GitLab

[NumPy] Remove references to deprecated NumPy type aliases.

This change replaces references to a number of deprecated NumPy type aliases (np.bool, np.int, np.float, np.complex, np.object, np.str) with their recommended replacement (bool, int, float, complex, object, str).

NumPy 1.24 drops the deprecated aliases, so we must remove uses before updating NumPy.
Co-authored-by: Peter Hawkins <phawkins@google.com>
Co-authored-by: Peter Hawkins <phawkins@google.com>

Added mask_time_prob and mask_time_length arguments to wav2vec2 pretraining script and readme - new branch

* [run_clm example] add torch_dtype option for model load.
for BLOOM 175B model. peak memory will reduce about 350G for inference. the weight of BLOOM in model hub is bfloat16
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add other type in option

* fix style
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

Update big table
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* [ASR Examples] Update README for seq2seq

* add language info

* add training results

* re-word

* Update reqs to include min gather_for_metrics Accelerate version

* Other reqs

* Init Update

* ClearML Callbacks integration

* update corrections

* args reporting updated

* {'tensorboard': False, 'pytorch': False}

* ClearML Tests added

* add clearml

* output_uri=True in Task.init

* reformatted integrations.py

* reformatted and fixed

* IF-ELSE statement issue on "has_clearml" resolved

* Add clearml in main callback docs

* Add additional clearml documentation

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

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Small change in comments

* Make style clearml

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Victor Sonck <victor.sonck@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

There is typo in the original hyperlink.

Below is the original version:
Based on the script [`run_translation_no_trainer.py`](https://github.com/huggingface/transformers/blob/main/examples/pytorch/translation/**run_translationn_no_trainer.py**).

* merge conflicts

* bos and eos in datacollator

* (temp) hardcode removal of attention mask

* freeze encoder

* actually freeze encoder

* set max length / num beams according to gen kwargs

* (temp) fix tests

* don't pop attn mask

* override return attention mask config from Hub

* Hub configs updated 🤗

* final fixes

* update type annotations

* backward comp

* Only resize embeddings when necessary

* Add comment

* Add CLIP image processor

* Crop size as dict too

* Update warning

* Actually use logger this time

* Normalize doesn't change dtype of input

* Add perceiver image processor

* Tidy up

* Add DPT image processor

* Add Vilt image processor

* Tidy up

* Add poolformer image processor

* Tidy up

* Add LayoutLM v2 and v3 imsge processors

* Tidy up

* Add Flava image processor

* Tidy up

* Add deit image processor

* Tidy up

* Add ConvNext image processor

* Tidy up

* Add levit image processor

* Add segformer image processor

* Add in post processing

* Fix up

* Add ImageGPT image processor

* Fixup

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Add VideoMAE image processor

* Tidy up

* Add ImageGPT image processor

* Fixup

* Add ViT image processor

* Tidy up

* Add beit image processor

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Fix up

* Fix flava and remove tree module

* Fix image classification pipeline failing tests

* Update feature extractor in trainer scripts

* Update pad_if_smaller to accept tuple and int size

* Update for image segmentation pipeline

* Update src/transformers/models/perceiver/image_processing_perceiver.py
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

* Update src/transformers/image_processing_utils.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/beit/image_processing_beit.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* PR comments - docstrings; remove accidentally added resize; var names

* Update docstrings

* Add exception if size is not in the right format

* Fix exception check

* Fix up

* Use shortest_edge in tuple in script
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

Adding the state-of-the-art contrastive search decoding methods for the codebase of generation_utils.py (#19477)

* add: the contrastive search for generaton_utils

* add: testing scripts for contrastive search under examples/text-generation

* update the quality of codes

* revise the docstring; make the generation_contrastive_search.py scripts;

* revise the examples/pytorch/text-generation/run_generation_contrastive_search.py to the auto-APIs format

* revise the necessary documents

* fix: revise the docstring of generation_contrastive_search.py

* Fix the code indentation

* fix: revise the nits and examples in contrastive_search docstring.

* fix the copyright

* delete generation_contrastive_search.py

* revise the logic in contrastive_search

* update the intergration test and the docstring

* run the tests over

* add the slow decorate to the contrastive_search intergrate test

* add more test

* do the style, quality, consistency checks

* [Examples] make default preprocessing_num_workers=1

* [Examples] revert changes in research projects

* fixed typo for SQuAD

* Fixed the preprocess_validation_function function for the labels to reflect the remaining truncated instances

* Rolled back the trainer_seq2seq_qa.py for UnboundLocalError: local variable 'metrics' referenced before assignment
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add multi-node conditions in trainer_qa.py and trainer_seq2seq.py

* Code improvement

Fix link typo of the following content.
PyTorch version, Trainer
PyTorch version, no Trainer

* edit: casting attention_mask to long in DataCollatorCTCWithPadding

* edit: casting attention_mask to long in DataCollatorCTCWithPadding

* Update no_trainer script for summarization

* removed unnecessary import

* fixes notation mistake

* removed: unused variable

* fix args option

* fix trainer eval log

* fix out of memory qa script

* do isort, black, flake

* fix tokenize target

* take it back.

* fix: comment

* Use repo_type instead of deprecated datasets repo IDs

* Add missing one in doc

The overwrite_cache parameter is declared twice.