1. 27 Mar, 2024 1 commit
    • Bo Zheng's avatar
      Add Qwen2MoE (#29377) · 1c39974a
      Bo Zheng authored
      
      
      * add support for qwen2 MoE models
      
      * update docs
      
      * add support for qwen2 MoE models
      
      * update docs
      
      * update model name & test
      
      * update readme
      
      * update class names & readme & model_doc of Qwen2MoE.
      
      * update architecture name
      
      * fix qwen2_moe tests
      
      * use Qwen2Tokenizer instead of Qwen2MoeTokenizer
      
      * update modeling_qwen2_moe.py
      
      * fix model architecture
      
      * fix qwen2_moe tests
      
      * use Qwen2Tokenizer instead of Qwen2MoeTokenizer
      
      * update modeling_qwen2_moe.py
      
      * fix model architecture
      
      * fix style
      
      * fix test when there are sparse and non sparse layers
      
      * fixup
      
      * Update README.md
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * fixup
      
      * fixup
      
      * add archive back
      
      * add support for qwen2 MoE models
      
      * update docs
      
      * update model name & test
      
      * update readme
      
      * update class names & readme & model_doc of Qwen2MoE.
      
      * update architecture name
      
      * fix qwen2_moe tests
      
      * use Qwen2Tokenizer instead of Qwen2MoeTokenizer
      
      * update modeling_qwen2_moe.py
      
      * fix model architecture
      
      * fixup
      
      * fix qwen2_moe tests
      
      * use Qwen2Tokenizer instead of Qwen2MoeTokenizer
      
      * fix style
      
      * fix test when there are sparse and non sparse layers
      
      * fixup
      
      * add archive back
      
      * fix integration test
      
      * fixup
      
      ---------
      Co-authored-by: default avatarbozheng-hit <dsoul0621@gmail.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      1c39974a
  2. 20 Mar, 2024 2 commits
    • NielsRogge's avatar
      Add LLaVa-1.6, bis (#29586) · d91fd7f9
      NielsRogge authored
      
      
      * First draft
      
      * Fix tests, add docs
      
      * Improve docstrings
      
      * Fix test
      
      * Address comments
      
      * Address comments
      
      * Remove vocab_size attribute
      
      * Remove batch_size
      
      * Address comment
      
      * Add image processor tests
      
      * Support fx
      
      * Update docstring
      
      * Add support for 34b
      
      * Convert 34b model
      
      * Add integration tests
      
      * Update checkpoints
      
      * Convert vicuna-13b, remove doc tests
      
      * Remove script
      
      * Remove file
      
      * Address comments
      
      * Improve docstrings
      
      * Deprecate vocab_size
      
      * Remove aspect_ratio_setting
      
      * Address comments
      
      * Update READMEs
      
      * Add tips about chat templates
      
      * Fix tests
      
      * Deprecate vocab_size safely
      
      * Update tests
      
      ---------
      Co-authored-by: default avatarAmy Roberts <22614925+amyeroberts@users.noreply.github.com>
      d91fd7f9
    • Arthur Zucker's avatar
      v4.40.0.dev.0 · 1248f092
      Arthur Zucker authored
      1248f092
  3. 19 Mar, 2024 1 commit
    • StevenBucaille's avatar
      Implementation of SuperPoint and AutoModelForKeypointDetection (#28966) · 56baa033
      StevenBucaille authored
      
      
      * Added SuperPoint docs
      
      * Added tests
      
      * Removed commented part
      
      * Commit to create and fix add_superpoint branch with a new branch
      
      * Fixed dummy_pt_objects
      
      * Committed missing files
      
      * Fixed README.md
      
      * Apply suggestions from code review
      
      Fixed small changes
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py
      
      * Removed AutoModelForKeypointDetection and related stuff
      
      * Fixed inconsistencies in image_processing_superpoint.py
      
      * Moved infer_on_model logic simply in test_inference
      
      * Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py
      
      * Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale
      
      * Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING
      
      * Apply suggestions from code review
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Fixed from (w, h) to (h, w) as input for tests
      
      * Removed unnecessary condition
      
      * Moved last_hidden_state to be the first returned
      
      * Moved last_hidden_state to be the first returned (bis)
      
      * Moved last_hidden_state to be the first returned (ter)
      
      * Switched image_width and image_height in tests to match recent changes
      
      * Added config as first SuperPointConvBlock init argument
      
      * Reordered README's after merge
      
      * Added missing first config argument to SuperPointConvBlock instantiations
      
      * Removed formatting error
      
      * Added SuperPoint to README's de, pt-br, ru, te and vi
      
      * Checked out README_fr.md
      
      * Fixed README_fr.md
      
      * Test fix README_fr.md
      
      * Test fix README_fr.md
      
      * Last make fix-copies !
      
      * Updated checkpoint path
      
      * Removed unused SuperPoint doc
      
      * Added missing image
      
      * Update src/transformers/models/superpoint/modeling_superpoint.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Removed unnecessary import
      
      * Update src/transformers/models/superpoint/modeling_superpoint.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Added SuperPoint to _toctree.yml
      
      ---------
      Co-authored-by: default avatarsteven <steven.bucaillle@gmail.com>
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      Co-authored-by: default avatarSteven Bucaille <steven.bucaille@buawei.com>
      56baa033
  4. 18 Mar, 2024 1 commit
    • Yoach Lacombe's avatar
      Add MusicGen Melody (#28819) · c43b380e
      Yoach Lacombe authored
      
      
      * first modeling code
      
      * make repository
      
      * still WIP
      
      * update model
      
      * add tests
      
      * add latest change
      
      * clean docstrings and copied from
      
      * update docstrings md and readme
      
      * correct chroma function
      
      * correct copied from and remove unreleated test
      
      * add doc to toctree
      
      * correct imports
      
      * add convert script to notdoctested
      
      * Add suggestion from Sanchit
      Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      
      * correct get_uncoditional_inputs docstrings
      
      * modify README according to SANCHIT feedback
      
      * add chroma to audio utils
      
      * clean librosa and torchaudio hard dependencies
      
      * fix FE
      
      * refactor audio decoder -> audio encoder for consistency with previous musicgen
      
      * refactor conditional -> encoder
      
      * modify sampling rate logics
      
      * modify license at the beginning
      
      * refactor all_self_attns->all_attentions
      
      * remove ignore copy from causallm generate
      
      * add copied from for from_sub_models
      
      * fix make copies
      
      * add warning if audio is truncated
      
      * add copied from where relevant
      
      * remove artefact
      
      * fix convert script
      
      * fix torchaudio and FE
      
      * modify chroma method according to feedback-> better naming
      
      * refactor input_values->input_features
      
      * refactor input_values->input_features and fix import fe
      
      * add input_features to docstrigs
      
      * correct inputs_embeds logics
      
      * remove dtype conversion
      
      * refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation
      
      * change warning for chroma length
      
      * Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py
      Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      
      * change way to save wav, using soundfile
      
      * correct docs and change to soundfile
      
      * fix import
      
      * fix init proj layers
      
      * remove line breaks from md
      
      * fix issue with docstrings
      
      * add FE suggestions
      
      * improve is in logics and remove useless imports
      
      * remove custom from_pretrained
      
      * simplify docstring code
      
      * add suggestions for modeling tests
      
      * make style
      
      * update converting script with sanity check
      
      * remove encoder attention mask from conditional generation
      
      * replace musicgen melody checkpoints with official orga
      
      * rename ylacombe->facebook in checkpoints
      
      * fix copies
      
      * remove unecessary warning
      
      * add shape in code docstrings
      
      * add files to slow doc tests
      
      * fix md bug and add md to not_tested
      
      * make fix-copies
      
      * fix hidden states test and batching
      
      ---------
      Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      c43b380e
  5. 15 Mar, 2024 1 commit
    • Saurabh Dash's avatar
      Cohere Model Release (#29622) · 0e4a1c34
      Saurabh Dash authored
      
      
      * Cohere Model Release (#1)
      
      Cohere Model Release
      
      * Remove unnecessary files and code (#2)
      
      Some cleanup
      
      * Delete cohere-model directory (#3)
      
      * Make Fix (#5)
      
      * Pr fixes (#6)
      
      * fixes for pr
      
      * pr fixes for the format
      
      * pr fixes for the format
      
      * src/transformers/models/auto/tokenization_auto.py
      
      * Tokenizer test (#8)
      
