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vas-bert-attn-refactors
64 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Ryan Mullins
|
c63cfd6a83
|
Gemma 3n (#39059)
* Gemma 3n * initial commit of Gemma 3n scaffold * Fixing param pass through on Gemm3p5RMSNorm * Adds Einsum layer to Gemma 3n * Updating EinsumLayer API * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Adds AltUp to Gemma 3n * Adding Gemma3p5 overall and text config with vision and audio config placeholders (#3) * Adding gemma3p5 text configs * Adding audio config placeholders * Adding a placeholder for vision configs * Updating MobileNetVisionConfig, inheriting TimmWrapperConfig * Updating text configs * Update src/transformers/models/gemma3p5/modular_gemma3p5.py Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Removing altup configs to accept the suggested configs * Update src/transformers/models/gemma3p5/modular_gemma3p5.py Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating altup config * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Addressing review comments and updating text configs * Adding a config for activation sparsity * Updating configs to pass through options to super class init and adjust some name prefixes * Updating laurel and altup with corrected config values * Normalizing sub_config initializers --------- Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating MLP with activation sparsity (#2) * Updating DecoderBlock for Gemma 3n (#3) * Initial Gemm3nTextModel (#4) NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference. * Adding KV Cache Sharing * Adds Einsum layer to Gemma 3n * Updating EinsumLayer API * Refactored kv cache sharing in attention * Adding KVStore for cache sharing * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update src/transformers/cache_utils.py Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Updating KV Cache Sharing implementation * Updating the q and k norm definitions in the attention module * Fixing name error for q,k,v RMS norm to use the right 3n module * Updating MLP with activation sparsity * Updating DecoderBlock for Gemma 3.5 * Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code * Isolating KV Cache logic to relevant components * Fixing logic error in Gemma3nAttention.forward * Refactoring caching contributions and fixing kv_store initialization * Simplifying Configs * Remove errant self from super init call * Bug fix in the Attention module - changing self.head_dim to config.head_dim * Bug fixes in the LaurelBlock and RMS Norm super init call * removing redundant code from a merge * Adding per_layer_inputs to TextModel * Adding preprocess embeddings with altup * Adds per-layer-to-single output and a host of TODOs * Integrating altup predict with the model workflow and other minor bug fixes * Using nn.Embedding temporarily for text model * It goes forward * Minor refactor of attention sparsity and RoPE initialization * Fixing duplicate rope_scaling param bug when loading from pretrained --------- Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Normalizing on altup_num_inputs config option * regenerating modeling file after syncing to HEAD * Use torch.std(..., unbiased=False) for activation sparsity (#8) * Refactoring to a single QVK Norm (#13) * AltUp: support scale_corrected_output (#14) * Converts einsums to nn.Linear (#7) * Converts einsums to nn.Linear * Removing unused variables * Aligning SharedKVCache with HybridCache (#11) * Alinging SharedKVStore with HybridCache * Remove KVStore. Refactor apply_rotary_pos_emb for sharing * Addressing review comments * Supporting split modality embeddings in Gemma3n (#10) * Adding the Embedder class * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Addressing review comments, adding audio embedding layers, integrating embedder with the remaining architecture, adding a forward method for conditional generation * Apply suggestions from code review Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Update modular Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> * Addressing review comments, prop drilling audio and vision configs to the text config * Removing TODO's that have been addressed * Simplify Embedder init and add audio embeddings * Embeddings refactor. Adds Gemma3nAudioEmbedder and Gemma3nVisionEmbedder * Refactoring vision and audio embeddings into ConditionalGeneration model --------- Co-authored-by: Ryan Mullins <ryan@ryanmullins.org> Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating attention mask for Gemma 3.5 (#15) * xxx_token_index to xxx_token_id * remvoing deprecated last_cache_position * Removing references to SigLIP * Always init per-layer inputs * Using torch.finfo().min for epsilon_tensor * Gemma3nDecoderLayer inherits from Gemma3DecoderLayer. Remove gating lambdas * fix modular GEMMA3N_INPUTS_DOCSTRING * Gemma3nAttention inherits from Gemma3Attention * Modular inheritance fixes * CausalLM conversion script for 4B model (#16) * Add Gemma3n Audio Encoder (#6) * initial commit of Gemma 3.5 scaffold * Fixing param pass through on Gemm3nRMSNorm * Adds Einsum layer to Gemma 3.5 * Updating EinsumLayer API * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Adds AltUp to Gemma 3n * Adding Gemma3n overall and text config with vision and audio config placeholders (#3) * Adding gemma3n text configs * Adding audio config placeholders * Adding a placeholder for vision configs * Updating MobileNetVisionConfig, inheriting TimmWrapperConfig * Updating text configs * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Removing altup configs to accept the suggested configs * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating altup config * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Addressing review comments and updating text configs * Adding a config for activation sparsity * Updating configs to pass through options to super class init and adjust some name prefixes * Updating laurel and altup with corrected config values * Normalizing sub_config initializers --------- Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating MLP with activation sparsity (#2) * Updating DecoderBlock for Gemma 3.5 (#3) * Initial Gemm3nTextModel (#4) NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference. * Adding KV Cache Sharing * Adds Einsum layer to Gemma 3.5 * Updating EinsumLayer API * Refactored kv cache sharing in attention * Adding KVStore for cache sharing * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update src/transformers/cache_utils.py Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Updating KV Cache Sharing implementation * Updating the q and k norm definitions in the attention module * Fixing name error for q,k,v RMS norm to use the right Gemma 3n module * Updating MLP with activation sparsity * Updating DecoderBlock for Gemma 3.5 * Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code * Isolating KV Cache logic to relevant components * Fixing logic error in Gemma3nAttention.forward * Refactoring caching contributions and fixing kv_store initialization * Simplifying Configs * Remove errant self from super init call * Bug fix in the Attention module - changing self.head_dim to config.head_dim * Bug fixes in the