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Hi! Thank you for this awesome library, it helps me a lot.
I am not sure whether I'm missing something, but I'm confused about why DifferentiableOptimizer detaches parameters when `track_higher_gra…
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## ❓ Questions and Help
In the constructor of `TracIn` is the flag `sample_wise_grads_per_batch`. In the “main” method `_compute_jacobian_wrt_params_with_sample_wise_trick` for this trick is the co…
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Dear UV-CDAT Developers,
Greetings!
When I am trying to access ensemble dimension (which has embedded within variable as another dimension / axis / coordinates) from grib2 file, cdms2 just suppresse…
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### Feature description
I would like to be able to take partial derivative of the neural network.
In PyTorch like this: https://stackoverflow.com/a/66709533/10969548
In TensorFlow like this: …
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I have already known that I can use ``radii>0`` to filter the gaussians which project onto a certain view. However, I want to know which gaussians contribute to a certain rendering? Or, which gaussia…
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@jasonb5 I don't have time to upload a test file (before next week), but maybe you can test this anyway
I have converted a grads dat/ctl file using cdms2
The ctl file has the following content
…
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I have multiple samples of one-dimensional inputs being classified in two classes, 0 and 1. I would like to know which parts of the signal are responsible for each of these classes, respectively, and …
ghost updated
6 years ago
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As title says, I'm wondering if its possible to adapt the save mechanics that already exist to make it save ONLY things with a specific variable? Would I be able to enable Grads-Fortification support …
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It seems that the code below always get eps=[0...], l_f_meta=0 and the params in meta_net do not update in each iteration.
```
eps = to_var(torch.zeros(cost.size()))
l_f_meta = torch.sum(cost *…
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deepspeed==0.7.0 pytorch-lightning==1.9.2 torch 1.13.1+cu117
一样的版本;
Traceback (most recent call last):
File "summarization_pipeline.py", line 1382, in
main()
File "summarization_pipeli…