 +1265,8 @@ def sequence_conv(input,
                   padding=None,
                   bias_attr=None,
                   param_attr=None,
-                  act=None):
+                  act=None,
+                  name=None):
     """
     This function creates the op for sequence_conv, using the inputs and
     other convolutional configurations for the filters and stride as given
@@ -1287,6 +1288,8 @@ def sequence_conv(input,
             will create ParamAttr as param_attr. If the Initializer of the param_attr
             is not set, the parameter is initialized with Xavier. Default: None.
         act (str): the activation type
+        name (str|None): A name for this layer(optional). If set None, the layer
+            will be named automatically. Default: None.
 
     Returns:
         Variable: output of sequence_conv
@@ -1315,7 +1318,7 @@ def sequence_conv(input,
     return helper.append_activation(pre_act)
 
 
-def sequence_softmax(input, use_cudnn=False):
+def sequence_softmax(input, use_cudnn=False, name=None):
     """
     This function computes the softmax activation among all time-steps for each
     sequence. The dimension of each time-step should be 1. Thus, the shape of
@@ -1336,7 +1339,9 @@ def sequence_softmax(input, use_cudnn=False):
     Args:
         input (Variable): The input variable which is a LoDTensor.
         use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn \
-        library is installed. Default: False
+            library is installed. Default: False.
+        name (str|None): A name for this layer(optional). If set None, the layer
+            will be named automatically. Default: None.
 
     Returns:
         Variable: output of sequence_softmax
@@ -1389,6 +1394,8 @@ def softmax(input, use_cudnn=True, name=None):
         input (Variable): The input variable.
         use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn \
             library is installed.
+        name (str|None): A name for this layer(optional). If set None, the layer
+            will be named automatically. Default: None.
 
     Returns:
         Variable: output of softmax