* Initial addition of t5forsequenceclassification
* Adding imports and adding tests
* Formatting
* Running make fix-copies
* Adding mt5forseq
* Formatting
* run make fix-copies
* Adding to docs
* Add model_parallel
* Fix bug
* Fix
* Remove TODO
* Fixing tests for T5ForSequenceClassification
* Undo changes to dependency_versions_table.py
* Change classification head to work with T5Config directly
* Change seq length to let tests pass
* PR comments for formatting
* Formatting
* Initial addition of UMT5ForSequenceClassification
* Adding to inits and formatting
* run make fix-copies
* Add doc for UMT5ForSeqClass
* Update UMT5 config
* Fix docs
* Skip torch fx test for SequenceClassification
* Formatting
* Add skip to UMT5 tests as well
* Fix umt5 tests
* Running make fix-copies
* PR comments
* Fix for change to sentence_representation
* Rename seq_len to hidden_size since that's what it is
* Use base_model to follow format of the rest of the library
* Update docs
* Extract the decoder_input_ids changes and make one liner
* Make one-liner
* pull and push updates
* add docs
* fix modeling
* Add and run test
* make copies
* add task
* fix tests and fix small issues
* Checks on a Pull Request
* fix docs
* add desc pvt.md
* Resolve typo in check_repo.py
* Specify encoding when opening modeling files
* Deprecate the OpenLlama architecture
* Add disclaimer pointing to Llama
I'm open to different wordings here
* Match the capitalisation of LLaMA
* add llama
* add other readmes
* update padding id in readme
* add link to paper
* fix paths and tokenizer
* more nits
* styling
* fit operation in 2 lines when possible
* nits
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add form
* update reademe
* update readme, we don't have a default pad token
* update test and tokenization
* LLaMA instead of Llama
* nits
* add expected text
* add greeedy output
* styling
* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* sequential device map
* skip relevant changes
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* first raw version of the bark integration
* working code on small models with single run
* add converting script from suno weights 2 hf
* many changes
* correct past_kv output
* working implementation for inference
* update the converting script according to the architecture changes
* add a working end-to-end inference code
* remove some comments and make small changes
* remove unecessary comment
* add docstrings and ensure no unecessary intermediary output during audio generation
* remove done TODOs
* make style + add config docstrings
* modification for batch inference support on the whole model
* add details to .generation_audio method
* add copyright
* convert EncodecModel from original library to transformers implementation
* add two class in order to facilitate model and sub-models loading from the hub
* add support of loading the whole model
* add BarkProcessor
* correct modeling according to processor output
* Add proper __init__ and auto support
* Add up-to-date copyright/license message
* add relative import instead of absolute
* cleaner head_dim computation
* small comment removal or changes
* more verbose LayerNorm init method
* specify eps for clearer comprehension
* more verbose variable naming in the MLP module
* remove unecessary BarkBlock parameter
* clearer code in the forward pass of the BarkBlock
* remove _initialize_modules method for cleaner code
* Remove unnecessary methods from sub-models
* move code to remove unnecessary function
* rename a variable for clarity and change an assert
* move code and change variable name for clarity
* remove unnecessary asserts
* correct small bug
* correct a comment
* change variable names for clarity
* remove asserts
* change import from absolute to relative
* correct small error due to comma missing + correct import
* Add attribute Bark config
* add first version of tests
* update attention_map
* add tie_weights and resize_token_embeddings for fineModel
* correct getting attention_mask in generate_text_semantic
* remove Bark inference trick
* leave more choices in barkProcessor
* remove _no_split_modules
* fixe error in forward of block and introduce clearer notations
* correct converting script with last changes
* make style + add draft bark.mdx
* correct BarkModelTest::test_generate_text_semantic
* add Bark in main README
* add dummy_pt_objects for Bark
* add missing models in the main init
* correct test_decoder_model_past_with_large_inputs
* disable torchscript test
* change docstring of BarkProcessor
* Add test_processor_bark
* make style
* correct copyrights