LaurelBlock and RMS Norm super init call * removing redundant code from a merge * Adding per_layer_inputs to TextModel * Adding preprocess embeddings with altup * Adds per-layer-to-single output and a host of TODOs * Integrating altup predict with the model workflow and other minor bug fixes * Using nn.Embedding temporarily for text model * It goes forward * Minor refactor of attention sparsity and RoPE initialization * Fixing duplicate rope_scaling param bug when loading from pretrained --------- Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Normalizing on altup_num_inputs config option * Adding audio encoder config * Adds high-level components for Audio Encoder * Implement uniform reducer for Audio Encoder * Adding placeholders for Conformer components in Audio Encoder * Adding placeholders for SubSampleConvProjection components in Audio Encoder * Adding SequenceLayer component placeholders * Implementing Gemma3nAudioEncoder with nn.Sequential * Implementing Gemma3nAudioSubSampleConvProjection with nn.Sequential * Implementing Conformer model with SequenceLayers * Use OrderedDict in nn.Sequential initializers * Implements sl.Residual in Torch with nn.Sequential and OrderedDict * Adopting a base SequenceLayer class with default forward() method * Implementing sl.GatedLinearUnit in Torch * Implementing sl.Swish in Torch * Implementing sl.ReLU in Torch * Implementing sl.Scale in Torch * Removing sl.Dropout after tree-shaking * Implementing sl.RMSNorm in Torch with fake shape * Implementing sl.GroupNorm in Torch * Implementing sl.Conv2d in Torch * Implementing sl.Dense in Torch * Removing sl.Delay layers, which act as pass-throughs * Connecting shapes to configs in initializers * Removing sl.Emit * Implementing sl.ExpandDims in Torch * Adding sl.GradientClipping to Torch * Implementing sl.DenseShaped in Torch * Implementing sl.LDPA in Torch * Removing unused sl.CombinedQKVProj class * Fixing erroneous type hint * Implemnenting sl.DepthwiseConv1D in Torch * Implementing sl.MaskInvalid in Torch * Fixes for initialization * Fixes for saving weights * Removing einsums per feedback from HF staff * Removing Sequence Layers idioms from audio encoder * Fixes for reviewer comments * CausalLM conversion script for 4B model * inv_timescales to non-persistent buffer * Addressing audio encoder Attention feedback * Addressing Gemma3nAudioSSCPConvBlock feedback * Addressing Gemma3nAudioConformerAttention feedback * Addressing padding feedback * Weights conversion loads audio state dict * Always use vision_config so saving works * Token id updates for configs * Stubs for interleaving audio embs * Addressing reviewer feedback --------- Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> * Fixing cache access error * Removing duplicate code from a bad merge * Gemma 3n Text + Vision Part 1 (#17) * testing utilities for numerics comparisons * Corrected einsum to nn.Linear weights conversion * Inherit scaled word embs from Gemma3 not Bart * Fixing transposes for collapsed linears * More transpose fixes * numpy api fix * RMSNorm: Explicit kwargs, scale_shift=0.0 when with_scale=True * Force AltUp to float32 * Updating debugging script for AudioEncoder debugging * Support divide_weight_by_sqrt_fan_in from JAX for per-layer inputs * Correcting attention einsum conversions * RMSNorm in type of x * Fixing douplicate laurel norm/gating * KV sharing using the right previous indices * Refactor kv shared index computation. Correct frac_shared_layers * Use num_shared_layers instead of inferring from a fraction * fixing a bug for logging * Fix shared data_ptrs in altup inits * rope: adjust proj -> norm -> rope to preserve computation (#20) * rope: adjust proj -> norm -> rope to preserve computation * Removing some breaking language model fluff in ConditionalGeneration * Consolidate query_states transforms --------- Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Vectorize the loops in AltUp (#19) * Vectorize the loops in AltUp * fix typo * Expanding to support batched inputs * remove extra debug script * Fix AltUp.forward --------- Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Add 'scale_shift=0.0, with_scale=True' to the final norm in TextModel * Convert norm to 1/sqrt (#21) * Convert norm to 1/sqrt * Scale shift change per Phil's rec * Adding default activation sparsity * Fixing 2B config in weights conversion script * Fixing RMSNorm parameters - adding scale_shift and with_scale * Correcting query pre-attention scaling * Adding query_rescale_scalar to text config * Adding layer_idx to MLP * Permafix for input_layernorm * Use 1/sqrt instead of rsqrt in DecoderLayer * Fix o_proj conversion * Conversion script update for vision encoder * Removing logging for debugging timm model * Fixing bugs in Gemma3nForConditionalGeneration for text generation * Generating the modeling_gemma3n.py file * Removing the addition of an erroneous line in the modeling file * Adding gemma3n text model to modeling_auto * Bugfix: Updating the interleaving of inputs_embeds and vision_embeds * Updating the modeling file with the latest bugfix changes * Updating models/auto for Gemma 3n * using AutoTokenizer in forward test * Adding processing_gemma3n.py * Gemma 3n configured for AutoModel. Conversion script updated. * Removing errant merge artifacts --------- Co-authored-by: Mayank Chaturvedi <imayank@google.com> Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com> Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> * Removing errant debugging statements from Gemma 3 * Gemma3n audio model (#18) * testing utilities for numerics comparisons * Implement CumulativeGroupNorm and add to SubSampleConvProjection and SSCPConvBlock * Add audio version of forward script based on RyanMullins' implementation * Updating to match encoder tests. WIP: config question needs resolving * Updates to audio classes to enable end-to-end running * Removing vestigial classes, cleaning up print statements * Adding SiLU / Swish to audio conformer feed forward block * Shifted Gemma3p5Audio naming prefix to Gemma3NanoAudio * Adding outputs to audio test * Fixes to padding in SSCP and 1D convolution, align RMS Norm with wider model * Update forward test to load from local weights * Update conversion to process / output audio layers * Update __all__ to export audio encoder * AutoModel registration for Gemma 3n Audio * Use AutoModel for ConditionalGeneration.audio_tower * Fixing input_proj_linear transpose * Fixing Gemma3NanoAudioConformerAttention.post conversion * Fixing Gemma3NanoAudioSSCPConvBlock.conv weights conversion * Correcting indentation issue on Gemma3p5RMSNorm --------- Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Text + Vision Part 2 (#23) * Updates for ConditionalGeneration.get_image_features * Adding a WIP draft of image_processing_gemma3p5.py * Update src/transformers/models/gemma3p5/modular_gemma3p5.py Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Modular conversion after github suggested change * Text + image gives good results * Fixing image size preset * Updating configs for the 2B variant in the conversion script * Using final generation config in conversion script --------- Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Audio