de8494a59edc4f67325194d2b4ac1f957dbe3ce6,lib/discriminators/pyramid_nostride_discriminator.py,,discriminator,#Any#Any#Any#Any#Any#,6

Before Change

    k=-1
    result = dense_block(result, k, activation, batch_size, "transition", "d_layers_transition_"+str(i))
    result = dense_block(result, k, activation, batch_size, "transition", "d_layers_transition_"+str(i+1))
    result = dense_block(result, k, activation, batch_size, "transition", "d_layers_transition_"+str(i+2))

    result = batch_norm(config["batch_size"], name="d_expand_bn_end_"+str(i))(result)

After Change

      filter_size_w = 2
      filter_size_h = 2
      if(i==depth-1):
          filter_size_w=int(result.get_shape()[1])
          filter_size_h=int(result.get_shape()[2])
      filter = [1,filter_size_w,filter_size_h,1]
      stride = [1,filter_size_w,filter_size_h,1]
      result = conv2d(result, int(int(result.get_shape()[3])*depth_increase), name="d_expand_layer"+str(i), k_w=3, k_h=3, d_h=1, d_w=1)
      result = tf.nn.avg_pool(result, ksize=filter, strides=stride, padding="SAME")

Instances