* add bark.mdx + make style, quality and consistency
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Remove unnecessary test method
* simply logic of a test
* Only check first ids for slow audio generation
* split full end-to-end generation tests
* remove unneccessary comment
* change submodel names for clearer naming
* remove ModuleDict from modeling_bark
* combine two if statements
* ensure that an edge misued won't happen
* modify variable name
* move code snippet to the right place (coarse instead of semantic)
* change BarkSemanticModule -> BarkSemanticModel
* align BarkProcessor with transformers paradigm
* correct BarkProcessor tests with last commit changes
* change _validate_voice_preset to an instance method instead of a class method
* tie_weights already called with post_init
* add codec_model config to configuration
* update bark modeling tests with recent BarkProcessor changes
* remove SubModelPretrainedModel + change speakers embeddings prompt type in BarkModel
* change absolute imports to relative
* remove TODO
* change docstrings
* add examples to docs and docstrings
* make style
* uses BatchFeature in BarkProcessor insteads of dict
* continue improving docstrings and docs + make style
* correct docstrings examples
* more comprehensible speaker_embeddings load/Save
* rename speaker_embeddings_dict -> speaker_embeddings
* correct bark.mdx + add bark to documentation_tests
* correct docstrings configuration_bark
* integrate last nit suggestions
* integrate BarkGeneration configs
* make style
* remove bark tests from documentation_tests.txt because timeout - tested manually
* add proper generation config initialization
* small bark.mdx documentation changes
* rename bark.mdx -> bark.md
* add torch.no_grad behind BarkModel.generate_audio()
* replace assert by ValueError in convert_suno_to_hf.py
* integrate a series of short comments from reviewer
* move SemanticLogitsProcessors and remove .detach() from Bark docs and docstrings
* actually remove SemanticLogitsProcessor from modeling_bark.oy
* BarkProcessor returns a single output instead of tuple + correct docstrings
* make style + correct bug
* add initializer_range to BarkConfig + correct slow modeling tests
* add .clone() to history_prompt.coarse_prompt to avoid modifying input array
* Making sure no extra "`" are present
* remove extra characters in modeling_bark.py
* Correct output if history_prompt is None
* remove TODOs
* remove ravel comment
* completing generation_configuration_bark.py docstrings
* change docstrings - number of audio codebooks instead of Encodec codebooks
* change 'bias' docstrings in configuration_bark.py
* format code
* rename BarkModel.generate_audio -> BarkModel.generate_speech
* modify AutoConfig instead of EncodecConfig in BarkConfig
* correct AutoConfig wrong init
* refactor BarkModel and sub-models generate_coarse, generate_fine, generate_text_semantic
* remove SemanticLogitsProcessor and replace it with SuppressTokensLogitsProcessor
* move nb_codebook related config arguments to BarkFineConfig
* rename bark.mdx -> bark.md
* correcting BarkModelConfig from_pretrained + remove keys_to_ignore
* correct bark.md with correct hub path
* correct code bug in bark.md
* correct list tokens_to_suppress
* modify Processor to load nested speaker embeddings in a safer way
* correct batch sampling in BarkFineModel.generate_fine
* Apply suggestions from code review
Small docstrings correction and code improvements
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* give more details about num_layers in docstrings
* correct indentation mistake
* correct submodelconfig order of docstring variables
* put audio models in alphabetical order in utils/check_repo.my
* remove useless line from test_modeling_bark.py
* makes BarkCoarseModelTest inherits from (ModelTesterMixin, GenerationTesterMixin, unittest.TestCase) instead of BarkSemanticModelTest
* make a Tester class for each sub-model instead of inheriting
* add test_resize_embeddings=True for Bark sub-models
* add Copied from transformers.models.gpt_neo.modeling_gpt_neo.GPTNeoSelfAttention._split_heads
* remove 'Copied fom Bark' comment
* remove unneccessary comment
* change np.min -> min in modeling_bark.py
* refactored all custom layers to have Bark prefix
* add attention_mask as an argument of generate_text_semantic
* refactor sub-models start docstrings to have more precise config class definition
* move _tied_weights_keys overriding
* add docstrings to generate_xxx in modeling_bark.py
* add loading whole BarkModel to convert_suno_to_hf
* refactor attribute and variable names
* make style convert_suno
* update bark checkpoints
