@@ -130,11 +130,11 @@ def conv(self,
130130 output = convolve (input , kernel )
131131 else :
132132 # Split the input into groups and then convolve each of them independently
133- input_groups = tf .split (3 , group , input )
134- kernel_groups = tf .split (3 , group , kernel )
133+ input_groups = tf .split (input , group , 3 )
134+ kernel_groups = tf .split (kernel , group , 3 )
135135 output_groups = [convolve (i , k ) for i , k in zip (input_groups , kernel_groups )]
136136 # Concatenate the groups
137- output = tf .concat (3 , output_groups )
137+ output = tf .concat (output_groups , 3 )
138138 # Add the biases
139139 if biased :
140140 biases = self .make_var ('biases' , [c_o ])
@@ -177,7 +177,7 @@ def lrn(self, input, radius, alpha, beta, name, bias=1.0):
177177
178178 @layer
179179 def concat (self , inputs , axis , name ):
180- return tf .concat (concat_dim = axis , values = inputs , name = name )
180+ return tf .concat (values = inputs , concat_dim = axis , name = name )
181181
182182 @layer
183183 def add (self , inputs , name ):
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