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License: MIT License
A collection of deep learning models (PyTorch implemtation)
License: MIT License
Thanks for your great work
Could you tell me how to use Condconv in my network ๏ผ
According to the code file, the implementation of Mish is as follows:
def mish(tensor: torch.Tensor) -> torch.Tensor:
return tensor * tensor.exp().add(1).log().tanh()
In my repository Mish implementation is like:
def mish(tensor: torch.Tensor) -> torch.Tensor:
return tensor * torch.tanh(F.softplus(tensor))
Is your implementation faster than mine??
Also, would appreciate if you included the paper link of Mish in the main Readme and in the activations readme, in the list of available activations, Mish is not present.
The paper link is in my repository here - https://github.com/digantamisra98/Mish
Issue: While training multiple models, all the models and the corresponding files generated are all saved in the same folder. This makes it hard to search for files generated by a particular model.
Recommendation: To generate a folder for the model being created with the same name and all the corresponding files get dumped inside it.
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