* remove never entered if statement
* move bark_modeling docstrings after BarkPretrainedModel class definition
* refactor modeling_bark.py: kv -> key_values
* small nits - code refactoring and removing unecessary lines from _init_weights
* nits - replace inplace method by variable assigning
* remove *optional* when necessary
* remove some lines in generate_speech
* add default value for optional parameter
* Refactor preprocess_histories_before_coarse -> preprocess_histories
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* correct usage after refactoring
* refactor Bark's generate_xxx -> generate and modify docstrings and tests accordingly
* update docstrings python in configuration_bark.py
* add bark files in utils/documentation_test.txt
* correct docstrings python snippet
* add the ability to use parameters in the form of e.g coarse_temperature
* add semantic_max_new_tokens in python snippet in docstrings for quicker generation
* Reformate sub-models kwargs in BakModel.generate
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* correct kwargs in BarkModel.generate
* correct attention_mask kwarg in BarkModel.generate
* add tests for sub-models args in BarkModel.generate and correct BarkFineModel.test_generate_fp16
* enrich BarkModel.generate docstrings with a description of how to use the kwargs
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Initial commit
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleanup config docstring
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Convert to relative imports
* Remove torch < 1.8 warning
* Restructure cos_sin header
* qkv -> query, key, value
* Refactor attention calculation
* Add a couple of config variables to account for the different checkpoints
* Successful merging of the code paths!
* Fix misplaced line in the non-parallel attention path
* Update config and tests
* Add a pad_token_id when testing
* Support output_attentions when alibi is None
* make fixup
* Skip KV cache shape test
* No more _keys_to_ignore_on_load_missing
* Simplify self attention a bit
* Simplify self attention a bit
* make fixup
* stash commit
* Some more attention mask updates
* Should pass all tests except assisted generation!
* Add big model generation test
* make fixup
* Add temporary workaround for test
* Test overrides for assisted generation
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Test overrides for assisted generation
* Add generation demo
* Update copyright
* Make the docstring model actually small
* Add module-level docstring
* Remove all assertions
* Add copied from bloom
* Reformat the QKV layer
* Add copied from bloom
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Remove unused line and reformat
* No single letter variables
* Cleanup return names
* Add copied from line
* Remove the deprecated arguments blocks
* Change the embeddings test to an alibi on/off test
* Remove position_ids from FalconForQA
* Remove old check for token type IDs
* Fix the alibi path when multi_query is False
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update config naming
* Fix typo for new_decoder_architecture
* Add some comments
* Fix docstring
* Fix docstring
* Create range in the right dtype from the start
* Review comment cleanup
* n_head_kv -> num_kv_heads
* self.alibi -> self.use_alibi
* self.num_kv -> self.num_kv_heads
* Reorder config args
* Made alibi arguments Optional
* Add all model docstrings
* Add extra checkpoints
* Add author info for Falcon
* Stop removing token_type_ids because our checkpoints shouldn't return it anymore
* Add one hopeful comment for the future
* Fix typo
* Update tests, fix cache issue for generation
* Use -1e9 instead of -inf to avoid float overflow
* Recompute the rotary embeddings much less often
* Re-enable disabled tests
* One final fix to attention mask calculation, and update tests
* Cleanup targeting falcon-40b equivalency
* Post-rebase docs update
* Update docstrings, especially in the config
* More descriptive variable names, and comments where we can't rename them
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Squash 88 commits
* Use markdown
* Remove mdx files due to bad rebase
* Fix modeling files due to bad rebase
* Fix style
* Update comment
* fix
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Add tf code for efficientformer
* Fix return dict bug - return last hidden state after last stage
* Fix corresponding return dict bug
* Override test tol
* Change default values of training to False
* Set training to default False X3
* Rm axis from ln
* Set init in dense projection
* Rm debug stuff
* Make style; all tests pass.