Integration (#12) * initial commit of Gemma 3n scaffold * Fixing param pass through on Gemm3nRMSNorm * Adds Einsum layer to Gemma 3n * Updating EinsumLayer API * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Adds AltUp to Gemma 3n * Adding Gemma 3n overall and text config with vision and audio config placeholders (#3) * Adding Gemma 3n text configs * Adding audio config placeholders * Adding a placeholder for vision configs * Updating MobileNetVisionConfig, inheriting TimmWrapperConfig * Updating text configs * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Removing altup configs to accept the suggested configs * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating altup config * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Addressing review comments and updating text configs * Adding a config for activation sparsity * Updating configs to pass through options to super class init and adjust some name prefixes * Updating laurel and altup with corrected config values * Normalizing sub_config initializers --------- Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Updating MLP with activation sparsity (#2) * Updating DecoderBlock for Gemma 3n (#3) * Initial Gemma3nTextModel (#4) NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference. * Adding KV Cache Sharing * Adds Einsum layer to Gemma 3n * Updating EinsumLayer API * Refactored kv cache sharing in attention * Adding KVStore for cache sharing * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update modular Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Update src/transformers/cache_utils.py Co-authored-by: Ryan Mullins <ryanmullins@google.com> * Undoing erroneous force push * Reverting RMSNorm to with_scale by default * Adds LAuReL to Gemma 3n * Updating KV Cache Sharing implementation * Updating the q and k norm definitions in the attention module * Fixing name error for q,k,v RMS norm to use the right 3n module * Updating MLP with activation sparsity * Updating DecoderBlock for Gemma 3n * Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code * Isolating KV Cache logic to relevant components * Fixing logic error in Gemma3nAttention.forward * Refactoring caching contributions and fixing kv_store initialization * Simplifying Configs * Remove errant self from super init call * Bug fix in the Attention module - changing self.head_dim to config.head_dim * Bug fixes in the LaurelBlock and RMS Norm super init call * removing redundant code from a merge * Adding per_layer_inputs to TextModel * Adding preprocess embeddings with altup * Adds per-layer-to-single output and a host of TODOs * Integrating altup predict with the model workflow and other minor bug fixes * Using nn.Embedding temporarily for text model * It goes forward * Minor refactor of attention sparsity and RoPE initialization * Fixing duplicate rope_scaling param bug when loading from pretrained --------- Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Normalizing on altup_num_inputs config option * Adding audio encoder config * Adds high-level components for Audio Encoder * Implement uniform reducer for Audio Encoder * Adding placeholders for Conformer components in Audio Encoder * Adding placeholders for SubSampleConvProjection components in Audio Encoder * Adding SequenceLayer component placeholders * Implementing Gemma3nAudioEncoder with nn.Sequential * Implementing Gemma3nAudioSubSampleConvProjection with nn.Sequential * Implementing Conformer model with SequenceLayers * Use OrderedDict in nn.Sequential initializers * Implements sl.Residual in Torch with nn.Sequential and OrderedDict * Adopting a base SequenceLayer class with default forward() method * Implementing sl.GatedLinearUnit in Torch * Implementing sl.Swish in Torch * Implementing sl.ReLU in Torch * Implementing sl.Scale in Torch * Removing sl.Dropout after tree-shaking * Implementing sl.RMSNorm in Torch with fake shape * Implementing sl.GroupNorm in Torch * Implementing sl.Conv2d in Torch * Implementing sl.Dense in Torch * Removing sl.Delay layers, which act as pass-throughs * Connecting shapes to configs in initializers * Removing sl.Emit * Implementing sl.ExpandDims in Torch * Adding sl.GradientClipping to Torch * Implementing sl.DenseShaped in Torch * Implementing sl.LDPA in Torch * Removing unused sl.CombinedQKVProj class * Fixing erroneous type hint * Implemnenting sl.DepthwiseConv1D in Torch * Implementing sl.MaskInvalid in Torch * Fixes for initialization * Fixes for saving weights * Removing einsums per feedback from HF staff * Removing Sequence Layers idioms from audio encoder * Fixes for reviewer comments * Converting sl.Frontend to FeatureExtractor * Updates for ConditionalGeneration.get_image_features * Adding a WIP draft of image_processing_gemma3n.py * Update modular Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> * Modular conversion after github suggested change * Text + image gives good results * Fixing image size preset * Draft of audio data in chat template * Removing image processing. Using SigLIP instead. * Audio input going end-to-end * Fixing dtype issues in audio encoder * x-lib formatting consistency * Adding example data * Save preprocessor_config.json from conversion script * Instrumentaiton for debugging * Additional instrumentation for preprocessing debugging * Updates to preprocessor, padding; produces correct end-to-end results on sample * Tackling configuraiton TODOs * Start of feature extractor refatcor * Adds Numpy version of USM extractor, removes Torch version and dependencies * Fixing AltUp.correct coef permute * Supporting batches of single audio segment inputs * Docstrings updates for config * In-lining audio feature extraction * Adjustments to conversion script and smoke test script --------- Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: pculliton <phillipculliton@gmail.com> * Gemma 3n renaming * Removing test data and utilities * Renaming test files * Gemma 3n refactor * Fix tokenizer config in conversion script * Address reviewer feedback * FeatureExtractor returns float32 by default * Adding basic tests for audio, and input name for audio encoder * Audio integration test, updates to model_id for other integration tests * Use scales for q and k norms (#26) * Update audio integration test to use HF dataset * Reviewer feedback * Expand embedding table to full vocab size in weights conversion * Mix-n-match MatFormers for Gemma 3n (#25) * Remove in-place operations (#30) * chore: removing inplace ops * remove [tensor] * n pattern * chore: reviewer feedback in AudioEncoder and AltUp * More grad clipping * Dynamo compatibility * fix: cache slicing error * chore: simplify shared kv cache slicing * chore: vision encoder rename in timm * fix: image processor do_normalize=False * fixup: style * chore: model_doc * fix: docs for code quality * chore: repo consistency * fix: RMSNorm in float as in prior Gemmas * fix: per_layer_inputs = None * chore: Gemma3nForCausalLM from Gemma3nForConditionalGeneration checkpoint * chore: repo consistency * Add initial unit tests for Gemma3nAudioFeatureExtractor (#27) * Add initial unit tests for Gemma3nAudioFeatureExtractor * Add basic unit tests for Gemma3nProcessor (#28) Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> * parameterize tests --------- Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> * chore: code style * fix: test cases * style and consistency * fix config in the test to be coherent with layer cache sharing * fix hidden states in tests and code * inits and mappings * fix modality prefixes * test order and prefixes * fix test exception * fix class order and reduce model size for faster tests * restore _checkpoint_conversion_mapping to load Caual from Conditional * fix config mapping! * fix: reviewer feedback --------- Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: raushan <raushan@huggingface.co> Co-authored-by: Mayank Chaturvedi <imayank@google.com> Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com> Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> Co-authored-by: pculliton <phillipculliton@gmail.com> Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com> Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * fix import test * add model args * auto_docstring * replace test path * consistency * skip tests for now * fix docstring for doc builder * skip unused attr --------- Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com> Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com> Co-authored-by: raushan <raushan@huggingface.co> Co-authored-by: Mayank Chaturvedi <imayank@google.com> Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com> Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com> Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> Co-authored-by: pculliton <phillipculliton@gmail.com> Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com> Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> Co-authored-by: Arthur <arthur.zucker@gmail.com> |
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Yoni Gozlan
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b6b4d43d6d
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Add support for auto_docstring with model outputs (#38242)
* experiment auto_docstring model outputs * Fix PatchTSMixer * Add check model output docstring to check_auto_docstring and fix all model outputs docstring * add reordering of docstring in check_docstrings * add check for redundant docstring in check_docstrings, remove redundant docstrings * refactor check_auto_docstring * make style * fix copies * remove commented code * change List-> list Tuple-> tuple in docstrings * fix modular * make style * Fix modular vipllava --------- Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co> |
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Matt
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508a704055
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No more Tuple, List, Dict (#38797)
* No more Tuple, List, Dict * make fixup * More style fixes * Docstring fixes with regex replacement * Trigger tests * Redo fixes after rebase * Fix copies * [test all] * update * [test all] * update * [test all] * make style after rebase * Patch the hf_argparser test * Patch the hf_argparser test * style fixes * style fixes * style fixes * Fix docstrings in Cohere test * [test all] --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> |
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Arthur
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5f5ccfdc54
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[AutoDocstring] Based on inspect parsing of the signature (#33771)
* delete common docstring * nit * updates * push * fixup * move stuff around fixup * no need for dataclas * damn nice modular * add auto class docstring * style * modular update * import autodocstring * fixup * maybe add original doc! * more cleanup * remove class do cas well * update * nits * more celanup * fix * wups * small check * updatez * some fixes * fix doc * update * nits * try? * nit * some updates * a little bit better * where ever we did not have help we are not really adding it! * revert llama config * small fixes and small tests * test * fixup * more fix-copies * updates * updates * fix doc building * style * small fixes * nits * fix-copies * fix merge issues faster * fix merge conf * nits jamba * ? * working autodoc for model class and forward except returns and example * support return section and unpack kwargs description * nits and cleanup * fix-copies * fix-copies * nits * Add support for llava-like models * fixup * add class args subset support * add examples inferred from automodel/pipelines * update ruff * autodocstring for Aria, Albert + fixups * Fix empty return blocks * fix copies * fix copies * add autodoc for all fast image processors + align, altclip * fix copies * add auto_doc for audio_spectrogram, auto_former, bark, bamba * Drastically improve speed + add bart beit bert * add autodoc to all bert-like models * Fix broken doc * fix copies * fix auto_docstring after merge * add autodoc to models * add models * add models * add models and improve support for optional, and custom shape in args docstring * update fast image processors * refactor auto_method_docstring in args_doc * add models and fix docstring parsing * add models * add models * remove debugging * add models * add fix_auto_docstrings and improve args_docs * add support for additional_info in args docstring * refactor (almost) all models * fix check docstring * fix -copies * fill in all missing docstrings * fix copies * fix qwen3 moe docstring * add documentation * add back labels * update docs and fix can_return_tuple in modular files * fix LongformerForMaskedLM docstring * add auto_docstring to _toctree * remove auto_docstring tests temporarily * fix copyrights new files * fix can_return_tuple granite hybrid * fix fast beit * Fix empty config doc * add support for COMMON_CUSTOM_ARGS in check_docstrings and add missing models * fix code block not closed flava * fix can_return_tuple sam hq * Fix Flaubert dataclass --------- Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co> Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com> |
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sushmanth reddy
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65e940208c
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Samhq model addition (#35147)