      * tokenizer test
      
      * format fix
      
      * Adding Docs and other minor changes (#7)
      
      * Add modeling tests (#9)
      
      * Smol Fix (#11)
      
      * tokenization tests are fixed
      
      * format fixes
      
      * fix pr doc tests
      
      * fix pr doc tests
      
      * fix pr doc tests
      
      * fix pr style check
      
      * small changes in cohere.md
      
      * FIX: Address final comments for transformers integration (#13)
      
      * fix modeling final nits and add proper test file
      
      * for now leave empty tests
      
      * add integration test
      
      * push new test
      
      * fix modeling cohere (#14)
      
      * Update chat templates to use the new API (#15)
      
      ---------
      Co-authored-by: default avatarahmetustun <ahmetustun89@gmail.com>
      Co-authored-by: default avatarYounes Belkada <49240599+younesbelkada@users.noreply.github.com>
      Co-authored-by: default avatarMatt <Rocketknight1@users.noreply.github.com>
      0e4a1c34
  6. 13 Mar, 2024 1 commit
    • Nate Cibik's avatar
      Add PvT-v2 Model (#26812) · 1fc505b8
      Nate Cibik authored
      
      
      * Added pytests for pvt-v2, all passed
      
      * Added pvt_v2 to docs/source/end/model_doc
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Reverted batch eval changes for PR
      
      * Expanded type support for Pvt-v2 config
      
      * Fixed config docstring. Added channels property
      
      * Fixed model names in tests
      
      * Fixed config backbone compat. Added additional type support for image size in config
      
      * Fixed config backbone compat
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * Set key and value layers to use separate linear modules. Fixed pruning function
      
      * Set AvgPool to 7
      
      * Fixed issue in init
      
      * PvT-v2 now works in AutoModel
      
      * Successful conversion of pretrained weights for PVT-v2
      
      * Successful conversion of pretrained weights for PVT-v2 models
      
      * Added pytests for pvt-v2, all passed
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * Set key and value layers to use separate linear modules. Fixed pruning function
      
      * Set AvgPool to 7
      
      * Fixed issue in init
      
      * PvT-v2 now works in AutoModel
      
      * Successful conversion of pretrained weights for PVT-v2
      
      * Successful conversion of pretrained weights for PVT-v2 models
      
      * Added pytests for pvt-v2, all passed
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * Reverted batch eval changes for PR
      
      * Updated index.md
      
      * Expanded type support for Pvt-v2 config
      
      * Fixed config docstring. Added channels property
      
      * Fixed model names in tests
      
      * Fixed config backbone compat
      
      * Ran fix-copies
      
      * Fixed PvtV2Backbone tests
      
      * Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py
      
      * Fixed backbone stuff and fixed tests: all passing
      
      * Ran make fixup
      
      * Made modifications for code checks
      
      * Remove ONNX config from configuration_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Use explicit image size dict in test_modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Make image_size optional in test_modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Remove _ntuple use in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Remove reference to fp16_enabled
      
      * Model modules now take config as first argument even when not used
      
      * Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"
      
      * All LayerNorm now instantiates with config.layer_norm_eps
      
      * Added docstring for depth-wise conv layer
      
      * PvtV2Config now only takes Union[int, Tuple[int, int]] for image size
      
      * Refactored PVTv2 in prep for gradient checkpointing
      
      * Gradient checkpointing ready to test
      
      * Removed override of _set_gradient_checkpointing
      
      * Cleaned out old code
      
      * Applied code fixup
      
      * Applied code fixup
      
      * Began debug of pvt_v2 tests
      
      * Leave handling of num_labels to base pretrained config class
      
      * Deactivated gradient checkpointing tests until it is fixed
      
      * Removed PvtV2ImageProcessor which duped PvtImageProcessor
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * Set key and value layers to use separate linear modules. Fixed pruning function
      
      * Set AvgPool to 7
      
      * Fixed issue in init
      
      * PvT-v2 now works in AutoModel
      
      * Successful conversion of pretrained weights for PVT-v2
      
      * Successful conversion of pretrained weights for PVT-v2 models
      
      * Added pytests for pvt-v2, all passed
      
      * Added pvt_v2 to docs/source/end/model_doc
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Reverted batch eval changes for PR
      
      * Expanded type support for Pvt-v2 config
      
      * Fixed config docstring. Added channels property
      
      * Fixed model names in tests
      
      * Fixed config backbone compat. Added additional type support for image size in config
      
      * Fixed config backbone compat
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * Set key and value layers to use separate linear modules. Fixed pruning function
      
      * Set AvgPool to 7
      
      * Fixed issue in init
      
      * PvT-v2 now works in AutoModel
      
      * Successful conversion of pretrained weights for PVT-v2
      
      * Successful conversion of pretrained weights for PVT-v2 models
      
      * Added pytests for pvt-v2, all passed
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * Set key and value layers to use separate linear modules. Fixed pruning function
      
      * Set AvgPool to 7
      
      * Fixed issue in init
      
      * PvT-v2 now works in AutoModel
      
      * Successful conversion of pretrained weights for PVT-v2
      
      * Successful conversion of pretrained weights for PVT-v2 models
      
      * Added pytests for pvt-v2, all passed
      
      * Ran fix-copies and fixup. All checks passed
      
      * Added additional ReLU for linear attention mode
      
      * pvt_v2_b2_linear converted and working
      
      * Reverted batch eval changes for PR
      
      * Expanded type support for Pvt-v2 config
      
      * Fixed config docstring. Added channels property
      
      * Fixed model names in tests
      
      * Fixed config backbone compat
      
      * Ran fix-copies
      
      * Fixed PvtV2Backbone tests
      
      * Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py
      
      * Fixed backbone stuff and fixed tests: all passing
      
      * Ran make fixup
      
      * Made modifications for code checks
      
      * Remove ONNX config from configuration_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Use explicit image size dict in test_modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Make image_size optional in test_modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Remove _ntuple use in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Remove reference to fp16_enabled
      
      * Model modules now take config as first argument even when not used
      
      * Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"
      
      * All LayerNorm now instantiates with config.layer_norm_eps
      
      * Added docstring for depth-wise conv layer
      
      * PvtV2Config now only takes Union[int, Tuple[int, int]] for image size
      
      * Refactored PVTv2 in prep for gradient checkpointing
      
      * Gradient checkpointing ready to test
      
      * Removed override of _set_gradient_checkpointing
      
      * Cleaned out old code
      
      * Applied code fixup
      
      * Applied code fixup
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Ran fix-copies and fixup. All checks passed
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Reverted batch eval changes for PR
      
      * Fixed config docstring. Added channels property
      
      * Fixed config backbone compat
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Ran fix-copies and fixup. All checks passed
      
      * Allowed for batching of eval metrics
      
      * copied models/pvt to adapt to pvt_v2
      
      * First commit of pvt_v2
      
      * PvT-v2 now works in AutoModel
      
      * Fixed config backbone compat
      
      * Ran fix-copies
      
      * Began debug of pvt_v2 tests
      
      * Leave handling of num_labels to base pretrained config class
      
      * Deactivated gradient checkpointing tests until it is fixed
      
      * Removed PvtV2ImageProcessor which duped PvtImageProcessor
      
      * Fixed issue from rebase
      
      * Fixed issue from rebase
      
      * Set tests for gradient checkpointing to skip those using reentrant since it isn't supported
      
      * Fixed issue from rebase
      
      * Fixed issue from rebase
      
      * Changed model name in docs
      
      * Removed duplicate PvtV2Backbone
      
      * Work around type switching issue in tests
      
      * Fix model name in config comments
      
      * Update docs/source/en/model_doc/pvt_v2.md
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * Changed name of variable from 'attn_reduce' to 'sr_type'
      
      * Changed name of variable from 'attn_reduce' to 'sr_type'
      
      * Changed from using 'sr_type' to 'linear_attention' for clarity
      
      * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      
      Removed old code
      
      * Changed from using 'sr_type' to 'linear_attention' for clarity
      
      * Fixed Class names to be more descriptive
      
      * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      
      Removed outdated code
      
      * Moved paper abstract to single line in pvt_v2.md
      
      * Added usage tips to pvt_v2.md
      
      * Simplified module inits by passing layer_idx
      
      * Fixed typing for hidden_act in PvtV2Config
      
      * Removed unusued import
      
      * Add pvt_v2 to docs/source/en/_toctree.yml
      
      * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.
      
      * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.
      
      * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      
      Move function parameters to single line
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      
      Update year of copyright to 2024
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      
      Make code more explicit
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Updated sr_ratio to be more explicit spatial_reduction_ratio
      
      * Removed excess type hints in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Move params to single line in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Removed needless comment in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update copyright date in pvt_v2.md
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Moved params to single line in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Updated copyright date in configuration_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Cleaned comments in modeling_pvt_v2.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Renamed spatial_reduction Conv2D operation
      
      * Revert "Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
      "
      
      This reverts commit c4a04416dde8f3475ab405d1feb368600e0f8538.
      
      * Updated conversion script to reflect module name change
      
      * Deprecated reshape_last_stage option in config
      
      * Removed unused imports
      
      * Code formatting
      
      * Fixed outdated decorators on test_inference_fp16
      
      * Added "Copied from" comments in test_modeling_pvt_v2.py
      
      * Fixed import listing
      
      * Updated model name
      
      * Force empty commit for PR refresh
      
      * Fixed linting issue
      
      * Removed # Copied from comments
      
      * Added PVTv2 to README_fr.md
      
      * Ran make fix-copies
      
      * Replace all FoamoftheSea hub references with OpenGVLab
      
      * Fixed out_indices and out_features logic in configuration_pvt_v2.py
      
      * Made ImageNet weight conversion verification optional in convert_pvt_v2_to_pytorch.py
      
      * Ran code fixup
      
      * Fixed order of parent classes in PvtV2Config to fix the to_dict method override
      
      ---------
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      1fc505b8
  7. 11 Mar, 2024 1 commit
  8. 05 Mar, 2024 2 commits
    • Arthur's avatar
      [`Add Mamba`] Adds support for the `Mamba` models (#28094) · fb1c62e9
      Arthur authored
      
      
      * initial-commit
      
      * start cleaning
      
      * small nits
      
      * small nits
      
      * current updates
      
      * add kernels
      
      * small refactoring little step
      
      * add comments
      
      * styling
      
      * nit
      
      * nits
      
      * Style
      
      * Small changes
      
      * Push dummy mambda simple slow
      
      * nit
      
      * Use original names
      
      * Use original names and remove norm
      
      * Updates for inference params
      
      * Style nd updates
      
      * nits
      
      * Match logits
      
      * Add a test
      
      * Add expected generated text
      
      * nits doc, imports and styling
      
      * style
      
      * oups
      
      * dont install kernels, invite users to install the required kernels
      
      * let use use the original packages
      
      * styling
      
      * nits
      
      * fix some copieds
      
      * update doc
      
      * fix-copies
      
      * styling done
      
      * nits
      
      * fix import check
      
      * run but wrong cuda ress
      
      * mamba CUDA works :)
      
      * fix the fast path
      
      * config naming nits
      
      * conversion script is not required at this stage
      
      * finish fixing the fast path: generation make sense now!
      
      * nit
      
      * Let's start working on the CIs
      
      * style
      
      * better style
      
      * more nits
      
      * test nit
      
      * quick fix for now
      
      * nits
      
      * nit
      
      * nit
      
      * nit
      
      * nits
      
      * update test rest
      
      * fixup
      
      * update test
      
      * nit
      
      * some fixes
      
      * nits
      
      * update test values
      
      * fix styling
      
      * nit
      
      * support peft
      
      * integrations tests require torchg
      
      * also add slow markers
      
      * styling
      
      * chose forward wisely
      
      * nits
      
      * update tests
      
      * fix gradient checkpointing
      
      * fixup
      
      * nit
      
      * fix doc
      
      * check copies
      
      * fix the docstring
      
      * fix some more tests
      
      * style
      
      * fix beam search
      
      * add init schene
      
      * update
      
      * nit
      
      * fix
      
      * fixup the doc
      
      * fix the doc
      
      * fixup
      
      * tentative update but slow is no longer good
      
      * nit
      
      * should we always use float32?
      
      * nits
      
      * revert wrong changes
      
      * res in float32
      
      * cleanup
      
      * skip fmt for now
      
      * update generation values
      
      * update test values running original model
      
      * fixup
      
      * update tests + rename inference_params to cache_params + make sure training does not use cache_params
      
      * small nits
      
      * more nits
      
      * fix final CIs
      
      * style
      
      * nit doc
      
      * I hope final doc nits
      
      * nit
      
      * 馃珷
      
      * final touch!
      
      * fix torch import
      
      * Apply suggestions from code review
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      
      * Apply suggestions from code review
      
      * fix fix and fix
      
      * fix base model prefix!
      
      * nit
      
      * Update src/transformers/models/mamba/__init__.py
      
      * Update docs/source/en/model_doc/mamba.md
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      
      * nit
      
      ---------
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      fb1c62e9
    • Joshua Lochner's avatar
      [docs] Update starcoder2 paper link (#29418) · ebccb091
      Joshua Lochner authored
      Update starcoder2 paper link
      ebccb091
  9. 04 Mar, 2024 1 commit
    • NielsRogge's avatar
      Add UDOP (#22940) · 836921fd
      NielsRogge authored
      
      
      * First draft
      
      * More improvements
      
      * More improvements
      
      * More fixes
      
      * Fix copies
      
      * More improvements
      
      * More fixes
      
      * More improvements
      
      * Convert checkpoint
      
      * More improvements, set up tests
      
      * Fix more tests
      
      * Add UdopModel
      
      * More improvements
      
      * Fix equivalence test
      
      * More fixes
      
      * Redesign model
      
      * Extend conversion script
      
      * Use real inputs for conversion script
      
      * Add image processor
      
      * Improve conversion script
      
      * Add UdopTokenizer
      
      * Add fast tokenizer
      
      * Add converter
      
      * Update README's
      
      * Add processor
      
      * Add fully fledged tokenizer
      
      * Add fast tokenizer
      
      * Use processor in conversion script
      
      * Add tokenizer tests
      
      * Fix one more test
      
      * Fix more tests
      
      * Fix tokenizer tests
      
      * Enable fast tokenizer tests
      
      * Fix more tests
      
      * Fix additional_special_tokens of fast tokenizer
      
      * Fix tokenizer tests
      
      * Fix more tests
      
      * Fix equivalence test
      
      * Rename image to pixel_values
      
      * Rename seg_data to bbox
      
      * More renamings
      
      * Remove vis_special_token
      
      * More improvements
      
      * Add docs
      
      * Fix copied from
      
      * Update slow tokenizer
      
      * Update fast tokenizer design
      
      * Make text input optional
      
      * Add first draft of processor tests
      
      * Fix more processor tests
      
      * Fix decoder_start_token_id
      
      * Fix test_initialization
      
      * Add integration test
      
      * More improvements
      
      * Improve processor, add test
      
      * Add more copied from
      
      * Add more copied from
      
      * Add more copied from
      
      * Add more copied from
      
      * Remove print statement
      
      * Update README and auto mapping
      
      * Delete files
      
      * Delete another file
      
      * Remove code
      
      * Fix test
      
      * Fix docs
      
      * Remove asserts
      
      * Add doc tests
      
      * Include UDOP in exotic model tests
      
      * Add expected tesseract decodings
      
      * Add sentencepiece
      
      * Use same design as T5
      
      * Add UdopEncoderModel
      
      * Add UdopEncoderModel to tests
      
      * More fixes
      
      * Fix fast tokenizer
      
      * Fix one more test
      
      * Remove parallelisable attribute
      
      * Fix copies
      
      * Remove legacy file
      
      * Copy from T5Tokenizer
      
      * Fix rebase
      
      * More fixes, copy from T5
      
      * More fixes
      
      * Fix init
      
      * Use ArthurZ/udop for tests
      
      * Make all model tests pass
      
      * Remove UdopForConditionalGeneration from auto mapping
      
      * Fix more tests
      
      * fixups
      
      * more fixups
      
      * fix the tokenizers
      
      * remove un-necessary changes
      
      * nits
      
      * nits
      
      * replace truncate_sequences_boxes with truncate_sequences for fix-copies
      
      * nit current path
      
      * add a test for input ids
      
      * ids that we should get taken from c9f7a32f57440d90ff79890270d376a1cc0acb68
      
      * nits converting
      
      * nits
      
      * apply ruff
      
      * nits
      
      * nits
      
      * style
      
      * fix slow order of addition
      
      * fix udop fast range as well
      
      * fixup
      
      * nits
      
      * Add docstrings
      
      * Fix gradient checkpointing
      
      * Update code examples
      
      * Skip tests
      
      * Update integration test
      
      * Address comment
      
      * Make fixup
      
      * Remove extra ids from tokenizer
      
      * Skip test
      
      * Apply suggestions from code review
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * Update year
      