* Modify year to 2023
* Fix attention biases codes
* Update the shape list logic
* Add a batch norm eps config
* Remove extract comments in test files
* Add conditional attn and hidden states return for serving output
* Change channel dim checking logic
* Add exception for withteacher model in training mode
* Revert layer count for now
* Add layer count for conditional layer naming
* Transpose for conv happens only in main layer
* Make tests smaller
* Make style
* Update doc
* Rm from_pt
* Change to actual expect image class label
* Remove stray print in tests
* Update image processor test
* Remove the old serving output logic
* Make style
* Make style
* Complete test
* First commit
* Add auto-translation with GPT-4
* make fixup
* Add a functional layernorm for TF
* Add all the auxiliary imports etc.
* Add the extra processor and tests
* rebase to main
* Add all the needed fixes to the GPT code
* make fixup
* Make convolutions channels-last so they run on CPU
* make fixup
* Fix final issues
* Fix other models affected by test change
* Clarify comment on the sparse_prompt_embeddings check
* Refactor functional_layernorm, use shape_list in place of .shape in some places
* Remove deprecated torch-alike code
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Refactor processor with common methods and separated private methods
* make fixup
* Quietly delete the file that didn't do anything (sorry Sylvain)
* Refactor the processor tests into one file
* make fixup
* Clean up some unnecessary indirection
* Fix TF mask postprocessing
* Add more processor equivalence tests
* Refactor generate_crop_boxes to use framework-neutral np code
* Make the serving output correctly conditional
* Fix error message line length
* Use dict keys rather than indices internally in both TF and PT SAM call/forward
* Return dicts internally in the call/forward methods
* Revert changes to common tests and just override check_pt_tf_outputs
* Revert changes to other model tests
* Clarify comments for functional layernorm
* Add missing transpose from PT code
* Removed unused copied from in PT code
* Remove overrides for tests that don't exist in TF
* Fix transpose and update tests for PT and TF to check pred_masks
* Add training flag
* Update tests to use TF checkpoints
* Update index.mdx
* Add missing cross-test decorator
* Remove optional extra asterisks
* Revert return_dict changes in PT code
* Update src/transformers/models/sam/modeling_tf_sam.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Remove None return annotations on init methods
* Update tests/models/sam/test_processor_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix input_boxes shapes
* make fixup
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* First draft of RWKV-4
* Add support for generate
* Style post-rebase
* Properly use state
* Write doc
* Fix doc
* More math
* Add model to README, dummies and clean config
* Fix init
* multiple fixes:
- fix common tests
- fix configuraion default values
- add CI test for checking state computation
- fix some CI tests
* correct tokenizer
* some tweaks
- fix config docstring
- fix failing tests
* fix CI tests
- add output_attention / output_hidden_states
- override test_initialization
- fix failing CIs
* fix conversion script
- fix sharded case
- add new arguments
* add slow tests + more fixes on conversion script
* add another test
* final fixes
* change single name variable
* add mock attention mask for pipeline to work
* correct eos token id
* fix nits
* add checkpoints
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add `tie_word_embeddings` in docstring
* change tensor name
* fix final nits
* Trigger CI
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* initial commit
* formatting
* adding the class to many places
* towards less unhappy checks
* nearly there
* and gpt neox for qa
* use right model
* forgot this one
* base_model_prefix is "gpt_neox" for GPTNeoX* models
* unnecessary stuff
* Update src/transformers/models/gpt_neox/modeling_gpt_neox.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* format
* Update src/transformers/models/gpt_neox/modeling_gpt_neox.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* removed gpt2 stuff
---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* initial commit
* formatting
* adding the class to many places
* towards less unhappy checks
* nearly there
* Update src/transformers/models/gpt_neo/modeling_gpt_neo.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* avoid error
