🚀 Feature request

Make CLIPFeatureExtractor (or any FeatureExtractor in general) accept batch of images as torch.Tensor.

Motivation

Currently batch of images as torch.Tensor are not treated as a batch, it has to be a List[torch.Tensor] but it is not the case when using native Pytorch DataLoader. Can we update this line so that it accepts batches as torch.Tensor. Maybe we ca

🚀 Feature

When evaluation trainer.validate(verbose=True) (or test) finishes, we print a dictionary with the results obtained

--------------------------------------------------------------------------------
DATALOADER:0 TEST RESULTS
{'test_loss': -3.4134674072265625}
--------------------------------------------------------------------------------

https://github.co

🙌🙌🙌🙌🙌

Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

🚀 Feature

Motivation

paper "LEARNING TO REPRESENT PROGRAMS WITH GRAPHS" which encode computer programs as graphs, with rich semantic information, however, most code implementation on this dataset VarMisuse is based on TensorFlow, like [tf-gnn-samples](https://github.com/microsof

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?

Motivated by huggingface/transformers#12789 in Transformers, one welcoming change would be replacing assertions with proper exceptions. The only type of assertions we should keep are those used as sanity checks.

Currently, there is a total of 87 files with the assert statements (located under datasets and src/datasets), so when working on this, to manage the PR s

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.