      * Address comment
      
      * Address more comments
      
      * Address comments
      
      * Add copied from
      
      * Update CI
      
      * Rename script
      
      * Update model id
      
      * Add AddedToken, skip tests
      
      * Update CI
      
      * Fix doc tests
      
      * Do not use Tesseract for the doc tests
      
      * Remove kwargs
      
      * Add original inputs
      
      * Update casting
      
      * Fix doc test
      
      * Update question
      
      * Update question
      
      * Use LayoutLMv3ImageProcessor
      
      * Update organization
      
      * Improve docs
      
      * Update forward signature
      
      * Make images optional
      
      * Remove deprecated device argument
      
      * Add comment, add add_prefix_space
      
      * More improvements
      
      * Remove kwargs
      
      ---------
      Co-authored-by: default avatarArthurZucker <arthur.zucker@gmail.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      836921fd
  10. 28 Feb, 2024 1 commit
  11. 26 Feb, 2024 2 commits
  12. 21 Feb, 2024 2 commits
  13. 16 Feb, 2024 1 commit
  14. 14 Feb, 2024 1 commit
    • Jonathan Tow's avatar
      Add `StableLM` (#28810) · de6029a0
      Jonathan Tow authored
      * Add `StableLM`
      
      * fix(model): re-create from `huggingface-cli add-new-model-like persimmon`
      
      * fix: re-add changes to address comments
      
      * fix(readme): add links to paper
      
      * fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref
      
      * fix(tests): re-add `@slow` decorator to integration tests
      
      * fix(tests): import slow...
      
      * fix(readme_hd): remove whitespace edit
      
      * fix(tokenizer): auto tokenizer tuple
      
      * skip doctests for `modeling_stablelm`
      de6029a0
  15. 12 Feb, 2024 1 commit
  16. 09 Feb, 2024 1 commit
  17. 06 Feb, 2024 1 commit
    • Klaus Hipp's avatar
      [Docs] Add missing language options and fix broken links (#28852) · 1c31b7aa
      Klaus Hipp authored
      * Add missing entries to the language selector
      
      * Add links to the Colab and AWS Studio notebooks for ONNX
      
      * Use anchor links in CONTRIBUTING.md
      
      * Fix broken hyperlinks due to spaces
      
      * Fix links to OpenAI research articles
      
      * Remove confusing footnote symbols from author names, as they are also considered invalid markup
      1c31b7aa
  18. 29 Jan, 2024 1 commit
  19. 25 Jan, 2024 1 commit
    • NielsRogge's avatar
      Add Depth Anything (#28654) · 963db81a
      NielsRogge authored
      * First draft
      
      * More improvements
      
      * More improvements
      
      * More improvements
      
      * More improvements
      
      * Add docs
      
      * Remove file
      
      * Add copied from
      
      * Address comments
      
      * Address comments
      
      * Address comments
      
      * Fix style
      
      * Update docs
      
      * Convert all checkpoints, add integration test
      
      * Rename checkpoints
      
      * Add pretrained backbone attributes
      
      * Fix default config
      
      * Address comment
      
      * Add figure to docs
      
      * Fix bug thanks to @xenova
      
      * Update conversion script
      
      * Fix integration test
      963db81a
  20. 19 Jan, 2024 1 commit
  21. 18 Jan, 2024 1 commit
    • Yoach Lacombe's avatar
      Add new meta w2v2-conformer BERT-like model (#28165) · d2cdefb9
      Yoach Lacombe authored
      
      
      * first commit
      
      * correct default value non causal
      
      * update config and modeling code
      
      * update converting checkpoint
      
      * clean modeling and fix tests
      
      * make style
      
      * add new config parameters to docstring
      
      * fix copied from statements
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      
      * make position_embeddings_type docstrings clearer
      
      * clean converting script
      
      * remove function not used
      
      * clean modeling file
      
      * apply suggestion for test file + add convert script to not_doctested
      
      * modify tests according to review - cleaner logic and more tests
      
      * Apply nit suggestions from code review
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * add checker of valid position embeddings type
      
      * instantiate new layer norm layer with the right eps
      
      * fix freeze_feature_encoder since it can be None in some cases
      
      * add test same output in convert script
      
      * restore wav2vec2conformer and add new model
      
      * create processor and FE + clean
      
      * add new model code
      
      * fix convert script and set default config parameters
      
      * correct model id paths
      
      * make style
      
      * make fix-copies and cleaning files
      
      * fix copied from statements
      
      * complete .md and fixe copies
      
      * clean convert script argument defaults
      
      * fix config parameters docstrings
      
      * fix config docstring
      
      * add copied from and enrich FE tests
      
      * fix copied from and repo-consistency
      
      * add autotokenizer
      
      * make test input length shorter and change docstring code
      
      * fix docstrings and copied from
      
      * add add_adapter to ASR training example
      
      * make testing of adapters more robust
      
      * adapt to multi adapter layers
      
      * refactor input_values->input_features and remove w2v2-bert feature extractor
      
      * remove pretraining model
      
      * remove depreciated features and useless lines
      
      * add copied from and ignore statements to modeling tests
      
      * remove pretraining model #2
      
      * change import in convert script
      
      * change default in convert script
      
      * update readme and remove useless line
      
      * Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * refactor BERT to Bert for consistency
      
      * remove useless ignore copy statement
      
      * add persistent to buffer in rotary
      
      * add eps in LayerNorm init and remove copied from
      
      * add adapter activation parameters and add copied from statements
      
      * Fix copied statements and add unitest.skip reasons
      
      * add copied statement in test_processor
      
      * refactor processor
      
      * make style
      
      * replace numpy random by torch rand
      
      * remove expected output CTC
      
      * improve converting script with processor class
      
      * Apply suggestions from code review
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * remove gumbel class
      
      * remove tests related to previously deleted class
      
      * Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * correct typos
      
      * remove uused parameters
      
      * update processor to takes both text and audio
      
      * update checkpoints
      
      * update expected output and add ctc expected output
      
      * add label_attention_mask
      
      * replace pt with np in processor tests
      
      * fix typo
      
      * revert to behaviour with labels_attention_mask
      
      ---------
      Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      d2cdefb9
  22. 17 Jan, 2024 1 commit
    • Junyang Lin's avatar
      Add qwen2 (#28436) · d6ffe74d
      Junyang Lin authored
      
      
      * add config, modeling, and tokenization
      
      * add auto and init
      
      * update readme
      
      * update readme
      
      * update team name
      
      * fixup
      
      * fixup
      
      * update config
      
      * update code style
      
      * update for fixup
      
      * update for fixup
      
      * update for fixup
      
      * update for testing
      
      * update for testing
      
      * fix bug for config and tokenization
      
      * fix bug for bos token
      
      * not doctest
      
      * debug tokenizer
      
      * not doctest
      
      * debug tokenization
      
      * debug init for tokenizer
      
      * fix style
      
      * update init
      
      * delete if in token auto
      
      * add tokenizer doc
      
      * add tokenizer in init
      
      * Update dummy_tokenizers_objects.py
      
      * update
      
      * update
      
      * debug
      
      * Update tokenization_qwen2.py
      
      * debug
      
      * Update convert_slow_tokenizer.py
      
      * add copies
      
      * add copied from and make style
      
      * update files map
      
      * update test
      
      * fix style
      
      * fix merge reading and update tests
      
      * fix tests
      
      * fix tests
      
      * fix style
      
      * debug a variable in readme
      
      * Update src/transformers/models/qwen2/configuration_qwen2.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * update test and copied from
      
