Closed libornovax closed 7 years ago
Memory consumption of net macc_0.3_r2_x2_to_x8_s2
vs macc_0.3_r2_x2_to_x8
:
TEST: 9046 MiB vs. 11610 MiB, TRAIN: 8760 MiB vs. 10666 MiB
I can happily say that it does not affect performance in a negative way. The net even performs slightly better, but that is probably just a coincidence:
With pooling after x1:
With stride=2 of the last conv layer in x1:
This is great news, because the net consumes way less memory and it is also faster to compute!
I want to do this because it saves a lot of GPU memory and I don't think it should affect the result...