GitLab

* Revert "Add tie_weights() to LM heads and set bias in set_output_embeddings() (#28948)"

This reverts commit 725f4ad1.

* Revert "Patch to skip failing `test_save_load_low_cpu_mem_usage` tests (#29043)"

This reverts commit 4156f517.

* Script & Manual edition

* Update

* Add tie_weights() to LM heads and set bias in set_output_embeddings()

The bias were not tied correctly in some LM heads, and this change should fix that.

* Moving test_save_and_load_low_cpu_mem_usage to ModelTesterMixin

* Adding _tie_weights() to MPNet and Vilt

* Skip test for low cpu mem usage for Deta/DeformableDetr since they cannot init on meta device

* Rename to test name to save_load to match the convention

* fix

* more fixes

* fix other models

* fix long t5

* use `gradient_checkpointing_func` instead

* fix copies

* set `gradient_checkpointing_func` as a private attribute and retrieve previous behaviour

* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* replace it with `is_gradient_checkpointing_set`

* remove default

* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fixup

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

* v1

* fix

* remove `create_custom_forward`

* fixup

* fixup

* add test and fix all failing GC tests

* remove all remaining `create_custom_forward` methods

* fix idefics bug

* fixup

* replace with `__call__`

* add comment

* quality

In assisted decoding, pass model_kwargs to model's forward call (fix prepare_input_for_generation in all models) (#25242)

* In assisted decoding, pass model_kwargs to model's forward call

Previously, assisted decoding would ignore any additional kwargs
that it doesn't explicitly handle. This was inconsistent with other
generation methods, which pass the model_kwargs through
prepare_inputs_for_generation and forward the returned dict to the
model's forward call.

The prepare_inputs_for_generation method needs to be amended in all
models, as previously it only kept the last input ID when a past_key_values
was passed.

* Improve variable names in _extend_attention_mask

* Refactor extending token_type_ids into a function

* Replace deepcopy with copy to optimize performance

* Update new persimmon model with llama changes for assisted generation

* Update new mistral model for assisted generation with prepare_inputs_for_generation

* Update position_ids creation in falcon prepare_inputs_for_generation to support assisted generation

* Fix GPTNeoX beam search when using parallelize

* Fix beam search idx device when using model parallel

* remove onnx related stuff
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix: move test_beam_search_on_multi_gpu to GenerationTesterMixin

* fix: add right item to _no_split_modules of MegaPreTrainedModel

* fix: add num_beams within parallelized beam_search test
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* Add attention mask and pad token warning to many of the models

* Remove changes under examples/research_projects

These files are not maintained by HG.

* Skip the warning check during torch.fx or JIT tracing

* Switch ordering for the warning and input shape assignment

This ordering is a little cleaner for some of the cases.

* Add missing line break in one of the files

* Changed AssertionError to ValueError

try-except block was using AssesrtionError in except statement while the expected error is value error. Fixed the same.

* Changed AssertionError to ValueError

try-except block was using AssesrtionError in except statement while the expected error is ValueError. Fixed the same.
Note: While raising the ValueError args are passed to it, but later added again while handling the error (See the code snippet)

* Changed AssertionError to ValueError

try-except block was using AssesrtionError in except statement while the expected error is ValueError. Fixed the same.
Note: While raising the ValueError args are passed to it, but later added again while handling the error (See the code snippet)

* Changed AssertionError to ValueError

* Changed AssertionError to ValueError

* Changed AssertionError to ValueError

* Changed AssertionError to ValueError

* Changed AssertionError to ValueError

* Changed assert statement to ValueError based

* Changed assert statement to ValueError based

* Changed assert statement to ValueError based

* Changed incorrect error handling from AssertionError to ValueError

* Undoed change from AssertionError to ValueError as it is not needed

* Reverted back to using AssertionError as it is not necessary to make it into ValueError

* Fixed erraneous comparision

Changed == to !=

* Fixed erraneous comparision

Changed == to !=

* formatted the code

* Ran make fix-copies

* Adding warning messages to BERT for missing attention masks

These warning messages when there are pad tokens within the input ids and
no attention masks are given. The warning message should only show up once.

* Adding warning messages to BERT for missing attention masks

These warning messages are shown when the pad_token_id is not None
and no attention masks are given. The warning message should only
show up once.

* Ran fix copies to copy over the changes to some of the other models

* Add logger.warning_once.cache_clear() to the test

* Shows warning when there are no attention masks and input_ids start/end with pad tokens

* Using warning_once() instead and fix indexing in input_ids check

---------
Co-authored-by: JB Lau <hckyn@voyager2.local>

* Preliminary work on some models

* Fix test load missing and make sure nonpersistent buffers are tested

* Always ignore nonpersistent buffers if in state_dict

* Treat models

* More models

* Treat remaining models

* Fix quality

* Fix tests

* Remove draft

* This test is not needed anymore

* Fix copies

* Fix last test

* Newly added models

* Fix last tests

* Address review comments

Revert "Fix gradient checkpointing + fp16 autocast for most models (#24247)"

This reverts commit 285a4801.

* fix gc bug

* continue PoC on OPT

* fixes

* :exploding_head:

* fix tests

* remove pytest.mark

* fixup

* forward contrib credits from discussions

* forward contrib credits from discussions

* reverting changes on untouched files.