* moving to device of star/end_logits
---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* [doc] Try a few ≠ ways of linking to Papers, users, and org profiles
* Empty commit
* Empty commit now that the backend is fixed
---------
Co-authored-by: Lysandre <lysandre@huggingface.co>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* make sure legacy code executes
* comment
* like this
---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Adds FocalNet by Microsoft to transformers
---------
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: alaradirik <alaradirik@gmail.com>
* Add model to doc tests
* Remove generate and replace by prepare_inputs_for_generation
* More fixes
* Remove print statements
* Update integration tests
* Fix generate
* Remove model from auto mapping
* Use auto processor
* Fix integration tests
* Fix test
* Add inference code snippet
* Remove is_encoder_decoder
* Update docs
* Remove notebook link
* resolve conflicts
* rebase and make style
* test
* test
* test
* rebase and make style
* rebase and make style
* tests
* tests
* rewrite some functions
* rebase and make style
* fix load_tf_weights_in_cpmant
* reformat some unrelated files
* upgrade quality
* fix some bugs & docstring
* add models and tests
* solve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* tests
* resolve conflicts
* resolve conflicts
* fix load_tf_weights_in_cpmant
* reformat some unrelated files
* upgrade quality
* fix some bugs & docstring
* save resolution
* make style
* delete redefinition code
* reformat function
* reformat
* resolve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* tests
* resolve conflicts
* resolve conflicts
* fix load_tf_weights_in_cpmant
* reformat some unrelated files
* upgrade quality
* resolve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* resolve conflicts
* fix load_tf_weights_in_cpmant
* reformat some unrelated files
* upgrade quality
* resolve conflicts
* make style
* fix bugs and refactor
* modify docstrings and make style
* unify import format in __init__.py
* fix import-altclp bug
* fix copies to update index.md
* fix unused config parameters
* fix unused config parameters
* fix unused config parameters
* update README_ja.md
* dummy commit for unit test
* fix attention mask
* add CPMAntTokenizer&-Fast to auto-mapping
* drop redundant changes in README_ko
* fix defaults in docstring
* fix use_cache and some docstring
* add missing args in tokenizer
* modify tester inheritance
* add is_jieba_available
* fix some bugs
* make style and fix-copies
* add doctests
* skip integration tests
* add is_jieba_available
* fix bugs in common tests
* adjust docstrings and make style
* add argument docstring
* adjust code to some specifications
* make style and fix-copies
* add fast tokenization test
* dummy commit for unit test
* dummy commit for unit test
* dummy commit for unit test
* normalize some comments and names
* Bert->CPMAnt
* camel names and drop redundant codes
* make style and fix-coies
* add CpmTokenizerFast _import_structure
* drop cpmanttokenizerfast in model_doc
* fix some problems
* fix CPMAnt tokenization for common test
* make style and fixup
* fix copies and fixup
* fix bugs in tokenization test
* dummy commit for connection failure in unittest
* fix copies
* drop trailing comma
* fix decorator in tests
* dummy commit for connection failure in unittest
---------
Co-authored-by: Gong Baitao <gongbaitao11@gmail.com>
* Adding Llama FastTokenizer support.
- Requires https://github.com/huggingface/tokenizers/pull/1183 version
- Only support byte_fallback for llama, raise otherwise (safety net).
- Lots of questions are special tokens
How to test:
```python
from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers import AutoTokenizer
from tokenizers import Tokenizer
tokenizer = AutoTokenizer.from_pretrained("huggingface/llama-7b")
if False:
new_tokenizer = Tokenizer.from_file("tok.json")
else:
new_tokenizer = convert_slow_tokenizer(tokenizer)
new_tokenizer.save("tok.json")
strings = [
"This is a test",
"生活的真谛是",
"生活的真谛是[MASK]。",
# XXX: This one is problematic because of special tokens
# "<s> Something something",
]
for string in strings:
encoded = tokenizer(string)["input_ids"]
encoded2 = new_tokenizer.encode(string).ids
assert encoded == encoded2, f"{encoded} != {encoded2}"
decoded = tokenizer.decode(encoded)
decoded2 = new_tokenizer.decode(encoded2)
assert decoded.strip() == decoded2, f"{repr(decoded)} != {repr(decoded2)}"
```
The converter + some test script.
