* Fix error in convert_openai_to_hf.py: "_download() missing 1 required positional argument: root"
* Fix error in convert_openai_to_hf.py: "TypeError: byte indices must be integers or slices, not str"
* Fix decoder_attention_heads value in convert_openai_to_hf.py.
Correct the assignment for `decoder_attention_heads` in the conversion script for the Whisper model.
* Black reformat convert_openai_to_hf.py file.
* Fix Whisper model configuration defaults (for Tiny).
- Correct encoder/decoder layers and attention heads count.
- Update model width (`d_model`) to 384.
* Add docstring to the convert_openai_to_hf.py script with a doctest
* Add shebang and +x permission to the convert_openai_to_hf.py
* convert_openai_to_hf.py: reuse the read model_bytes in the _download() function
* Move convert_openai_to_hf.py doctest example to whisper.md
* whisper.md: Add an inference example to the Conversion section.
* whisper.md: remove `model.config.forced_decoder_ids` from examples (deprecated)
* whisper.md: Remove "## Format Conversion" section; not used by users
* whisper.md: Use librispeech_asr_dummy dataset and load_dataset()
I'm adding accelerate as one of the libraries to install because otherwise when running the Trainer, the model errorr out with the error.
ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.20.1`: Please run `pip install transformers[torch]` or `pip install accelerate -U`
Further context:
1. I've tried this across different environments so I believe that the environment is not the issue.
2. I had the latest transformers library version running.
3. Typically even after install accelerate and import it, it wouldn't resolve the issue until I restart the notebook and try again.
* first batch of structure improvements for model_docs
* second batch of structure improvements for model_docs
* more structure improvements for model_docs
* more structure improvements for model_docs
* structure improvements for cv model_docs
* more structural refactoring
* addressed feedback about image processors
* Use Llama RoPE implementation for Falcon
+ Add copy functionalities
* Use standard cache format for Falcon
* Simplify apply_rotary_pos_emb, copy from Llama
* Remove unnecessary cache conversion test
We don't need to convert any caches anymore!
* Resolve copy complaint
* Fixed base model class name extraction from PeftModels
* Changes to first unwrap the model then extract the base model name
* Changed base_model to base_model.model to stay consistent with peft model abstractions
* Removed the redundant SiLUActivation class and now use nn.functional.silu directly.
* I apologize for adding torch.functional.silu. I have replaced it with nn.SiLU.
* Fixing m4t.
* Trying to remove comparison ? Odd test failure.
* Adding shared. But why on earth does it hang ????
* Putting back the model weights checks the test is silently failing on
cuda.
* Fix style + unremoved comment.
* Fix Fuyu image scaling bug
It could produce negative padding and hence inference errors for certain
image sizes.
* initial rework commit
* add batching capabilities, refactor image processing
* add functional batching for a list of images and texts
* make args explicit
* Fuyu processing update (#27133)
* Add file headers
* Add file headers
* First pass - preprocess method with standard args
* First pass image processor rework
* Small tweaks
* More args and docstrings
* Tidying iterating over batch
* Tidying up
* Modify to have quick tests (for now)
* Fix up
* BatchFeature
* Passing tests
* Add tests for processor
* Sense check when patchifying
* Add some tests
* FuyuBatchFeature
* Post-process box coordinates
* Update to `size` in processor
* Remove unused and duplicate constants
* Store unpadded dims after resize
* Fix up
* Return FuyuBatchFeature
* Get unpadded sizes after resize
* Update exception
* Fix return
* Convert input `<box>` coordinates to model format.
* Post-process point coords, support multiple boxes/points in a single
sequence
* Replace constants
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Preprocess List[List[image]]
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update to Amy's latest state.
* post-processing returns a list of tensors
* Fix error when target_sizes is None
Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Review comments
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Fix up
* Fix up
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Co-authored-by: Ubuntu <ubuntu@ip-172-31-72-126.ec2.internal>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>
* Fix conflicts in fuyu_follow_up_image_processing (#27228)
fixing conflicts and updating on main
* Revert "Fix conflicts in fuyu_follow_up_image_processing" (#27232)
Revert "Fix conflicts in fuyu_follow_up_image_processing (#27228)"
This reverts commit acce10b6c6.
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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-72-126.ec2.internal>
* add whisper fa2
* correct
* change all
* correct
* correct
* fix more
* fix more
* fix more
* fix more
* fix more
* fix more
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix more
* fix more
* fix more
* fix more
* fix more
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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Enable split_batches through TrainingArguments
* Extra dispatch_batches
* Keep as default false
* Add to docstring
* Add to docstring
* Remove the capturewarnings change
* Comma
* Add type annotations to TFConvNextDropPath
* Use tf.debugging.assert_equal for TFConvNextEmbeddings shape check
* Add TensorFlow implementation of ConvNeXTV2
* check_docstrings: add TFConvNextV2Model to exclusions
TFConvNextV2Model and TFConvNextV2ForImageClassification have docstrings
which are equivalent to their PyTorch cousins, but a parsing issue prevents them
from passing the test.
Adding exclusions for these two classes as discussed in #25558.
