Comments (3)
Lyken17
commented on July 25, 2024
Current counting already considers the case.
https://github.com/Lyken17/pytorch-OpCounter/blob/master/thop/count_hooks.py#L24
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pgr2015
commented on July 25, 2024
Thank you for your reply! Sorry that I am not familar with pytorch API.
I have checked your code and pytorch documentation, if I understand correctly, the parameter m.groups distinguish the standard conv and depthwise conv. For standard conv m.groups will be 1, but for depthwise conv m.groups will be the number of output channel.
Hope to get your reply, thanks!
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ujsyehao
commented on July 25, 2024
@pgr2015 yes
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Related Issues (20)
- Does it support non-image models? HOT 1
- question about the MACs of nn.BatchNorm2d
- got 0 ops for nn.MultiheadAttention HOT 7
- Count flops by a range
- thop/profile.py:12: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. `if LooseVersion(torch.__version__) < LooseVersion("1.0.0"):` HOT 2
- Does MACs and FLOPs count correctly for and INT8 quantized model? HOT 1
- Upload sdist to PyPI HOT 1
- Problem in bert HOT 1
- multiple inputs HOT 1
- Is the latest version calculate MACs or FLOPs HOT 2
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
- How to calculate the FLOPs of each type of layers?
- How to exclude flops of 1st input? HOT 1
- Incorrect macs without specifying batch size for conv layers
- will torch.matmul regards as zero_ops ?
- Is thop also effective for calculating Flops for spiking neural networks?
- rename calculate_conv2d_flops HOT 1
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- RuntimeError: Can't add a new parameter
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