Comments (5)
Hi @yueyinqiu !
Thanks for writing up the diff. I went through all the methods/modules that were missing in TorchSharp, and they are all pure PyTorch code that don't appear in LibTorch (the underlying C++ library). This means that we would need to rewrite all the methods ourselves in TorchSharp, which can take time to write properly.
Do you have any specific methods that are more important for you in the short term? If so, I can dedicate some time to porting those over in the shorter term.
All contributions are more than welcome, so if you want to port some of the functions as well, that would be great!
[Side note: The clip_grad_norm
function in PyTorch is deprecated and just calls the clip_grad_norm_
function, which exists in TorchSharp as well].
from torchsharp.
Hi @yueyinqiu ! Thanks for writing up the diff. I went through all the methods/modules that were missing in TorchSharp, and they are all pure PyTorch code that don't appear in LibTorch (the underlying C++ library). This means that we would need to rewrite all the methods ourselves in TorchSharp, which can take time to write properly. Do you have any specific methods that are more important for you in the short term? If so, I can dedicate some time to porting those over in the shorter term.
All contributions are more than welcome, so if you want to port some of the functions as well, that would be great!
[Side note: The
clip_grad_norm
function in PyTorch is deprecated and just calls theclip_grad_norm_
function, which exists in TorchSharp as well].
Well in fact I'm just a newbie to deep learning and I was trying reproducing some others' work which used spectral_norm
. But I have later found that they skipped all the spectral_norm
s in their final configuration. So it's not that urgent and I'm just making a note here.
Actually I'd like to contribute the project. It's so great to be able to use C# instead of Python. However I'm afraid that my unfamiliarity with deep learning and PyTorch will mess everything up :(
(Please feel free to edit my list, like just remove the clip_grad_norm
here if you think it's appropriate.)
from torchsharp.
Hi @yueyinqiu ! Thanks for writing up the diff. I went through all the methods/modules that were missing in TorchSharp, and they are all pure PyTorch code that don't appear in LibTorch (the underlying C++ library). This means that we would need to rewrite all the methods ourselves in TorchSharp, which can take time to write properly. Do you have any specific methods that are more important for you in the short term? If so, I can dedicate some time to porting those over in the shorter term.
All contributions are more than welcome, so if you want to port some of the functions as well, that would be great!
[Side note: The
clip_grad_norm
function in PyTorch is deprecated and just calls theclip_grad_norm_
function, which exists in TorchSharp as well].
I've tried to add fuse_conv_bn_weights
and fuse_linear_bn_weights
in #1262 . Could you please take a look and give me some advice?
from torchsharp.
Related Issues (20)
- Can TorchSharp still be running in the background after terminating program? HOT 3
- Not supported exception with libtorch-cpu-win-x64 (2.1.0.1) HOT 1
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- Missing `prod` function `torch.prod` or `a.prod()` where a is Tensor HOT 1
- Tensor.masked_fill applying mask incorrectly? HOT 1
- rng_state on cuda HOT 1
- Missing attribute compare with Pytorch HOT 5
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- cstr and npstr for 0d tensors HOT 2
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- InverseMelScale in NewDisposeScope HOT 4
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