      * fix style
      
      * update qwen2 tokenization  and tests
      
      * Update tokenization_qwen2.py
      
      * delete the copied from after property
      
      * fix style
      
      * update tests
      
      * update tests
      
      * add copied from
      
      * fix bugs
      
      * update doc
      
      * add warning for sliding window attention
      
      * update qwen2 tokenization
      
      * fix style
      
      * Update src/transformers/models/qwen2/modeling_qwen2.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * fix tokenizer fast
      
      ---------
      Co-authored-by: default avatarRen Xuancheng <jklj077@users.noreply.github.com>
      Co-authored-by: default avatarrenxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      d6ffe74d
  23. 11 Jan, 2024 1 commit
  24. 10 Jan, 2024 1 commit
  25. 08 Jan, 2024 1 commit
    • NielsRogge's avatar
      Add SigLIP (#26522) · 3b742ea8
      NielsRogge authored
      
      
      * Add first draft
      
      * Use appropriate gelu function
      
      * More improvements
      
      * More improvements
      
      * More improvements
      
      * Convert checkpoint
      
      * More improvements
      
      * Improve docs, remove print statements
      
      * More improvements
      
      * Add link
      
      * remove unused masking function
      
      * begin tokenizer
      
      * do_lower_case
      
      * debug
      
      * set split_special_tokens=True
      
      * Remove script
      
      * Fix style
      
      * Fix rebase
      
      * Use same design as CLIP
      
      * Add fast tokenizer
      
      * Add SiglipTokenizer to init, remove extra_ids
      
      * Improve conversion script
      
      * Use smaller inputs in conversion script
      
      * Update conversion script
      
      * More improvements
      
      * Add processor to conversion script
      
      * Add tests
      
      * Remove print statements
      
      * Add tokenizer tests
      
      * Fix more tests
      
      * More improvements related to weight initialization
      
      * More improvements
      
      * Make more tests pass
      
      * More improvements
      
      * More improvements
      
      * Add copied from
      
      * Add canonicalize_text
      
      * Enable fast tokenizer tests
      
      * More improvements
      
      * Fix most slow tokenizer tests
      
      * Address comments
      
      * Fix style
      
      * Remove script
      
      * Address some comments
      
      * Add copied from to tests
      
      * Add more copied from
      
      * Add more copied from
      
      * Add more copied from
      
      * Remove is_flax_available
      
      * More updates
      
      * Address comment
      
      * Remove SiglipTokenizerFast for now
      
      * Add caching
      
      * Remove umt5 test
      
      * Add canonicalize_text inside _tokenize, thanks Arthur
      
      * Fix image processor tests
      
      * Skip tests which are not applicable
      
      * Skip test_initialization
      
      * More improvements
      
      * Compare pixel values
      
      * Fix doc tests, add integration test
      
      * Add do_normalize
      
      * Remove causal mask and leverage ignore copy
      
      * Fix attention_mask
      
      * Fix remaining tests
      
      * Fix dummies
      
      * Rename temperature and bias
      
      * Address comments
      
      * Add copied from to tokenizer tests
      
      * Add SiglipVisionModel to auto mapping
      
      * Add copied from to image processor tests
      
      * Improve doc
      
      * Remove SiglipVisionModel from index
      
      * Address comments
      
      * Improve docs
      
      * Simplify config
      
      * Add first draft
      
      * Make it like mistral
      
      * More improvements
      
      * Fix attention_mask
      
      * Fix output_attentions
      
      * Add note in docs
      
      * Convert multilingual model
      
      * Convert large checkpoint
      
      * Convert more checkpoints
      
      * Add pipeline support, correct image_mean and image_std
      
      * Use padding=max_length by default
      
      * Make processor like llava
      
      * Add code snippet
      
      * Convert more checkpoints
      
      * Set keep_punctuation_string=None as in OpenCLIP
      
      * Set normalized=False for special tokens
      
      * Fix doc test
      
      * Update integration test
      
      * Add figure
      
      * Update organization
      
      * Happy new year
      
      * Use AutoModel everywhere
      
      ---------
      Co-authored-by: default avatarpatil-suraj <surajp815@gmail.com>
      3b742ea8
  26. 04 Jan, 2024 1 commit
  27. 03 Jan, 2024 1 commit
    • Connor Henderson's avatar
      Add FastSpeech2Conformer (#23439) · d83ff5ee
      Connor Henderson authored
      * start - docs, SpeechT5 copy and rename
      
      * add relevant code from FastSpeech2 draft, have tests pass
      
      * make it an actual conformer, demo ex.
      
      * matching inference with original repo, includes debug code
      
      * refactor nn.Sequentials, start more desc. var names
      
      * more renaming
      
      * more renaming
      
      * vocoder scratchwork
      
      * matching vocoder outputs
      
      * hifigan vocoder conversion script
      
      * convert model script, rename some config vars
      
      * replace postnet with speecht5's implementation
      
      * passing common tests, file cleanup
      
      * expand testing, add output hidden states and attention
      
      * tokenizer + passing tokenizer tests
      
      * variety of updates and tests
      
      * g2p_en pckg setup
      
      * import structure edits
      
      * docstrings and cleanup
      
      * repo consistency
      
      * deps
      
      * small cleanup
      
      * forward signature param order
      
      * address comments except for masks and labels
      
      * address comments on attention_mask and labels
      
      * address second round of comments
      
      * remove old unneeded line
      
      * address comments part 1
      
      * address comments pt 2
      
      * rename auto mapping
      
      * fixes for failing tests
      
      * address comments part 3 (bart-like, train loss)
      
      * make style
      
      * pass config where possible
      
      * add forward method + tests to WithHifiGan model
      
      * make style
      
      * address arg passing and generate_speech comments
      
      * address Arthur comments
      
      * address Arthur comments pt2
      
      * lint  changes
      
      * Sanchit comment
      
      * add g2p-en to doctest deps
      
      * move up self.encoder
      
      * onnx compatible tensor method
      
      * fix is symbolic
      
      * fix paper url
      
      * move models to espnet org
      
      * make style
      
      * make fix-copies
      
      * update docstring
      
      * Arthur comments
      
      * update docstring w/ new updates
      
      * add model architecture images
      
      * header size
      
      * md wording update
      
      * make style
      d83ff5ee
  28. 13 Dec, 2023 2 commits
    • Lysandre's avatar
      Dev version · 3ed3e319
      Lysandre authored
      3ed3e319
    • Younes Belkada's avatar
      Adds VIP-llava to transformers (#27932) · c7f076a0
      Younes Belkada authored
      * v1
      
      * add-new-model-like
      
      * revert
      
      * fix forward and conversion script
      
      * revert
      
      * fix copies
      
      * fixup
      
      * fix
      
      * Update docs/source/en/index.md
      
      * Apply suggestions from code review
      
      * push
      
      * fix
      
      * fixes here and there
      
      * up
      
      * fixup and fix tests
      
      * Apply suggestions from code review
      
      * add docs
      
      * fixup
      
      * fixes
      
      * docstring
      
      * add docstring
      
      * fixup
      
      * docstring
      
      * fixup
      
      * nit
      
      * docs
      
      * more copies
      
      * fix copies
      
      * nit
      
      * update test
      c7f076a0
  29. 11 Dec, 2023 2 commits
    • Arthur's avatar
      [`Add Mixtral`] Adds support for the Mixtral MoE (#27942) · accccdd0
      Arthur authored
      
      
      * up
      
      * up
      
      * test
      
      * logits ok
      
      * up
      
      * up
      
      * few fixes
      
      * conversion script
      
      * up
      
      * nits
      
      * nits
      
      * update
      
      * nuke
      
      * more updates
      
      * nites
      
      * fix many issues
      
      * nit
      
      * scatter
      
      * nit
      
      * nuke megablocks
      
      * nits
      
      * fix conversion script
      
      * nit
      
      * remove
      
      * nits
      
      * nit
      
      * update
      
      * oupsssss
      
      * change
      
      * nits device
      
      * nits
      
      * fixup
      
      * update
      
      * merge
      
      * add copied from
      
      * fix the copy mentions
      
      * update tests
      
      * more fixes
      
      * nits
      
      * conversion script
      
      * add parts of the readme
      
      * Update tests/models/mixtral/test_modeling_mixtral.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * new test + conversion script
      
      * Apply suggestions from code review
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * Apply suggestions from code review
      