The test script.
Tmp save.
Adding Fast tokenizer + tests.
Adding the tokenization tests.
Correct combination.
Small fix.
Fixing tests.
Fixing with latest update.
Rebased.
fix copies + normalized added tokens + copies.
Adding doc.
TMP.
Doc + split files.
Doc.
Versions + try import.
Fix Camembert + warnings -> Error.
Fix by ArthurZucker.
Not a decorator.
* Fixing comments.
* Adding more to docstring.
* Doc rewriting.
* Initial commit
* more stash commit
* Yet another stash commit
* yet more stash commit
* Mostly working except for docs / repo consistency
* Stop importing model list from torch file
* Add TF BLIP models to docs
* Add auto classes
* Move get_text_features and get_image_features
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/blip/test_modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/blip/test_modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/models/blip/test_modeling_tf_blip_text.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Use channels_last convolutions in TF (better performance + compatibility)
* Remove _shape function
* Move multi-line statement to one line in PT + TF
* Specify tf.keras.layers instead of importing from it
* Remove test_gradient_checkpointing and empty test_training methods
* move some multi-line statements to one line
* Update docstring for generate
* Remove pruned heads set
* Remove self.seq_len_dim
* Fixed issues with loss computation, should resolve some tests. Also ensured that the PT version follows the config for output_attentions and output_hidden_states
* ensure original model follows config in more cases
* Skip the same cross-attention tests in the PT tests - didn't realize we did it twice!
* Add training args throughout the models and layers
* make fixup
* Fix docstring for inputs_embeds
* Add docstring for is_decoder
* Add docstrings to text models
* Remove redundant computation
* Add unpack_inputs / keras_serializable
* Add modeling_tf_blip to doctests
* Add config classes for keras serialization
* Changes to allow model porting with pt-to-tf
* Quick fix to decoder head and test tweaks
* Revert an issue with masking the embeddings outputs
* Allow missing keys in some equivalence tests (for unused layers)
* Add tf-pt equivalence tests back in
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make fixup
* Refactor invert_attention_mask out into tf_utils
* Re-enable cross-tests on the PT side too
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Initial commit
* update modeling code
* update doc
* add functions necessary
* fix impotrs
* revert changes
* fixup
* more styling to get going
* remove standalone encoder
* update code
* styling
* fix config and model
* update code and some refactoring
* make more tests pass
* Adding NLLB-200 - MoE - 54.5B for no language left behind
Fixes#21300
* fix mor common tests
* styke
* update testing file
* update
* update
* Router2 doc
* update check config with sparse layer
* add dummy router
* update current conversion script
* create on the fly conversion script
* Fixup
* style
* style 2
* fix empty return
* fix return
* Update default config sparse layers
* easier to create sparse layers
* update
* update conversion script
* update modeling
* add to toctree
* styling
* make ruff happy
* update docstring
* update conversion script
* update, will break tests but impelemting top2
* update
* ❗local groups are supported here
* ⚠️ Support for local groups is now removed ⚠️
This is because it has to work with model parallelism that we do not support
* finish simplificaiton
* Fix forward
* style
* fixup
* Update modelling and test, refactoring
* update tests
* remove final layer)norm as it is done in the FF
* routing works! Logits test added
* nit in test
* remove top1router
* style
* make sure sparse are tested. Had to change route_tokens a liottle bit
* add support for unslip models when converting
* fixup
* style
* update test s
* update test
* REFACTOR
* encoder outputs match!
* style
* update testing
* 🎉encoder and decoder logits match 🎉
* styleing
* update tests
* cleanup tests
* fix router test and CIs
* cleanup
* cleanup test styling
* fix tests
* Finally the generation tests match!
