transformers/docs/source/main_classes/data_collator.rst
Matt 854260ca44
TF/Numpy variants for all DataCollator classes (#13105)
* Adding a TF variant of the DataCollatorForTokenClassification to get feedback

* Added a Numpy variant and a post_init check to fail early if a missing import is found

* Fixed call to Numpy variant

* Added a couple more of the collators

* Update src/transformers/data/data_collator.py

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

* Fixes, style pass, finished DataCollatorForSeqToSeq

* Added all the LanguageModeling DataCollators, except SOP and PermutationLanguageModeling

* Adding DataCollatorForPermutationLanguageModeling

* Style pass

* Add missing `__call__` for PLM

* Remove `post_init` checks for frameworks because the imports inside them were making us fail code quality checks

* Remove unused imports

* First attempt at some TF tests

* A second attempt to make any of those tests actually work

* TF tests, round three

* TF tests, round four

* TF tests, round five

* TF tests, all enabled!

* Style pass

* Merging tests into `test_data_collator.py`

* Merging tests into `test_data_collator.py`

* Fixing up test imports

* Fixing up test imports

* Trying shuffling the conditionals around

* Commenting out non-functional old tests

* Completed all tests for all three frameworks

* Style pass

* Fixed test typo

* Style pass

* Move standard `__call__` method to mixin

* Rearranged imports for `test_data_collator`

* Fix data collator typo "torch" -> "pt"

* Fixed the most embarrassingly obvious bug

* Update src/transformers/data/data_collator.py

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

* Renaming mixin

* Updating docs

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
Co-authored-by: Andrew Romans <andrew.romans@hotmail.com>
2021-08-31 13:06:48 +01:00

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..
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
Data Collator
-----------------------------------------------------------------------------------------------------------------------
Data collators are objects that will form a batch by using a list of dataset elements as input. These elements are of
the same type as the elements of :obj:`train_dataset` or :obj:`eval_dataset`.
To be able to build batches, data collators may apply some processing (like padding). Some of them (like
:class:`~transformers.DataCollatorForLanguageModeling`) also apply some random data augmentation (like random masking)
on the formed batch.
Examples of use can be found in the :doc:`example scripts <../examples>` or :doc:`example notebooks <../notebooks>`.
Default data collator
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autofunction:: transformers.data.data_collator.default_data_collator
DataCollatorWithPadding
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorWithPadding
:members:
DataCollatorForTokenClassification
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorForTokenClassification
:members:
DataCollatorForSeq2Seq
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorForSeq2Seq
:members:
DataCollatorForLanguageModeling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorForLanguageModeling
:members: numpy_mask_tokens, tf_mask_tokens, torch_mask_tokens
DataCollatorForWholeWordMask
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorForWholeWordMask
:members: numpy_mask_tokens, tf_mask_tokens, torch_mask_tokens
DataCollatorForPermutationLanguageModeling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.data.data_collator.DataCollatorForPermutationLanguageModeling
:members: numpy_mask_tokens, tf_mask_tokens, torch_mask_tokens