      * fix
      
      * fix copies
      
      * fix copies
      
      * ooops
      
      * fix config
      
      * Apply suggestions from code review
      
      * fix nits
      
      * nit
      
      * add copies
      
      * add batched tests
      
      * docs
      
      * fix flash attention
      
      * let's add more verbose
      
      * add correct outputs
      
      * support router ouptus
      
      * ignore copies where needed
      
      * fix
      
      * cat list if list is given for now
      
      * nits
      
      * Update docs/source/en/model_doc/mixtral.md
      
      * finish router refactoring
      
      * fix forward
      
      * fix expected values
      
      * nits
      
      * fixup
      
      * fix
      
      * fix bug
      
      * fix
      
      * fix dtype mismatch
      
      * fix
      
      * grrr grrr I support item assignment
      
      * fix CI
      
      * docs
      
      * fixup
      
      * remove some copied form
      
      * fix weird diff
      
      * skip doctest fast on the config and modeling
      
      * mark that is supports flash attention in the doc
      
      * update
      
      * Update src/transformers/models/mixtral/modeling_mixtral.py
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      
      * Update docs/source/en/model_doc/mixtral.md
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      
      * revert router logits config issue
      
      * update doc accordingly
      
      * Update src/transformers/models/mixtral/convert_mixtral_weights_to_hf.py
      
      * nits
      
      * use torch testing asssert close
      
      * fixup
      
      * doc nits
      
      ---------
      Co-authored-by: default avataryounesbelkada <younesbelkada@gmail.com>
      Co-authored-by: default avatarYounes Belkada <49240599+younesbelkada@users.noreply.github.com>
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      accccdd0
    • NielsRogge's avatar
      [LLaVa] Some improvements (#27895) · 7ea21f1f
      NielsRogge authored
      * More improvements
      
      * Improve variable names
      
      * Update READMEs, improve docs
      7ea21f1f
  30. 07 Dec, 2023 1 commit
    • Younes Belkada's avatar
      [`Llava`]聽Add Llava to transformers (#27662) · 44b5506d
      Younes Belkada authored
      * add model like
      
      * logits match
      
      * minor fixes
      
      * fixes
      
      * up
      
      * up
      
      * add todo
      
      * llava processor
      
      * keep the processor simple
      
      * add conversion script
      
      * fixup
      
      * fix copies
      
      * up
      
      * add to index
      
      * fix config + logits
      
      * fix
      
      * refactor
      
      * more refactor
      
      * more refactor
      
      * fix copies
      
      * add authors
      
      * v1 tests
      
      * add `LlavaProcessor` in init
      
      * remove unneeded import
      
      * up
      
      * up
      
      * docs
      
      * up
      
      * fix CI
      
      * fix CI
      
      * add attention  mask in test
      
      * make fixup
      
      * remove the vision model
      
      * that' s the dirty way to do it
      
      * nits
      
      * nits
      
      * updates
      
      * add more tests
      
      * add input tests
      
      * fixup
      
      * more styling
      
      * nits
      
      * updates amd cleanup
      
      * fixup the generation expected results
      
      * fix the testing script
      
      * some cleanup and simplification which does not work yet but almost there!
      
      * make correct dispatch operations
      
      * vectorize works for batch of images and text
      
      * last todos
      
      * nits
      
      * update test and modeling code
      
      * remove useless function for now
      
      * fix few issues
      
      * fix generation
      
      * some nits
      
      * add bakllava
      
      * nits
      
      * remove duplicated code
      
      * finis merge
      
      * cleanup
      
      * missed this line
      
      * fill the todos
      
      * add left padding offset
      
      * add left and rignt padding logic
      
      * bool to properly index
      
      * make sure
      
      * more cleanups
      
      * batch is fixed 馃槈
      
      
      
      * add correct device for tensor creation
      
      * fix some dtype missmatch
      
      * ruff
      
      * update conversion script
      
      * Update src/transformers/__init__.py
      
      * fa 2 support + fix conversion script
      
      * more
      
      * correct reshaping
      
      * fix test dict
      
      * fix copies by ignoring
      
      * fix nit
      
      * skip clip vision model
      
      * fixup
      
      * fixup
      
      * LlavaForVisionText2Text -> LlavaForCausalLM
      
      * update
      
      * fix
      
      * raise correct errors
      
      * fix
      
      * docs
      
      * nuke for now
      
      * nits here and there
      
      * fixup
      
      * fix remaining tests
      
      * update LlavaForConditionalGeneration instead of CausalLM
      
      * fixups
      
      * pipeline support
      
      * slow and piepline tests
      
      * supports batch
      
      * nits
      
      * cleanup
      
      * fix first integration tests
      
      * add pad token where needed
      
      * correct etsts
      
      * fixups
      
      * update pipeline testr
      
      * fix quality
      
      * nits
      
      * revert unneeded change
      
      * nit
      
      * use BatchFeature
      
      * from ...feature_extraction_utils import BatchFeature
      
      * nits
      
      * nits
      
      * properly update
      
      * more f*** nits
      
      * fix copies
      
      * comment
      
      * keep slow test slow
      
      * Update src/transformers/models/llava/processing_llava.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * add piepline example
      
      * add pixel values in docstrign
      
      * update pr doctest
      
      * fix
      
      * fix slow tests
      
      * remove hack
      
      * fixup
      
      * small note
      
      * forward contrib credits from PR25789
      
      * forward contrib credits from original implementation and work
      
      * add arthur
      
      * Update src/transformers/models/llava/processing_llava.py
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      
      * update docstring
      
      * nit
      
      * move to not doctested because of timeout issues
      
      * fixup
      
      * add description
      
      * more
      
      * fix-copies
      
      * fix docs
      
      * add beam search
      
      * add more comments
      
      * add typehints on processor
      
      * add speedup plot
      
      * update slow tests and docs
      
      * push test
      
      * push batched test
      
      * fix batched generation with different number of images
      
      * remove benchmark due to a bug
      
      * fix test
      
      * fix copies
      
      * add gcolab demo
      
      ---------
      Co-authored-by: default avatarArthur Zucker <arthur.zucker@gmail.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      Co-authored-by: default avatarshauray8 <shauray8@users.noreply.github.com>
      Co-authored-by: default avatarhaotian-liu <haotian-liu@users.noreply.github.com>
      Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      44b5506d
  31. 05 Dec, 2023 1 commit
    • Arindam Jati's avatar
      [Time series] Add PatchTSMixer (#26247) · b242d0f2
      Arindam Jati authored
      
      
      * patchtsmixer initial commit
      
      * x,y->context_values,target_values, unittest addded
      
      * cleanup code
      
      * minor
      
      * return hidden states
      
      * model tests, partial integration tests
      
      * ettm notebook temporary
      
      * minor
      
      * config mask bug fix, tests updated
      
      * final ETT notebooks
      
      * add selfattn
      
      * init
      
      * added docstrings
      
      * PatchTSMixerForPretraining -> PatchTSMixerForMaskPretraining
      
      * functionality tests added
      
      * add start and input docstrings
      
      * docstring edits
      
      * testcase edits
      
      * minor changes
      
      * docstring error fixed
      
      * ran make fixup
      
      * finalize integration tests and docs
      
      * minor
      
      * cleaned gitignore
      
      * added dataclass decorator, ran black formatter
      
      * ran ruff
      
      * formatting
      
      * add slow decorator
      
      * renamed in_Channel to input_size and default to 1
      
      * shorten dataclass names
      
      * use smaller model for testing
      
      * moved the 3 heads to the modeling file
      
      * use scalers instead of revin
      
      * support forecast_channel_indices
      
      * fix regression scaling
      
      * undo reg. scaling
      
      * removed unneeded classes
      
      * forgot missing
      
      * add more layers
      
      * add copied positional_encoding
      
      * use patchmask from patchtst
      
      * removed dependency on layers directory
      
      * formatting
      
      * set seed
      
      * removed unused imports
      
      * fixed forward signature test
      
      * adding distributional head for PatchTSMixerForecasting
      
      * add generate to forecast
      
      * testcases for generate
      
      * add generate and distributional head for regression
      
      * raise Exception for negative values for neg binominal distribution
      
      * formatting changes
      
      * remove copied from patchtst and add TODO for test passing
      
      * make copies
      
      * doc edits
      
      * minor changes
      
      * format issues
      
      * minor changes
      
      * minor changes
      
      * format docstring
      
      * change some class names to PatchTSMixer + class name
      
      Transpose to PatchTSMixerTranspose
      GatedAttention to PatchTSMixerGatedAttention
      
