A problem in src/conv3dTranspose.py

[RadiantJeral]

Hi, I run the test commend "python test.py -data driving_RGB_cleanpass/ -pspath driving_RGB_cleanpass/a-out/ -bs 1 " and I get the problem as follow.
Use shared weight for first stage
Traceback (most recent call last):
File "test.py", line 60, in
Predict()
File "test.py", line 42, in Predict
model = createGCNetwork(hp, tp, True)
File "src/gcnetwork.py", line 167, in createGCNetwork
disp_map = LearnReg(cv, num_filters, ksize, ds_stride, resnet, padding, highway_func, num_down_conv)
File "src/gcnetwork.py", line 114, in LearnReg
deconv = createDeconv3D(up_convs, filters, ksize, ds_stride, padding)
File "src/gcnetwork.py", line 38, in createDeconv3D
deconv = Conv3DTranspose(filters, ksize, stride, padding) (input)
File "/home/lucifer16/venv/local/lib/python2.7/site-packages/keras/engine/base_layer.py", line 457, in call
output = self.call(inputs, **kwargs)
File "src/conv3dTranspose.py", line 237, in call
self.padding)
TypeError: deconv_length() takes at least 5 arguments (4 given)

The problem seems occurs in the line 237 of "src/conv3dTranspose.py".
The code is "out_depth = conv_utils.deconv_length(depth, stride_h, kernel_h, self.padding)". It passes 4 arguments.

But the source code in Keras github about the "conv_utils.deconv_length" is as follows. And it passes 5arguments.

def deconv_length(dim_size, stride_size, kernel_size, padding,
output_padding, dilation=1):
"""Determines output length of a transposed convolution given input length.
# Arguments
dim_size: Integer, the input length.
stride_size: Integer, the stride along the dimension of dim_size.
kernel_size: Integer, the kernel size along the dimension of dim_size.
padding: One of "same", "valid", "full".
output_padding: Integer, amount of padding along the output dimension, Can be set to None in
which case the output length is inferred.
dilation: dilation rate, integer.
link : https://github.com/keras-team/keras/blob/master/keras/utils/conv_utils.py

I use the "Keras==2. 2. 4". Shall I use a older version or any other suggestions?

Your prompt response will be most appreciated.

[IceTTTb]

Hi, @RadiantJeral : l met the same problem as you. Have you solved it?

[czy341181]

Hi, @RadiantJeral : l met the same problem as you. Have you solved it?

hi, i also met the same problem , which version should I change keras ? Your prompt response will be most appreciated

[alphaccw]

keras 2.1.6 is fine. Or you can just give the 5th argument.