• 版本、环境信息：
     1）PaddlePaddle版本：1.6.1
     2）CPU：Intel(R) Core(TM) i5-6300HQ CPU @ 2.30GHz
     3）GPU：未使用
     4）系统环境：windows 7 64Bit，Python 3.7.4
• 模型信息
      主要使用 fluid.layers.conv2d 方法
• 复现信息：使用paddle的 conv2d算法建立一个简单的BN操作程序（程序No.1），在连续使用 conv2d时，动态图模式出现错误。 为了查找问题，我建立一个静态运行模式程序（程序 No.2） ，一模一样的算法，却正确通过。
• 问题描述：问题我都注释在代码文档里面了 , 主要是两个：
  1.同样的算法，为何静态没问题，动态却出错，是我的理解错误导致代码不当，还是 Bug？
  2.报错的信息中脚本位置错误，是否是Bug?
  谢谢！

下面贴的代码显示有点问题，请看这个issue的附件

No.1 Program 出错的脚本

import paddle
import paddle.fluid as fluid
from paddle.fluid.param_attr import ParamAttr
from paddle.fluid.dygraph.nn import Conv2D, Pool2D, FC, BatchNorm
from paddle.fluid.regularizer import L2Decay
import numpy as np

class BN(fluid.dygraph.Layer):
def init(self, name_scope,
num_filters,
filter_size,
stride,
padding):
super(BN, self).init(name_scope)

    self._conv2d = Conv2D(
        self.full_name(),
        num_filters=num_filters,
        filter_size=filter_size,
        stride=stride,
        padding=padding,
        param_attr=ParamAttr(
            initializer=fluid.initializer.Normal(0, 0.02)),            
        bias_attr=False,
        act=None)
    
    self._bn = BatchNorm(
        self.full_name(),
        num_channels = num_filters,
        act=None,
        param_attr=ParamAttr(
            initializer=fluid.initializer.Normal(0., 0.02),
            regularizer=L2Decay(0.)),
        bias_attr=ParamAttr(
            initializer=fluid.initializer.Constant(0.0),
            regularizer=L2Decay(0.)))

def forward(self, inputs):
    # print("forward from dbl_block,inputs:", inputs)
    x = self._conv2d(inputs)
    x = self._bn(x)
    return x

place = fluid.CPUPlace()
with fluid.dygraph.guard(place):

x = fluid.layers.ones(shape=[1, 1024, 9, 9], dtype='float32') 

conv1 = BN("conv1", 256, 1, 1, 0)
conv2 = BN("conv2", 512, 3, 1, 1)


print("Step 0,x shape is:", x.shape)  # Step 0,x shape is: [1, 1024, 9, 9]
x1 = conv1(x)
print("Step 1,x shape is:", x1.shape) #Step 1,x shape is: [1, 256, 9, 9]    
x2 = conv2(x1)
print("Step 2,x shape is:", x2.shape) # Step 2,x shape is: [1, 512, 9, 9]    
x3 = conv1(x2)
# PaddleCheckError: Expected input_channels == filter_dims[1] * groups, 
# but received input_channels:512 != filter_dims[1] * groups:1024.
# ShapeError: The number of input channels should be equal to 
# filter channels * groups. But received: the input channels is [512], 
# the shapeof input is [1, 512, 9,9], the filter channel is [1024], 
# the shape of filter is [256, 1024, 1, 1],the groups is [1] at 
# [D:\1.6.1\paddle\paddle\fluid\operators\conv_op.cc:90]

# Interrupted here , and the scripts path is wrong , 
# My scripts path is something like below:
# "C:\Users\Administrator\Anaconda3\envs\paddle\lib\site-packages\paddle\fluid\layers\nn.py
# And instead of it ,I have no  "D:\1.6.1\..."  dir.

print("Step 3,x shape is:", x3.shape)    
x4 = conv2(x3)
print("Step 4,x shape is:", x4.shape)

No.2 Program 未报错的脚本

import paddle.fluid as fluid
from paddle.fluid.param_attr import ParamAttr
from paddle.fluid.initializer import Constant
from paddle.fluid.regularizer import L2Decay
import numpy as np

def BN( input,
ch_out,
filter_size,
stride,
padding,
name=None):

conv1 = fluid.layers.conv2d(
    input=input,
    num_filters=ch_out,
    filter_size=filter_size,
    stride=stride,
    padding=padding,
    param_attr=ParamAttr(
        initializer=fluid.initializer.Normal(0., 0.02)),
    bias_attr=False,
    act=None)

out = fluid.layers.batch_norm(
    input=conv1,
    act=None,
    param_attr=ParamAttr(
        initializer=fluid.initializer.Normal(0., 0.02),
        regularizer=L2Decay(0.)),
    bias_attr=ParamAttr(
        initializer=fluid.initializer.Constant(0.0),
        regularizer=L2Decay(0.)))
return out

place = fluid.CPUPlace()
exe = fluid.Executor(place)

exe.run(fluid.default_startup_program())

x = fluid.layers.ones(shape=[1, 1024, 9, 9], dtype='float32')

x1 = BN(x, 256, 1, 1, 0)
x2 = BN(x1, 512,3, 1, 1)
x3 = BN(x2, 256, 1, 1, 0)
x4 = BN(x3, 512,3, 1, 1)

print("Step 0,x shape is:", x.shape) #Step 0,x shape is: (1, 1024, 9, 9)
print("Step 1,x shape is:", x1.shape) #Step 1,x shape is: (1, 256, 9, 9)
print("Step 2,x shape is:", x2.shape) #Step 2,x shape is: (1, 512, 9, 9)
print("Step 3,x shape is:", x3.shape) #Step 3,x shape is: (1, 256, 9, 9)
print("Step 4,x shape is:", x4.shape) #Step 4,x shape is: (1, 512, 9, 9)

All pass and the result is ok

TheTwoPythonProgram.zip
上面的代码复制显示有点问题，请看附件吧 ，谢谢