GitLab

* update `tokenizers` version pin

* force tokenizers>=0.15

* use  0.14
Co-authored-by: Lysandre <lysandre@huggingface.co>

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Co-authored-by: Lysandre <lysandre@huggingface.co>

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

* skip 4 tests

* nits

* style

* wow it's not my day

* skip new failing tests

* style

* skip for NLLB MoE as well

* skip `test_assisted_decoding_sample` for everyone

thoroughly was misspelled thouroughly

* Improve conversion scripts

* Fix paths

* Fix style

* Add tests

* Add integration test

* More improvements

* Fix tests

* Fix style

* Skip gradient checkpointing tests

* Update script

* Remove scripts

* Remove Fuyu from auto mapping

* Fix integration test

* More improvements

* Remove file

* Add Fuyu to slow documentation tests

* Address comments

* Clarify comment

* skip 4 tests

* nits

* style

* wow it's not my day

* skip new failing tests

* style

* skip for NLLB MoE as well

* Add tokens seen

* Address comments, add to TrainingArgs

* Update log

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use self.args

* Fix docstring
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Have seq2seq just use gather

* Change

* Reset after

* Make slow

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Clean

* Simplify and just use gather

* Update tests/trainer/test_trainer_seq2seq.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* gather always for seq2seq

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Minor type annotation fix

* Trigger Build

* Update and reorder docs for chat templates

* Fix Mistral docstring

* Add section link and small fixes

* Remove unneeded line in Mistral example

* Add comment on saving memory

* Fix generation prompts linl

* Fix code block languages

fix exponential doctest

* translate

* translate

* update

The model was merged before final review and approval.

This reverts commit 2ac5b932.

remove wasteful np.stack

Np.stack on large 1-D tensor, causing ~0.5s processing time on short audio (<10s). Compared to 0.02s for medium length audio

* fix speecht5 wrong attention mask when padding

* enable batch generation and add parameter attention_mask

* fix doc

* fix format

* batch postnet inputs, return batched lengths, and consistent to old api

* fix format

* fix format

* fix the format

* fix doc-builder error

* add test, cross attention and docstring

* optimize code based on reviews

* docbuild

* refine

* not skip slow test

* add consistent dropout for batching

* loose atol

* add another test regarding to the consistency of vocoder

* fix format

* refactor

* add return_concrete_lengths as parameter for consistency w/wo batching

* fix review issues

* fix cross_attention issue

fix seamless m4t weights tying

* skip 4 tests

* nits

* style

* wow it's not my day

* `modules_to_save` support for peft integration

* Update docs/source/en/peft.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* slightly elaborate test

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* put back import

* switch to logger.warnings instead

* Initial commit of PatchTST model classes
Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>

* Add PatchTSTForPretraining

* update to include classification
Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>

* clean up auto files

* Add PatchTSTForPrediction

* Fix relative import

* Replace original PatchTSTEncoder with ChannelAttentionPatchTSTEncoder

* temporary adding absolute path + add PatchTSTForForecasting class

* Update base PatchTSTModel + Unittest

* Update ForecastHead to use the config class

* edit cv_random_masking, add mask to model output

* Update configuration_patchtst.py

* add masked_loss to the pretraining

* add PatchEmbeddings

* Update configuration_patchtst.py

* edit loss which considers mask in the pretraining

* remove patch_last option

* Add commits from internal repo

* Update ForecastHead

* Add model weight initilization + unittest

* Update PatchTST unittest to use local import

* PatchTST integration tests for pretraining and prediction

* Added PatchTSTForRegression + update unittest to include label generation

* Revert unrelated model test file

* Combine similar output classes

* update PredictionHead

* Update configuration_patchtst.py

* Add Revin

* small edit to PatchTSTModelOutputWithNoAttention

* Update modeling_patchtst.py

* Updating integration test for forecasting

* Fix unittest after class structure changed

* docstring updates

* change input_size to num_input_channels

* more formatting

* Remove some unused params

* Add a comment for pretrained models

* add channel_attention option

add channel_attention option and remove unused positional encoders.

* Update PatchTST models to use HF's MultiHeadAttention module

* Update paper + github urls

* Fix hidden_state return value

* Update integration test to use PatchTSTForForecasting

* Adding dataclass decorator for model output classes

* Run fixup script

* Rename model repos for integration test

* edit argument explanation

* change individual option to shared_projection

* style

* Rename integration test + import cleanup

* Fix outpu_hidden_states return value

* removed unused mode

* added std, mean and nops scaler

* add initial distributional loss for predition

* fix typo in docs

* add generate function

* formatting

* add num_parallel_samples

* Fix a typo

* copy weighted_average function, edit PredictionHead

* edit PredictionHead

* add distribution head to forecasting

* formatting

* Add generate function for forecasting

* Add generate function to prediction task

* formatting

* use argsort

* add past_observed_mask ordering

* fix arguments

* docs

* add back test_model_outputs_equivalence test

* formatting

* cleanup

* formatting

* use ACT2CLS

* formatting

* fix add_start_docstrings decorator

* add distribution head and generate function to regression task

add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput,  PatchTSTForRegressionOutput.