      * change NormLayer to PatchTSMixerNormLayer
      
      * change MLP to PatchTSMixerMLP
      
      * change PatchMixer to PatchMixerBlock, FeatureMixer to FeatureMixerBlock
      
      * change ChannelFeatureMixer to ChannelFeatureMixerBlock
      
      * change PatchMasking to PatchTSMixerMasking
      
      * change Patchify to PatchTSMixerPatchify
      
      * list to `list`
      
      * fix docstrings
      
      * formatting
      
      * change bs to batch_size, edit forecast_masking
      
      * edit random_masking
      
      * change variable name and update docstring in PatchTSMixerMasking
      
      * change variable name and update docstring in InjectScalerStatistics4D
      
      * update forward call in PatchTSMixerTranspose
      
      * change variable name and update docstring in PatchTSMixerNormLayer
      
      * change variable name and update docstring in PatchTSMixerMLP
      
      * change variable name and update docstring in ChannelFeatureMixerBlock
      
      * formatting
      
      * formatting issues
      
      * docstring issue
      
      * fixed observed_mask type in docstrings
      
      * use FloatTensor type
      
      * formatting
      
      * fix rescaling issue in forecasting, fixed integration tests
      
      * add docstring from decorator
      
      * fix docstring
      
      * Update README.md
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * PatchTSMixerChannelFeatureMixerBlock
      
      * formatting
      
      * ForPretraining
      
      * use num_labels instead of n_classes
      
      * remove commented out code
      
      * docstring fixed
      
      * nn.functional used instead of one letter F
      
      * x_tmp renamed
      
      * one letter variable x removed from forward calls
      
      * one letter variable y removed
      
      * remove commented code
      
      * rename patch_size, in_channels, PatchTSMixerBackbone
      
      * add config to heads
      
      * add config to heads tests
      
      * code reafactoring to use config instead of passing individual params
      
      * Cdocstring fixes part 1
      
      * docstring fixes part 2
      
      * removed logger.debug
      
      * context_values -> past_values
      
      * formatting changes
      
      * pe -> positional_encoding
      
      * removed unused target variable
      
      * self.mode logic fixed
      
      * formatting change
      
      * edit docstring and var name
      
      * change n_targets to num_targets
      
      * rename input_size to num_input_channels
      
      * add head names with prefix PatchTSMixer
      
      * edit docstring in PatchTSMixerForRegression
      
      * fix var name change in testcases
      
      * add PatchTSMixerAttention
      
      * return dict for all exposed classes, test cases added
      
      * format
      
      * move loss function to forward call
      
      * make style
      
      * adding return dict/tuple
      
      * make repo-consistency
      
      * remove flatten mode
      
      * code refactoring
      
      * rename data
      
      * remove PatchTSMixer and keep only PatchTSMixerEncoder
      
      * docstring fixes
      
      * removed unused code
      
      * format
      
      * format
      
      * remove contiguous and formatting changes
      
      * remove model description from config
      
      * replace asserts with ValueError
      
      * remove nn.Sequential from PatchTSMixerNormLayer
      
      * replace if-else with map
      
      * remove all nn.Sequential
      
      * format
      
      * formatting
      
      * fix gradient_checkpointing error after merge, and formatting
      
      * make fix-copies
      
      * remove comments
      
      * reshape
      
      * doesnt support gradient checkpointing
      
      * corect Patchify
      
      * masking updates
      
      * batchnorm copy from
      
      * format checks
      
      * scaler edits
      
      * remove comments
      
      * format changes
      
      * remove self.config
      
      * correct class PatchTSMixerMLP(nn.Module):
      
      * makr fix
      
      * doc updates
      
      * fix-copies
      
      * scaler class correction
      
      * doc edits
      
      * scaler edits
      
      * update readme with links
      
      * injectstatistics add
      
      * fix-copies
      
      * add norm_eps option to LayerNorm
      
      * format changes
      
      * fix copies
      
      * correct make copies
      
      * use parametrize
      
      * fix doc string
      
      * add docs to toctree
      
      * make style
      
      * doc segmenting
      
      * docstring edit
      
      * change forecast to prediction
      
      * edit doc
      
      * doc edits
      
      * remove PatchTSMixerTranspose
      
      * add PatchTSMixerPositionalEncoding and init position_enc
      
      * remove positional_encoding
      
      * edit forecast_masking, remove forecast_mask_ratios
      
      * fix broken code
      
      * var rename target_values -> future_values
      
      * num_features -> d_model
      
      * fix broken code after master merge
      
      * repo consistency
      
      * use postional embedding
      
      * prediction_logits -> prediction_outputs, make fix-copies
      
      * uncommented @slow
      
      * minor changes
      
      * loss first in tuple
      
      * tuple and dict same ordering
      
      * style edits
      
      * minor changes
      
      * dict/tuple consistent enablement
      
      * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * fix formatting
      
      * formatting
      
      * usage tip
      
      * test on cpu only
      
      * add sample usage
      
      * change PatchTSMixerForClassification to PatchTSMixerForTimeSeriesClassification
      
      * push changes
      
      * fix copies
      
      * std scaling set to default True case
      
      * minor changes
      
      * stylechanges
      
      ---------
      Co-authored-by: default avatarArindam Jati <arindam.jati@ibm.com>
      Co-authored-by: default avatarvijaye12 <vijaye12@in.ibm.com>
      Co-authored-by: default avatarKashif Rasul <kashif.rasul@gmail.com>
      Co-authored-by: default avatarnnguyen <nnguyen@us.ibm.com>
      Co-authored-by: default avatarvijaye12 <vijaykr.e@gmail.com>
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      Co-authored-by: default avatarNam Nguyen <namctin@gmail.com>
      Co-authored-by: default avatarWesley Gifford <79663411+wgifford@users.noreply.github.com>
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      b242d0f2
  32. 01 Dec, 2023 1 commit
  33. 30 Nov, 2023 1 commit
    • Yoach Lacombe's avatar
      Add SeamlessM4T v2 (#27779) · 29f1aee3
      Yoach Lacombe authored
      
      
      * add working convertion script
      
      * first non-working version of modeling code
      
      * update modeling code (working)
      
      * make style
      
      * make fix-copies
      
      * add config docstrings
      
      * add config to ignore docstrings formatage due to unconventional markdown
      
      * fix copies
      
      * fix generation num_return_sequences
      
      * enrich docs
      
      * add and fix tests beside integration tests
      
      * update integration tests
      
      * update repo id
      
      * add tie weights and make style
      
      * correct naming in .md
      
      * fix imports and so on
      
      * correct docstrings
      
      * fix fp16 speech forward
      
      * fix speechencoder attention
      
      * make style
      
      * fix copied from
      
      * rename SeamlessM4Tv2-v2 to SeamlessM4Tv2
      
      * Apply suggestions on configuration
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * remove useless public models
      
      * fix private models + better naming for T2U models
      
      * clean speech encoder relative position embeddings
      
      * refactor chunk attention
      
      * add docstrings to chunk attention method
      
      * improve naming and docstrings
      
      * rename some attention variables + add temperature sampling in T2U model
      
      * rename DOCSTRINGS variable names
      
      * make style + remove 2 useless config parameters
      
      * enrich model card
      
      * remove any attention_head reference + fix temperature in T2U
      
      * new fmt and make style
      
      * Apply suggestions from code review
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      
      * rename spkr_id->speaker_id and change docstrings of get_char_input_ids
      
      * simplify v2attention
      
      * make style
      
      * Update seamless_m4t_v2.md
      
      * update code and tests with last update
      
      * update repo ids
      
      * fill article name, abstract andauthors
      
      * update not_doctested and slow_doc tests
      
      ---------
      Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      29f1aee3
  34. 29 Nov, 2023 1 commit
    • Kashif Rasul's avatar
      [Time series] Add patchtst (#27581) · af8acc47
      Kashif Rasul authored
      
      
      * add distribution head to forecasting
      
      * formatting
      
      * Add generate function for forecasting
      
      * Add generate function to prediction task
      
      * formatting
      
      * use argsort
      
      * add past_observed_mask ordering
      
      * fix arguments
      
      * docs
      
      * add back test_model_outputs_equivalence test
      
      * formatting
      
      * cleanup
      
      * formatting
      
      * use ACT2CLS
      
      * formatting
      
      * fix add_start_docstrings decorator
      
      * add distribution head and generate function to regression task
      
      add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput,  PatchTSTForRegressionOutput.
      
