# specifics of dilated convolutions in tensorflow

This ones a little esoteric. I'm developing a wave-net inspired model. First time needing dilated convolutions.

My question is which values is the convolution looking at relative to the output position? For example if I have a Conv1D with kernel_size=4, dilation_rate=2 and padding='same' are the inputs split evenly to both sides so relative positions of input data would be (-3,-1,1,3), or justified to one side giving relative positions like (-6,-4,-2,0) or something different? Is there an easy way to control this behavior?