---------
Co-authored-by: zhaoqf123 <zhaoqf123@users.noreply.github.com>
Co-authored-by: 7eu7d7 <7eu7d7@users.noreply.github.com>

* First test

* Add info for all models

* style

* Repo consistency

* Fix last model and cleanup prints

* Repo consistency

* Use consistent function for detecting tied weights

Co-authored-by: saswatmeher <saswatmeher@cse.iitb.ac.in>

* logger.warning_once

* style

* fix past renamed to past_key_value

* update more `past`that were ski^êd

* fixup

* remove changes made to rag

* refactor `_reorder_cache` to use `past_key_values`

* fix git `prepare_inputs_for_generation` to pass tests when false is needed in use_cache

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* Clean all models

* Style

* Last to remove

* address review comments

* Address review comments

* Rework automatic code samples in docstrings

* ImageProcessor->AutoImageProcessor

* Add models to fix copies

* Last typos

* A couple more models

* Fix copies

* start cleanup

* more updates

* more models are affected

* more updates

* update generation utils

* style

* revert change that removed reorder cachce

* update generation utils

* style

* style

* remove reorder cache

* update relative positional embedding

* make fix copies

* add `use_cache` to list of arguments

* fixup

* 1line fucntion

* add `test_decoder_model_past_with_large_inputs_relative_pos_emb`

* add relative pos embedding test for more models

* style

* Attempting to test automatically the `_keys_to_ignore`.

* Style.

* First fix pass.

* Moving test on its own.

* Another batch.

* Second round removing BatchNorm

* Fixing layoutlmv{2,3} + support older Python.

* Disable miss missing warning.

* Removing dodgy additions.

* Big pass.

* mbart.

* More corrections.

* Fixup.

* Updating test_correct_missing_keys

* Add escape hatch for when the head has no extra params so doesn't need

the missing keys check.

* Fixing test.

* Greener.

* Green ! (except for weird splinter bug).

* Adding a test about `named_parameters` usage.

* Shorten message.

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* After rebase modifications.

* More explicit condition checking.

* Fixing slow tests issues.

* Remove extra pdb.

* Remove print.

* Attempt to make failure consistent + fixing roc_bert.

* Removing the seed  (all tests passing with it).
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Comparisons like
version.parse(torch.__version__) > version.parse("1.6")
are True for torch==1.6.0+cu101 or torch==1.6.0+cpu

version.parse(version.parse(torch.__version__).base_version) are preferred (and available in pytorch_utils.py

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* Type hint complete Albert model file.

* Update typing.

* Update src/transformers/models/albert/modeling_albert.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Moved functions to pytorch_utils.py

* isort formatting

* Reverted tf changes

* isort, make fix-copies

* documentation fix

* Fixed Conv1D import

* Reverted research examples file

* backward compatibility for pytorch_utils

* missing import

* isort fix

* Add doctest BERT

* make fixup

* fix typo

* change checkpoints

* make fixup

* define doctest output value, update doctest for mobilebert

* solve fix-copies

* update QA target start index and end index

* change checkpoint for docs and reuse defined variable

* Update src/transformers/models/bert/modeling_tf_bert.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* make fixup
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* make tuple annotation more specific to avoid failures during symbolic_trace

* make tuple annotation more specific to avoid failures during symbolic_trace

* Big file_utils cleanup

* This one still needs to be treated separately

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* undo black autoformat

* minor fix to rembert forward with default

* make fix-copies, make quality

* Adding types to template model

* Removing List from the template types

* Remove `Optional` from a couple of types that don't accept `None`
Co-authored-by: matt <rocketknight1@gmail.com>

* Add type annotations for BERT and copies

* make fixup

* Change the way tracing happens, enabling dynamic axes out of the box

* Update the tests and modeling xlnet

* Add the non recoding of leaf modules to avoid recording more values for the methods to record than what will be seen at tracing time (which would otherwise desynchronize the recorded values and the values that need to be given to the proxies during tracing, causing errors).

* Comments and making tracing work for gpt-j and xlnet

* Refactore things related to num_choices (and batch_size, sequence_length)

* Update fx to work on PyTorch 1.10

* Postpone autowrap_function feature usage for later

* Add copyrights

* Remove unnecessary file

* Fix issue with add_new_model_like

* Apply suggestions

* Fix loss calculation in TFFunnelForTokenClassification

* revert the change in TFFunnelForTokenClassification

* fix FunnelForTokenClassification loss

* fix other TokenClassification loss

* fix more

* fix more

* add num_labels to ElectraForTokenClassification

* revert the change to research projects
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix bad examples

* Add black formatting to style_doc

* Use first nonempty line

* Put it at the right place

* Don't add spaces to empty lines

* Better templates

* Deal with triple quotes in docstrings

* Result of style_doc

* Enable mdx treatment and fix code examples in MDXs

* Result of doc styler on doc source files

* Last fixes

* Break copy from

* New doc styler

* Fix issue with args at the start

* Code sample fixes

* Style code examples in MDX

* Fix more patterns

* Typo

* Typo

* More patterns

* Do without black for now

* Get more info in error

* Docstring style

* Re-enable check

* Quality

* Fix add_end_docstring decorator

* Fix docstring

* Convert file_utils docstrings to Markdown

* Test on BERT

* Return block indent

* Temporarily disable doc styler

* Remove from quality checks as well

* Remove doc styler mess

* Remove check from circleCI

* Fix typo

* Convert file_utils docstrings to Markdown

* Test on BERT

* Return block indent

* Temporarily disable doc styler

* Remove from quality checks as well

* Remove doc styler mess

* Remove check from circleCI

* Fix typo

* Let's go on all other model files

* Add templates too

* Styling and quality