From 9f44af9d7c9dd2f1dc775f59d059a87eb9e64fd6 Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Mon, 11 Dec 2017 18:37:18 +0800
Subject: [PATCH] Fix #6460 (#6461)

---
 python/paddle/v2/fluid/layers.py | 20 +++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/python/paddle/v2/fluid/layers.py b/python/paddle/v2/fluid/layers.py
index b4426bad149..fd8a2ed18c9 100644
--- a/python/paddle/v2/fluid/layers.py
+++ b/python/paddle/v2/fluid/layers.py
@@ -762,7 +762,7 @@ def sequence_conv(input,
     helper = LayerHelper('sequence_conv', **locals())
     dtype = helper.input_dtype()
     filter_shape = [filter_size * input.shape[1], num_filters]
-    filter = helper.create_parameter(
+    filter_param = helper.create_parameter(
         attr=helper.param_attr, shape=filter_shape, dtype=dtype)
     pre_bias = helper.create_tmp_variable(dtype)
 
@@ -770,7 +770,7 @@ def sequence_conv(input,
         type='sequence_conv',
         inputs={
             'X': [input],
-            'Filter': [filter],
+            'Filter': [filter_param],
         },
         outputs={"Out": pre_bias},
         attrs={
@@ -785,7 +785,7 @@ def sequence_conv(input,
 def conv2d(input,
            num_filters,
            filter_size,
-           stride=[1, 1],
+           stride=None,
            padding=None,
            groups=None,
            param_attr=None,
@@ -802,6 +802,8 @@ def conv2d(input,
     conv-2d output, if mentioned in the input parameters.
     """
 
+    if stride is None:
+        stride = [1, 1]
     helper = LayerHelper('conv2d', **locals())
     dtype = helper.input_dtype()
 
@@ -827,7 +829,7 @@ def conv2d(input,
         std = (2.0 / (filter_size[0]**2 * num_channels))**0.5
         return Normal(0.0, std, 0)
 
-    filter = helper.create_parameter(
+    filter_param = helper.create_parameter(
         attr=helper.param_attr,
         shape=filter_shape,
         dtype=dtype,
@@ -839,7 +841,7 @@ def conv2d(input,
         type='conv2d_cudnn',
         inputs={
             'Input': input,
-            'Filter': filter,
+            'Filter': filter_param,
         },
         outputs={"Output": pre_bias},
         attrs={'strides': stride,
@@ -875,8 +877,8 @@ def sequence_pool(input, pool_type, **kwargs):
 def pool2d(input,
            pool_size,
            pool_type,
-           pool_stride=[1, 1],
-           pool_padding=[0, 0],
+           pool_stride=None,
+           pool_padding=None,
            global_pooling=False,
            main_program=None,
            startup_program=None):
@@ -884,6 +886,10 @@ def pool2d(input,
     This function adds the operator for pooling in 2 dimensions, using the
     pooling configurations mentioned in input parameters.
     """
+    if pool_padding is None:
+        pool_padding = [0, 0]
+    if pool_stride is None:
+        pool_stride = [1, 1]
     if pool_type not in ["max", "avg"]:
         raise ValueError(
             "Unknown pool_type: '%s'. It can only be 'max' or 'avg'.",
-- 
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