      * add distribution head and generate function to regression task
      
      add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput,  PatchTSTForRegressionOutput.
      
      * fix typos
      
      * add forecast_masking
      
      * fixed tests
      
      * use set_seed
      
      * fix doc test
      
      * formatting
      
      * Update docs/source/en/model_doc/patchtst.md
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      
      * better var names
      
      * rename PatchTSTTranspose
      
      * fix argument names and docs string
      
      * remove compute_num_patches and unused class
      
      * remove assert
      
      * renamed to PatchTSTMasking
      
      * use num_labels for classification
      
      * use num_labels
      
      * use default num_labels from super class
      
      * move model_type after docstring
      
      * renamed PatchTSTForMaskPretraining
      
      * bs -> batch_size
      
      * more review fixes
      
      * use hidden_state
      
      * rename encoder layer and block class
      
      * remove commented seed_number
      
      * edit docstring
      
      * Add docstring
      
      * formatting
      
      * use past_observed_mask
      
      * doc suggestion
      
      * make fix-copies
      
      * use Args:
      
      * add docstring
      
      * add docstring
      
      * change some variable names and add PatchTST before some class names
      
      * formatting
      
      * fix argument types
      
      * fix tests
      
      * change x variable to patch_input
      
      * format
      
      * formatting
      
      * fix-copies
      
      * Update tests/models/patchtst/test_modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * move loss to forward
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * formatting
      
      * fix a bug when pre_norm is set to True
      
      * output_hidden_states is set to False as default
      
      * set pre_norm=True as default
      
      * format docstring
      
      * format
      
      * output_hidden_states is None by default
      
      * add missing docs
      
      * better var names
      
      * docstring: remove default to False in output_hidden_states
      
      * change labels name to target_values in regression task
      
      * format
      
      * fix tests
      
      * change to forecast_mask_ratios and random_mask_ratio
      
      * change mask names
      
      * change future_values to target_values param in the prediction class
      
      * remove nn.Sequential and make PatchTSTBatchNorm class
      
      * black
      
      * fix argument name for prediction
      
      * add output_attentions option
      
      * add output_attentions to PatchTSTEncoder
      
      * formatting
      
      * Add attention output option to all classes
      
      * Remove PatchTSTEncoderBlock
      
      * create PatchTSTEmbedding class
      
      * use config in PatchTSTPatchify
      
      * Use config in PatchTSTMasking class
      
      * add channel_attn_weights
      
      * Add PatchTSTScaler class
      
      * add output_attentions arg to test function
      
      * format
      
      * Update doc with image patchtst.md
      
      * fix-copies
      
      * rename Forecast <-> Prediction
      
      * change name of a few parameters to match with PatchTSMixer.
      
      * Remove *ForForecasting class to match with other time series models.
      
      * make style
      
      * Remove PatchTSTForForecasting in the test
      
      * remove PatchTSTForForecastingOutput class
      
      * change test_forecast_head to test_prediction_head
      
      * style
      
      * fix docs
      
      * fix tests
      
      * change num_labels to num_targets
      
      * Remove PatchTSTTranspose
      
      * remove arguments in PatchTSTMeanScaler
      
      * remove arguments in PatchTSTStdScaler
      
      * add config as an argument to all the scaler classes
      
      * reformat
      
      * Add norm_eps for batchnorm and layernorm
      
      * reformat.
      
      * reformat
      
      * edit docstring
      
      * update docstring
      
      * change variable name pooling to pooling_type
      
      * fix output_hidden_states as tuple
      
      * fix bug when calling PatchTSTBatchNorm
      
      * change stride to patch_stride
      
      * create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder
      
      * formatting
      
      * initialize scalers with configs
      
      * edit output_hidden_states
      
      * style
      
      * fix forecast_mask_patches doc string
      
      * doc improvements
      
      * move summary to the start
      
      * typo
      
      * fix docstring
      
      * turn off masking when using prediction, regression, classification
      
      * return scaled output
      
      * adjust output when using distribution head
      
      * remove _num_patches function in the config
      
      * get config.num_patches from patchifier init
      
      * add output_attentions docstring, remove tuple in output_hidden_states
      
      * change SamplePatchTSTPredictionOutput and SamplePatchTSTRegressionOutput to SamplePatchTSTOutput
      
      * remove print("model_class: ", model_class)
      
      * change encoder_attention_heads to num_attention_heads
      
      * change norm to norm_layer
      
      * change encoder_layers to num_hidden_layers
      
      * change shared_embedding to share_embedding, shared_projection to share_projection
      
      * add output_attentions
      
      * more robust check of norm_type
      
      * change dropout_path to path_dropout
      
      * edit docstring
      
      * remove positional_encoding function and add _init_pe in PatchTSTPositionalEncoding
      
      * edit shape of cls_token and initialize it
      
      * add a check on the num_input_channels.
      
      * edit head_dim in the Prediction class to allow the use of cls_token
      
      * remove some positional_encoding_type options, remove learn_pe arg, initalize pe
      
      * change Exception to ValueError
      
      * format
      
      * norm_type is "batchnorm"
      
      * make style
      
      * change cls_token shape
      
      * Change forecast_mask_patches to num_mask_patches. Remove forecast_mask_ratios.
      
      * Bring PatchTSTClassificationHead on top of PatchTSTForClassification
      
      * change encoder_ffn_dim to ffn_dim and edit the docstring.
      
      * update variable names to match with the config
      
      * add generation tests
      
      * change num_mask_patches to num_forecast_mask_patches
      
      * Add examples explaining the use of these models
      
      * make style
      
      * Revert "Revert "[time series] Add PatchTST (#25927)" (#27486)"
      
      This reverts commit 78f6ed6c
      
      .
      
      * make style
      
      * fix default std scaler's minimum_scale
      
      * fix docstring
      
      * close code blocks
      
      * Update docs/source/en/model_doc/patchtst.md
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update tests/models/patchtst/test_modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/configuration_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * Update src/transformers/models/patchtst/modeling_patchtst.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      * fix tests
      
      * add add_start_docstrings
      
      * move examples to the forward's docstrings
      
      * update prepare_batch
      
      * update test
      
      * fix test_prediction_head
      
      * fix generation test
      
      * use seed to create generator
      
      * add output_hidden_states and config.num_patches
      
      * add loc and scale args in PatchTSTForPredictionOutput
      
      * edit outputs if if not return_dict
      
      * use self.share_embedding to check instead checking type.
      
      * remove seed
      
      * make style
      
      * seed is an optional int
      
      * fix test
      
      * generator device
      
      * Fix assertTrue test
      
      * swap order of items in outputs when return_dict=False.
      
      * add mask_type and random_mask_ratio to unittest
      
      * Update modeling_patchtst.py
      
      * add add_start_docstrings for regression model
      
      * make style
      
      * update model path
      
      * Edit the ValueError comment in forecast_masking
      
      * update examples
      
      * make style
      
      * fix commented code
      
      * update examples: remove config from from_pretrained call
      
      * Edit example outputs
      
      * Set default target_values to None
      
      * remove config setting in regression example
      
      * Update configuration_patchtst.py
      
      * Update configuration_patchtst.py
      
      * remove config from examples
      
      * change default d_model and ffn_dim
      
      * norm_eps default
      
      * set has_attentions to Trye and define self.seq_length = self.num_patche
      
      * update docstring
      
      * change variable mask_input to do_mask_input
      
      * fix blank space.
      
      * change logger.debug to logger.warning.
      
      * remove unused PATCHTST_INPUTS_DOCSTRING
      
      * remove all_generative_model_classes
      
      * set test_missing_keys=True
      
      * remove undefined params in the docstring.
      
      ---------
      Co-authored-by: default avatarnnguyen <nnguyen@us.ibm.com>
      Co-authored-by: default avatarNielsRogge <48327001+NielsRogge@users.noreply.github.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarNam Nguyen <namctin@gmail.com>
      Co-authored-by: default avatarWesley Gifford <79663411+wgifford@users.noreply.github.com>
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      af8acc47