* cleanup
* update test
* style testing file
* remove script
* cleanup
* more cleanup
* nits
* update
* NLLB tokenizer is wrong and will be fixed soon
* use LongTensors
* update tests
* revert some small changes
* fix second expert sampling and batch prioritized routing
* update tests
* finish last tests
* make ruff happy
* update
* ruff again
* style
* Update docs/source/en/model_doc/nllb-moe.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Updates based on review
* style and fix import issue
* nit
* more nits
* cleanup
* styling
* update test_seconde_expert_policy
* fix name
* last nit on the markdown examples
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add mega file structure and plain pytorch version of mega source code
* added config class with old naming conventions
* filled in mega documentation
* added config class and embeddings with optional token types
* updated notes
* starting the conversion process, deleted intermediate and added use_cache back to config
* renamed config attributes in modeling_mega.py
* checkpointing before refactoring incremental decoding functions
* removed stateful incremental key/values for EMA and self-attention
* refactored MovingAverageGatedAttention to remove stateful k/v history and use unified attention mask
* MovingAverageGatedAttention works with incremental decoding + past values, added sequence length enforcement
* more comments in MovingAverageGatedAttention + checkpointing before GatedCrossAttention
* bug fix in attention mask handling in MovingAverageGatedAttention
* removed incremental state from GatedCrossAttention and removed IncrementalState class
* finished gated cross attention and got MegaLayer working
* fixed causal masking in mega decoder
* fixed how padding and causal masks are passed through MegaLayer with and without k/v caching
* finished MegaModel; tested with encoder, decoder-only, and cross-attention type inputs; started work on downstream classes; removed mentions of position_ids
* added optional dense hidden layer for masked and causal LM classes
* docstring updates in MultiHeadEMA and GatedCrossAttention, removed unnecessary inputs in cross-attention
* removed before_attn_fn in Mega class and updated docstrings and comments up to there
* bug fix in MovingAverageGatedAttention masking
* working conversion of MLM checkpoint in scratchpad script -- perfect matches
* moved arg for hidden dense layer in LM head to config; discovered issue where from_pretrained is renaming gamma and beta parameters
* renamed gamma and beta parameters to avoid HF renaming when loading from checkpoint
* finished checkpoint conversion script
* cleanup old class in mega config script
* removed 'copied from' statements and passing integration tests
* added num_attention_heads=1 to config for integration compatibility, decoder tests working, generation tests failing
* fixed tuple output of megamodel
* all common tests passing after fixing issues in decoder, gradient retention, and initialization
* added mega-specific tests, ready for more documentation and style checks
* updated docstrings; checkpoint before style fixes
* style and quality checks, fixed initialization problem in float_tensor, ready for PR
* added mega to toctree
* removed unnecessary arg in megaconfig
* removed unused arg and fixed code samples with leftover roberta models
* Apply suggestions from code review
Applied all suggestions except the one renaming a class, as I'll need to update that througout
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixed issue where .view breaks batch dimension, conversion script fixed with absolute imports, updated readme with Mega->MEGA
* removed asserts in Mega code, renamed sequencenorm, gatedcrossattention, and NFFN, replaced get_activation_fn with ACTFN, and added sequencenorm to layer norms
* reformatted .forward() docstrings to match style and removed unused mask input in cross-attention
* removed all reset_parameters() methods and rolled into MegaPreTrainedModel._init_weights()
* renamed all single-letter variables and improved readability in tensor size comments, Mega->MEGA in 2 documentation files
* variable names in NFFN
* manual Mega->MEGA changes in docs
* Mega->MEGA in config auto
* style and quality fixes
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* renamed parameters and variables with confusing names, added copied from statements, moved fft conv to its own method, other cleanup from PR comments
* commit before dealing with merge conflicts
* made new attention activation functions available in ACT2FN and added generation test from OPT
* style and quality in activations and tests
* documentation fixes, renaming variables in dropout and rotary positions, used built-in causal masking, encoders->layers in MegaModel, moved comments into docstrings
* style and quality fixes after latest updates, before rotary position ids
* causal mask in MegaBlock docstring + added missing device passing
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* added Mega prefixes where missing, reverted MegaSequenceNorm to if-else, other module renaming requested in PR
* style and quality fixes + readme updates pointing to main
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