* added the configuartion for sam_hq * added the modeelling for sam_hq * added the sam hq mask decoder with hq features * added the code for the samhq * added the code for the samhq * added the code for the samhq * Delete src/transformers/models/sam_hq/modelling_sam_hq.py * added the code for the samhq * added the code for the samhq * added the chnages for the modeelling * added the code for sam hq for image processing * added code for the sam hq model * added the required changes * added the changes * added the key mappings for the sam hq * adding the working code of samhq * added the required files * adding the pt object * added the push to hub account * added the args for the sam maks decoder * added the args for the sam hq vision config * aded the some more documentation * removed the unecessary spaces * all required chnages * removed the image processor * added the required file * added the changes for the checkcopies * added the code for modular file * added the changes for the __init file * added the code for the interm embeds * added the code for sam hq * added the changes for modular file * added the test file * added the changes required * added the changes required * added the code for the * added the cl errors * added the changes * added the required changes * added the some code * added the code for the removing image processor * added the test dimensins * added the code for the removing extra used variables * added the code for modeluar file hf_mlp for a better name * removed abbrevaation in core functionality * removed abbrevaation in core functionality * .contiguous() method is often used to ensure that the tensor is stored in a contiguous block of memory * added the code which is after make fixup * added some test for the intermediate embeddings test * added the code for the torch support in sam hq * added the code for the updated modular file * added the changes for documentations as mentioned * removed the heading * add the changes for the code * first mentioned issue resolved * added the changes code to processor * added the easy loading to init file * added the changes to code * added the code to changes * added the code to work * added the code for sam hq * added the code for sam hq * added the code for the point pad value * added the small test for the image embeddings and intermediate embedding * added the code * added the code * added the code for the tests * added the code * added ythe code for the processor file * added the code * added the code * added the code * added the code * added the code * added the code for tests and some checks * added some code * added the code * added the code * added some code * added some code * added the changes for required * added the code * added the code * added the code * added the code * added the code * added the code * added the code * added the code * added the code * added the code * added some changes * added some changes * removed spaces and quality checks * added some code * added some code * added some code * added code quality checks * added the checks for quality checks * addded some code which fixes test_inference_mask_generation_no_point * added code for the test_inference_mask_generation_one_point_one_bb * added code for the test_inference_mask_generation_one_point_one_bb_zero * added code for the test_inference_mask_generation_one_box * added some code in modelling for testing * added some code which sort maks with high score * added some code * added some code * added some code for the move KEYS_TO_MODIFY_MAPPING * added some code for the unsqueeze removal * added some code for the unsqueeze removal * added some code * added some code * add some code * added some code * added some code * added some testign values changed * added changes to code in sam hq for readbility purpose * added pre commit checks * added the fix samvisionmodel for compatibilty * added the changes made on sam by cyyever * fixed the tests for samhq * added some the code * added some code related to init file issue during merge conflicts * remobved the merge conflicts * added changes mentioned by aruther and mobap * added changes mentioned by aruther and mobap * solving quality checks * added the changes for input clearly * added the changes * added changes in mask generation file rgearding model inputs and sam hq quargs in processor file * added changes in processor file * added the Setup -> setupclass conversion * added the code mentioned for processor * added changes for the code * added some code * added some code * added some code --------- Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> |
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Huajie Tan
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6f7ea1cf00
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Add MLCD model (#36182)
* Add MLCD model * Update codes for auto-mapping * Add test scripts for MLCD * Update doc for MLCD model * Fix import error * Fix import error * Fix CI error for attention_outputs * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix CI error for initialization * Fix code style for CI * Fix code style for CI * Reformat codes and docs for CI test * Reformat codes and docs for CI test * Remove unused attributes for CI test * Fix style for CI test * List MLCD in flash_attn doc * Fix: typos, modulars, refactors from suggestions * Refactoring convert_mlcd_weights_to_hf.py from suggestions * Fix: docs conflicts * Fix error for CI test * Fix style for CI test * Add integration test for MLCD * Refactoring by class inheritance * Fix: refactor attention interface, adjust codes * Fix: merging conflicts * Fix: merging conflicts * Fix: style for CI test * Fix: style for CI test * Fix: set test_resize_embeddings to be False * Fix: initializer for CI test * Fix: conflicts, CI test, warning and refactoring * Fix: merging conflicts * Refactor * Update docs * Fix mistakes * Remove unused args and fix multi-gpu error * Revert position_embeddings * Solve conflicts * Solve conflicts * Remove dummy * Update _init_weights * Update _init_weights * Update _init_weights for CI test |
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Alex Brooks
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2515a5a290
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Expose blip2qformer (#37254)
* Expose blip2qformer * Add missing args to blip2 config |
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Arthur
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2da82e432d
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Multiple llama4 fixe (#37353)
* update for fixes * more fixes * fuxix dynamic cache? * style * fix both traiining and generating. Eager seems alright * dynamic does not work * fix most cases, use_cache or not, eager or not, no default cache (ex: not training but you want to get cache states) * should be final fixes * fix more stuff no cat * style * fix * style * final sytle * qualityeioiwhjfaopsejdpofqsdjkfjha;wesdhgfkjlqsw.denghjkaswednkgs * fix * revert |
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Arthur
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25b7f27234
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Add llama4 (#37307)
