Comments (2)
muslll
commented on August 17, 2024
Hi! We have previously discussed this on EE discord, I removed this re-parametrization because it tries to optimizer eval_conv, which torch can't:
2023-12-11 03:47:37,177 WARNING: Params conv_1.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params conv_1.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_1.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,177 WARNING: Params block_2.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_2.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_2.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_2.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_2.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_2.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_3.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_4.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,178 WARNING: Params block_4.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_4.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_4.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_4.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_4.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_5.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_6.c1_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_6.c1_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_6.c2_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,179 WARNING: Params block_6.c2_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,180 WARNING: Params block_6.c3_r.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,180 WARNING: Params block_6.c3_r.eval_conv.bias will not be optimized.
2023-12-11 03:47:37,180 WARNING: Params conv_2.eval_conv.weight will not be optimized.
2023-12-11 03:47:37,180 WARNING: Params conv_2.eval_conv.bias will not be optimized.
While it doesn't prevent training, I would rather not have such issues. In the official code, the author used a bool flag (self.training), but even when setting it to true torch still sends it to the optimizer. So because we were just testing this network and eval_conv doesn't affect training (only inference), I didn't dig much further.
We should ask the authors if they have a good solution for this. Thanks for reporting.
edit: made an issue on SPAN repo
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muslll
commented on August 17, 2024
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