* add distribution head and generate function to regression task

add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput,  PatchTSTForRegressionOutput.

* fix typos

* add forecast_masking

* fixed tests

* use set_seed

* fix doc test

* formatting

* Update docs/source/en/model_doc/patchtst.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* better var names

* rename PatchTSTTranspose

* fix argument names and docs string

* remove compute_num_patches and unused class

* remove assert

* renamed to PatchTSTMasking

* use num_labels for classification

* use num_labels

* use default num_labels from super class

* move model_type after docstring

* renamed PatchTSTForMaskPretraining

* bs -> batch_size

* more review fixes

* use hidden_state

* rename encoder layer and block class

* remove commented seed_number

* edit docstring

* Add docstring

* formatting

* use past_observed_mask

* doc suggestion

* make fix-copies

* use Args:

* add docstring

* add docstring

* change some variable names and add PatchTST before some class names

* formatting

* fix argument types

* fix tests

* change x variable to patch_input

* format

* formatting

* fix-copies

* Update tests/models/patchtst/test_modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* move loss to forward

* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* formatting

* fix a bug when pre_norm is set to True

* output_hidden_states is set to False as default

* set pre_norm=True as default

* format docstring

* format

* output_hidden_states is None by default

* add missing docs

* better var names

* docstring: remove default to False in output_hidden_states

* change labels name to target_values in regression task

* format

* fix tests

* change to forecast_mask_ratios and random_mask_ratio

* change mask names

* change future_values to target_values param in the prediction class

* remove nn.Sequential and make PatchTSTBatchNorm class

* black

* fix argument name for prediction

* add output_attentions option

* add output_attentions to PatchTSTEncoder

* formatting

* Add attention output option to all classes

* Remove PatchTSTEncoderBlock

* create PatchTSTEmbedding class

* use config in PatchTSTPatchify

* Use config in PatchTSTMasking class

* add channel_attn_weights

* Add PatchTSTScaler class

* add output_attentions arg to test function

* format

* Update doc with image patchtst.md

* fix-copies

* rename Forecast <-> Prediction

* change name of a few parameters to match with PatchTSMixer.

* Remove *ForForecasting class to match with other time series models.

* make style

* Remove PatchTSTForForecasting in the test

* remove PatchTSTForForecastingOutput class

* change test_forecast_head to test_prediction_head

* style

* fix docs

* fix tests

* change num_labels to num_targets

* Remove PatchTSTTranspose

* remove arguments in PatchTSTMeanScaler

* remove arguments in PatchTSTStdScaler

* add config as an argument to all the scaler classes

* reformat

* Add norm_eps for batchnorm and layernorm

* reformat.

* reformat

* edit docstring

* update docstring

* change variable name pooling to pooling_type

* fix output_hidden_states as tuple

* fix bug when calling PatchTSTBatchNorm

* change stride to patch_stride

* create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder

* formatting

* initialize scalers with configs

* edit output_hidden_states

* style

* fix forecast_mask_patches doc string

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Co-authored-by: Gift Sinthong <gift.sinthong@ibm.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
Co-authored-by: Wesley M. Gifford <wmgifford@us.ibm.com>
Co-authored-by: nnguyen <nnguyen@us.ibm.com>
Co-authored-by: Ngoc Diep Do <diiepy@gmail.com>
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Update pipelines.md

* translate perrf_torch_compile.md

* translate tf_xla.md

* update

addresses todo for awq tests

* Improve pipeline tokenizer loading and hope nothing breaks

* Let's try a hacky solution

* Revert the changes to init

* Add a falcon hack to the automapping

* Add a falcon hack to the automapping

* Add version check for Jinja

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make fixup

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* First draft

* Fix style

* More improvements

* Fix tests

* Fix tests

* Convert checkpoint

* Improve DPTImageProcessor

* Remove scripts, improve conversion script

* Remove print statements

* Fix test

* Improve docstring

* More improvements

* Fix style

* Fix image processor

* Add tests

* Address comments

* Address comments

* Make bias backwards compatible

* Address comment

* Address comment

* Address comment

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Address comments

* Add flag

* Add tests

* Make tests smaller

* Use regular BackboneOutput

* Fix all tests

* Update test

* Convert more checkpoints

* Convert giant checkpoints, add integration test

* Rename size_divisibility to size_divisor

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

Docstring entry for `gradient_checkpointing_kwargs` was
`gradient_checkpointing_args`. This is incorrect.

* OWLv2: bug fix in post_process_object_detection() when using cuda device

* fix copies issue by fixing original function in owlvit

* Fix

* Tests

* Fix

* Default to msgpack for safetensors

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add droppouts

* add the dropout

* add doc in the config

* nits

* fix mistral config

* nits

* don't use `use_auth_token`internally

* let's use token everywhere

* fixup

"past key much have a shape" -> "past key must have a shape"

* fix

* fix

* fix

* fix

* fix

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

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