* remove one of the last deps * update fast image processor after refactor * styling * more quality of life improvements * nit * update * cleanups * some cleanups * vllm updates * update fake image token * [convert] Fix typo * [convert] Strip extraneous bytes from shards * [convert] Minor fixes * [convert] Use num_experts * multi-image fixes in modeling + processor * fixup size * 128 experts * Use default rope * Unfuse mlp * simplify a lot inputs embeds merging * remove .item() 👀 * fix from review * Address feedback * Use None "default" for rope_scaling. Add eot. * set seed * return aspect ratios and bug fixes * Moe 128 rebased (#8) * 128 experts * Use default rope * Unfuse mlp * Address feedback * Use None "default" for rope_scaling. Add eot. * Meta/llama quant compat (#7) * add quant compatible model & conversion code for llama4 * fix a few issues * fix a few issues * minor type mapping fix --------- Co-authored-by: Lu Fang <fanglu@fb.com> * use a new config parameter to determine which model definition to use for MoE --------- Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: Lu Fang <fanglu@fb.com> * un-comment write_tokenizer from converting script * remove un-used imports * [llama4] Pop aspect_ratios from image processor output in Llama4Processor Signed-off-by: Jon Swenson <jmswen@gmail.com> * Fix parameter_count name * Update src/transformers/models/llama4/configuration_llama4.py * nit * Add changes for no_rope, moe_layers, chunked attention. Just need to test all * Update src/transformers/models/llama4/image_processing_llama4_fast.py * nit * fix post merge with main * support flex attention * fixes * fix * add layer * small updates * rebase and delete llm_compressor * nit * [llama4/mm] Add back <|image|> token that delimits global tile * [llama4/mm] Fix Llama 4 image processing unit tests * add explicit dtype Signed-off-by: Jon Swenson <jmswen@gmail.com> * sdpa works * comment todo small * fix model loading Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * revert * nits * small fix for TP on 1 node * Read new params from config * Add <|eom|> * lol don't know how this got here * adding fp8 * Save processor, fix chat template * style * Add boi/eoi tokens We don't use them. * fixes for now flex seems to work :) * updates * nits * updates * missking keys * add context parallel * update * update * fix * nits * add worldsize and make eager attn work for vision * Ignore new key present in base models * add tp_plan * fix nope Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * minor fix Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * Clean up Llama4 vision model * current updates * add support for `attn_temperature_tuning` * add floor scale * add missing attn scales * push what works, dirty trick for the device synch * oups * Fix pad_token_id See https://huggingface.co/ll-re/Llama-4-Scout-17B-16E/discussions/2/files Confirmed in the original codebase. * fix causallml loading * rm * fix tied-weights * fix sdpa * push current version * should work with both short and long * add compressed_tensos & fix fbgemm tp * Fix flex impl * style * chunking * try to revert the potentially breaking change * fix auto factory * fix shapes in general * rm processing * commit cache utils cleanup * Fix context length * fix * allocate * update tp_plan * fix SDPA! * Add support for sparse `Llama4TextMoe` layer from the kernel hub * cleanup * better merge * update * still broken fixing now * nits * revert print * Write max_position_embeddings and max_model_length * Update modeling_llama4.py * Save attention_chunk_size * Sync eos terminators * Read initializer_range * style * remove `dict` * fix * eager should use `chunked_attention_mask` * revert * fixup * fix config * Revert "Merge pull request #36 from huggingface/sparse-llama4-moe" This reverts commit |
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cyyever
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6cc9c8d7d1
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Remove deprecated batch_size parameter (#37007) | ||
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Yih-Dar
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c6814b4ee8
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Update ruff to 0.11.2 (#36962)
* update * update * update --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> |
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Cyril Vallez
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4303d88c09
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Add Phi4 multimodal (#36939)
* raw start * update * update * add to imports * update * up * simplify configs * clean configs * style * typos * Update convert_phi4_multimodal_weights_to_hf.py * Update convert_phi4_multimodal_weights_to_hf.py * fix * up * up * up * Update convert_phi4_multimodal_weights_to_hf.py * Update convert_phi4_multimodal_weights_to_hf.py * up * up * up * Update feature_extraction_phi4_multimodal.py * up * up * up * up * up * simplify configs * typo * cut code * typo * typo * typo * re * typo * up * up * up * add tests * fix * fix * Update test_modeling_phi4_multimodal.py * up * Update test_modeling_phi4_multimodal.py * doc * fix * up * up * up * up * up * up * simplify * up * simplify * config docstrings * cleanup * clean * typo * typo * fix * Update phi4_multimodal.md * fix * fix * Update test_modeling_phi4_multimodal.py * update * simplify reshapes and permutes * up * simplify special tokens * simplify processor a lot * Update processing_phi4_multimodal.py * Update processing_phi4_multimodal.py * switch to fast processor * image processor * Update image_processing_phi4_multimodal_fast.py * add lora extraction to converter * Update convert_phi4_multimodal_weights_to_hf.py * Update __init__.py * add AudioInput type in audio_utils * rewrite feature_extraction: support torch batched FFT * input_audio_embeds -> audio_input_features, input_image_embeds -> image_pixel_values * test update * not mono channel warning update * remove auto maps from processor * kargs dispatch in processor * simplify kwargs dispatch * simplify merging * remove default sampling rate * style * Update test_modeling_phi4_multimodal.py * update doc * doc * torch only feature extractor * make fake tokens adjustable * Update feature_extraction_phi4_multimodal.py * fix * Update processing_phi4_multimodal.py * simplify mask * last touch * fix copies * style * Update audio_utils.py * style * Update feature_extraction_phi4_multimodal.py * Update __init__.py * docstrings * copies * fix all checks * back to fix-copies * trigger CIs * Update feature_extraction_phi4_multimodal.py * improve tests with multimodal inputs * trigger CIs --------- Co-authored-by: Eustache Le Bihan <eulebihan@gmail.com> |
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Afanti
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d84569387f
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chore: fix typos in utils module (#36668)
* chore: fix typos in utils module * chore: fix typos in utils module * chore: fix typos in utils module * chore: fix typos in utils module * chore: fix typos in utils module * chore: fix typos in utils module |
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Yoni Gozlan
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fa56dcc2ab
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Refactoring of ImageProcessorFast (#35069)
