* Added support for seed in `DataCollatorForWholeWordMask`, and also wrote tests.
Also fixed bugs where the code hardcoded values for mask replacement probability and random replacement probability, instead of using the values passed by the user.
* formatting issues
* Used better way to generate seed in TF. Made tests more consistent.
Fixed 2 issues regarding `tests/trainer/test_data_collator.py::TFDataCollatorIntegrationTest::test_all_mask_replacement`:
1. I got the error `RuntimeError: "bernoulli_tensor_cpu_p_" not implemented for 'Long'`. This is because the `mask_replacement_prob=1` and `torch.bernoulli` doesn't accept this type (which would be a `torch.long` dtype instead. I fixed this by manually casting the probability arguments in the `__post_init__` function of `DataCollatorForLanguageModeling`.
2. I also got the error `tensorflow.python.framework.errors_impl.InvalidArgumentError: cannot compute Equal as input #1(zero-based) was expected to be a int64 tensor but is a int32 tensor [Op:Equal]` due to the line `tf.reduce_all((batch["input_ids"] == inputs) | (batch["input_ids"] == tokenizer.mask_token_id))` in `test_data_collator.py`. This occurs because the type of the `inputs` variable is `tf.int32`. Solved this by manually casting it to `tf.int64` in the test, as the expected return type of `batch["input_ids"]` is `tf.int64`.
* DataCollatorForLanguageModeling class was updated with new parameters that provides more control over the token masking and relacing
* DataCollatorForLanguageModeling class was updated with new parameters that provides more control over the token masking and relacing
* Addressed review comments, modified the docstring and made a test for the DataCollatorForLanguageModeling
* kinda works
* update
* add tests
* update
* use special tokens in processors
* typo
* fix copies
* fix
* fix moshi after rebase
* update
* fix tests
* update
* Update docs/source/en/main_classes/tokenizer.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* update docs
* test for load time adding tokens
* fix some more tests which are now fetched better
* one more fix
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add DataCollatorBatchFlattening
* Update data_collator.py
* change name
* new FA2 flow if position_ids is provided
* add comments
* minor fix
* minor fix data collator
* add test cases for models
* add test case for data collator
* remove extra code
* formating for ruff check and check_repo.py
* ruff format
ruff format tests src utils
* custom_init_isort.py
* immutability fix for seq2seq as well as immutability tests for the collators
* ensure we don't act on none labels and formatting
* remove tf/pt in respective tests as they are not required
* more type error fixes tf/np
* remove todo
* apply suggestions from code review
* formatting / style
* fix seq2seq data collator to respect the given padding strategy
further added tests for the seq2seq data collator in the style of the `data_collator_for_token_classification` (pt, tf, np)
* formatting and change bool equals "==" to "is"
* add missed return types in tests
* update numpy test as it can handle unequal shapes, not like pt or tf
