1. 19 Mar, 2024 8 commits
  2. 18 Mar, 2024 5 commits
  3. 15 Mar, 2024 15 commits
  4. 14 Mar, 2024 8 commits
  5. 13 Mar, 2024 4 commits
    • Aaron Jimenez's avatar
      [docs] Remove broken ChatML format link from chat_templating.md (#29643) · f738ab3b
      Aaron Jimenez authored
      * remove ChatML link from en/
      
      * remove ChatML link in ja/
      
      * remove ChatML link in zh/
      f738ab3b
    • 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
    • Yih-Dar's avatar
    • Raushan Turganbay's avatar
      Fix batching tests for new models (Mamba and SegGPT) (#29633) · 5ac264d8
      Raushan Turganbay authored
      
      
      * fix batchinng tests for new models
      
      * Update tests/models/seggpt/test_modeling_seggpt.py
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      
      ---------
      Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      5ac264d8