* add init and base image processing functions * add add_fast_image_processor to transformers-cli * add working fast image processor clip * add fast image processor to doc, working tests * remove "to be implemented" SigLip * fix unprotected import * fix unprotected vision import * update ViTImageProcessorFast * increase threshold slow fast ewuivalence * add fast img blip * add fast class in tests with cli * improve cli * add fast image processor convnext * add LlavaPatchingMixin and fast image processor for llava_next and llava_onevision * add device kwarg to ImagesKwargs for fast processing on cuda * cleanup * fix unprotected import * group images by sizes and add batch processing * Add batch equivalence tests, skip when center_crop is used * cleanup * update init and cli * fix-copies * refactor convnext, cleanup base * fix * remove patching mixins, add piped torchvision transforms for ViT * fix unbatched processing * fix f strings * protect imports * change llava onevision to class transforms (test) * fix convnext * improve formatting (following Pavel review) * fix handling device arg * improve cli * fix * fix inits * Add distinction between preprocess and _preprocess, and support for arbitrary kwargs through valid_extra_kwargs * uniformize qwen2_vl fast * fix docstrings * add add fast image processor llava * remove min_pixels max_pixels from accepted size * nit * nit * refactor fast image processors docstrings * cleanup and remove fast class transforms * update add fast image processor transformers cli * cleanup docstring * uniformize pixtral fast and make _process_image explicit * fix prepare image structure llava next/onevision * Use typed kwargs instead of explicit args * nit fix import Unpack * clearly separate pops and gets in base preprocess. Use explicit typed kwargs * make qwen2_vl preprocess arguments hashable |
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Joao Gante
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80dbbd103c
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🧹 remove generate-related objects and methods scheduled for removal in v4.48 (#35677)
* remove things scheduled for removal * make fixup |
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Aymeric Roucher
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9ad4c93536
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Add Aria (#34157)
* Add Aria --------- Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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João Marcelo
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50189e36a6
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Add I-JEPA (#33125)
* first draft * add IJepaEmbeddings class * fix copy-from for IJepa model * add weight conversion script * update attention class names in IJepa model * style changes * Add push_to_hub option to convert_ijepa_checkpoint function * add initial tests for I-JEPA * minor style changes to conversion script * make fixup related * rename conversion script * Add I-JEPA to sdpa docs * minor fixes * adjust conversion script * update conversion script * adjust sdpa docs * [run_slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * formatting issues * adjust modeling to modular code * add IJepaModel to objects to ignore in docstring checks * [run-slow] ijepa * fix formatting issues * add usage instruction snippet to docs * change pos encoding, add checkpoint for doc * add verify logits for all models * [run-slow] ijepa * update docs to include image feature extraction instructions * remove pooling layer from IJepaModel in image classification class * [run-slow] ijepa * remove pooling layer from IJepaModel constructor * update docs * [run-slow] ijepa * [run-slow] ijepa * small changes * [run-slow] ijepa * style adjustments * update copyright in init file * adjust modular ijepa * [run-slow] ijepa |
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Yoni Gozlan
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203e27059b
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Add image text to text pipeline (#34170)
* Standardize image-text-to-text-models-output add post_process_image_text_to_text to chameleon and cleanup Fix legacy kwarg behavior and deprecation warning add post_process_image_text_to_text to qwen2_vl and llava_onevision Add post_process_image_text_to_text to idefics3, mllama, pixtral processor * nit var name post_process_image_text_to_text udop * nit fix deprecation warnings * Add image-text-to-text pipeline * add support for image url in chat template for pipeline * Reformat to be fully compatible with chat templates * Add tests chat template * Fix imports and tests * Add pipeline tag * change logic handling of single prompt ans multiple images * add pipeline mapping to models * fix batched inference * fix tests * Add manual batching for preprocessing * Fix outputs with nested images * Add support for all common processing kwargs * Add default padding when multiple text inputs (batch size>1) * nit change version deprecation warning * Add support for text only inference * add chat_template warnings * Add pipeline tests and add copied from post process function * Fix batched pipeline tests * nit * Fix pipeline tests blip2 * remove unnecessary max_new_tokens * revert processing kosmos2 and remove unnecessary max_new_tokens * fix pipeline tests idefics * Force try loading processor if pipeline supports it * revert load_processor change * hardcode loading only processor * remove unnecessary try except * skip imagetexttotext tests for kosmos2 as tiny model causes problems * Make code clearer * Address review comments * remove preprocessing logic from pipeline * fix fuyu * add BC resize fuyu * Move post_process_image_text_to_text to ProcessorMixin * add guard in post_process * fix zero shot object detection pipeline * add support for generator input in pipeline * nit * change default image-text-to-text model to llava onevision * fix owlv2 size dict * Change legacy deprecation warning to only show when True |
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MAHIR DAIYAN
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843e5e20ca
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Add Flax Dinov2 (#31960)
* tfmsenv restored in main * installed flax * forward pass done and all tests passed * make fix-copies and cleaning the scripts * fixup attempt 1 * fixup attempt 2 * fixup third attempt * fixup attempt 4 * fixup attempt 5 * dinov2 doc fixed * FlaxDinov2Model + ForImageClassification added to OBJECTS_TO_IGNORE * external pos_encoding layer removed * fixup attempt 6 * fixed integration test values * fixup attempt 7 * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * comments removed * comment removed from the test * fixup * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * new fixes 1 * interpolate_pos_encoding function removed * droppath rng fixed, pretrained beit copied-from still not working * modeling_flax_dinov2.py reformatted * Update tests/models/dinov2/test_modeling_flax_dinov2.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * added Copied from, to the tests * copied from statements removed from tests * fixed copied from statements in the tests * [run_slow] dinov2 --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Joao Gante
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cf32ee1753
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Cache: use batch_size instead of max_batch_size (#32657)
* more precise name * better docstrings * Update src/transformers/cache_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Joao Gante
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70d5df6107
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Generate: unify LogitsWarper and LogitsProcessor (#32626)
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Joao Gante
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026a173a64
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Repo checks: skip docstring checks if not in the diff (#32328)
