GitLab

* use Repository for push_to_hub

* update readme

* update other flax scripts

* update readme

* update qa example

* fix push_to_hub call

* fix typo

* fix more typos

* update readme

* use abosolute path to get repo name

* fix glue script

* missing requirement

* list both

* add a note about tokenizer

* add  tips to load model is less RAM

* fix link

* fix more links

* Fix length of IterableDatasetShard and add test

* Add comments

* Enable readme link synchronization

* Style

* Reuse regex pattern

* Apply suggestions

* Update

Fix LayoutLM ONNX test error

* Keras callback to push to hub each epoch, or after N steps

* Reworked the callback to use Repository

* Use an Enum for save_strategy

* Style pass

* Correct type for tokenizer

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/keras_callbacks.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding print message to the final upload

* Adding print message to the final upload

* Change how we wait for the last process to finish

* is_done is a property, not a method, derp

* Docstrings and documentation

* Style pass

* Style edit

* Docstring reformat

* Docstring rewrite

* Replacing print with internal logger
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Allows models to be compiled without a loss, and to use the internal loss computations for training with fit()

Co-authored-by: quantitative-technologies <james.hirschorn@quantitative-technologies.com>
Co-authored-by: quantitative-technologies <james.hirschorn@quantitative-technologies.com>

* Fix type annotations for `distributed_concat()`

* Use Any

[Trainer] Make sure shown loss in distributed training is correctly averaged over all workers (#13681)

* push

* improve tr loss gather

* Update run_glue.py

* Update run_glue.py

* Add model creation snippet to other scripts

* Fix style

* Warn for unexpected argument combinations

* Updated the waning message for pad_to_max_length

Fixes #13697

We use `torch.unique` here only to check whether every elements have
the same value.
Therefore, we can use `torch.unique_consecutive` here.

This function eliminates all but the first element from every consecutive
group of equivalent elements.
Like, if we apply this function to `[1, 2, 2, 1]`, it will result in
`[1, 2, 1]`.

As you could see, this is enough for checking whether every elements
have the same value.

Since `torch.unique_consecutive` do less thing, it is much more faster.
On my computer, it is 25x faster on GPU and 15x faster on CPU.

This moves the assertion on checking input dimensions into a block that will only be called if the function is actually going to do chunking forward. This is often not the case at inference time and PyTorch tracing a model with this assertion in it leads to a tracing warning.

TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
  input_tensor.shape[chunk_dim] == tensor_shape for input_tensor in input_tensors

* up

* rename

* add asr example

* add auto feature extractor

* some more fixes

* correct layerdrop

* correct for multi-gpu dist

* clean up

* refactor

* refactor

* more fixes

* more fixes

* clean-up

* finish

* up

* Apply suggestions from code review

* fix isort

* update

* up

* add note

* apply surajs suggestions

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* isort

* small change

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* add hubert

* Update examples/pytorch/speech-recognition/run_speech_recognition_ctc.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>