pytorch
Here are 16,191 public repositories matching this topic...
-
Updated
Jun 20, 2021 - Jupyter Notebook
-
Updated
Jun 25, 2021 - Python
-
Updated
Jun 10, 2021 - Python
-
Updated
Jun 23, 2021 - Jupyter Notebook
We keep this issue open to collect feature requests from users and hear your voice. Our monthly release plan is also available here.
You can either:
- Suggest a new feature by leaving a comment.
- Vote for a feature request with
👍 or be against with👎 . (Remember that developers are busy and cannot respond to all feature requests, so vote for your most favorable one!) - Tell us that
-
Updated
Jun 1, 2021 - Python
-
Updated
Jun 26, 2021 - JavaScript
-
Updated
May 25, 2021 - Jupyter Notebook
🚀 Feature
Log non-matching keys when loading checkpoints in non-strict mode.
Motivation
When load from an older checkpoint or partially initialize the model with pre-trained weights, we call the load_from_checkpoint
API with strict=False, but we also want to know which keys are missing and unexpected.
Pitch
When [loading model states](https://github.com/PyTorchLightning/
-
Updated
Jun 26, 2021 - Python
Change tensor.data
to tensor.detach()
due to
pytorch/pytorch#6990 (comment)
tensor.detach()
is more robust than tensor.data
.
-
Updated
Jun 26, 2021 - Python
-
Updated
May 2, 2021
-
Updated
Jun 26, 2021 - C
-
Updated
Jun 24, 2021 - Python
-
Updated
May 16, 2021 - Jupyter Notebook
-
Updated
Jun 26, 2021 - Python
-
Updated
Jun 26, 2021 - Python
-
Updated
Jun 23, 2021 - Python
New Operator
Describe the operator
Why is this operator necessary? What does it accomplish?
This is a frequently used operator in tensorflow/keras
Can this operator be constructed using existing onnx operators?
If so, why not add it as a function?
I don't know.
Is this operator used by any model currently? Which one?
Are you willing to contribute it?
-
Updated
Jun 23, 2021 - Python
Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict
command opens the file and reads lines for the Predictor
. This fails when it tries to load data from my compressed files.
-
Updated
Jun 26, 2021 - Python
-
Updated
Jun 26, 2021 - Python
-
Updated
Jun 23, 2021 - Python
-
Updated
Mar 14, 2021 - Jupyter Notebook
-
Updated
May 2, 2021 - Jupyter Notebook
-
Updated
Jun 7, 2021 - Python
Improve this page
Add a description, image, and links to the pytorch topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the pytorch topic, visit your repo's landing page and select "manage topics."
Add better error message to
HubertForCTC
,Wav2Vec2ForCTC
if labels are bigger than vocab size.Motivation
Following this issue: huggingface/transformers#12264 it is clear that an error message should be thrown if any of the any of the labels are >
self.config.vocab_size
or else silent errors can sneak into the training script.So w