* tmp * skip files not in the diff * use git.Repo instead of an external subprocess * add tiny change to confirm that the diff is working on pushed changes * add make quality task * more profesh main commit reference |
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Joao Gante
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535fe78b9f
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Repo: remove exceptions in check_docstrings (#32259)
remove exceptions |
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Matt
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065729a692
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Remove ConversationalPipeline and Conversation object (#31165)
* Remove ConversationalPipeline and Conversation object, as they have been deprecated for some time and are due for removal * Update not-doctested.txt * Fix JA and ZH docs * Fix JA and ZH docs some more * Fix JA and ZH docs some more |
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Arthur
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673440d073
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update ruff version (#30932)
* update ruff version * fix research projects * Empty * Fix errors --------- Co-authored-by: Lysandre <lysandre@huggingface.co> |
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João David
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d2cec09baa
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Add TF swiftformer (#23342)
* Duplicate swiftformer * Convert SwiftFormerPatchEmbedding * Convert SwiftFormerEmbeddings * Convert TFSwiftFormerMlp * Convert TFSwiftFormerConvEncoder * Convert TFSwiftFormerLocalRepresentation * convert TFSwiftFormerEncoderBlock * Convert SwiftFormerStage * Convert SwiftFormerEncoder * Add TFSWiftFormerPreTrainedModel * Convert SwiftFormerForImageClassification * Add kwargs and start drop path * Fix syntax * Change Model class name * Add TFSwiftFormer to __init__ * Duplicate test_modeling_swiftformer * First test conversions * Change require_torch to require_tf * Add exports to swiftformer __init__ * Add TFSwiftFormerModel wrapper * Fix __init__ and run black * Remove docstring from MainLayer, fix padding * Use keras.layers.Activation on keras.Sequential * Fix swiftformer exports * Fix activation layer from config * Remove post_inits * Use tf.keras.layers.ZeroPadding2D * Convert torch normalize * Change tf test input shape * Fix softmax and reduce_sum * Convert expand_dims and repeat * Add missing reshape and tranpose * Simplify TFSwiftFormerEncoderBlock.call * Fix mismatch in patch embeddings * Fix expected output shape to match channels last * Fix swiftformer typo * Disable test_onnx * Fix TFSwiftFormerForImageClassification call * Add unpack inputs * Convert flatten(2).mean(-1) * Change vision dummy inputs (to be reviewed) * Change test_forward_signature to use .call * Fix @unpack_inputs * Set return_tensors="tf" and rename class * Rename wrongly named patch_embeddings layer * Add serving_output and change dummy_input shape * Make dimensions BCHW and transpose inside embedding layer * Change SwiftFormerEncoderBlock * Fix ruff problems * Add image size to swiftformer config * Change tranpose to MainLayer and use -1 for reshape * Remove serving_outputs and dummy_inputs * Remove test_initialization test from tf model * Make Sequential component a separate layer * Fix layers' names * Tranpose encoder outputs * Fix tests and check if hidden states is not None * Fix TFSwiftFormerForImageClassification * Run make fixup * Run make fix-copies * Update modeling_tf_auto * Update docs * Fix modeling auto mapping * Update modelint_tf_swiftformer docs * Fill image_size doc and type * Add reduction=None to loss computation * Update docs * make style * Debug: Delete the tip to see if that changes anything * Re-add tip * Remove add_code_sample_docstrings * Remove unused import * Get the debug to actually tell us the problem it has with the docs * Try a substitution to match the PyTorch file? * Add swiftformer to ignore list * Add build() methods * Update copyright year Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove FIXME comment * Remove from_pt * Update copyright year Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Rename one-letter variables * Remove FIXMEs related to momentum * Remove old TODO comment * Remove outstanding FIXME comments * Get dropout rate from config * Add specific dropout config for MLP * Add convencoder dropout to config * Pass config to SwiftFormerDropPath layer * Fix drop_path variable name and add Adapted from comment * Run ruff * Removed copied from comment * Run fix copies * Change drop_path to identity to match pt * Cleanup build() methods and move to new keras imports * Update docs/source/en/model_doc/swiftformer.md Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> * Raise error if drop_path_rate > 0.0 * Apply suggestions from code review Replace (self.dim), with self.dim, Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> * Remove drop_path function * Add training to TFSwiftFormerEncoder * Set self.built = True last Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Should have been added to previous commit Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Change default_feature_extractor to default_image_processor Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Import Keras from modeling_tf_utils * Remove relative import * Run ruff --fix * Move import keras to tf_available * Add copied from comment to test_forward_signature * Reduce batch size and num_labels * Extract loss logic to hf_compute_loss * Run ruff format --------- Co-authored-by: Matt <rocketknight1@gmail.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> |
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Yoach Lacombe
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c43b380e70
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Add MusicGen Melody (#28819)
* 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: Sanchit 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: Sanchit 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: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Arthur
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594c1277b2
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[ gemma] Adds support for Gemma 💎 (#29167)
* inital commit * update * update conversion checkpoint * update conversion script * nits * some fixes * nits * merge * fix permute * nits * fix * nits * nits * nits * fix rope * fix both rope * nites * style * make sure flax works * fix flax init code * fix foward * nits * print flax generation out * current code * nits * SIIIIIIIIIIIIIIIIIII * update * add new tokenizer * correct fast tokenizer * fix conversion * more comments * fix modeling and conversion * nits and nits * nits testing * add some tokenization tests * add some edge cases * add slow tests and fix them * fixup * fix copies for modeling * fix copies * add 7B slow tests * fix * fix * fix tests * make tokenizer cis go green * styling * last tokenizer nits * update jax tests * fix flax for 7b * add jit testing 🤗 * cleanups * isolated nit, inv_freq for rotary_emb.inv_freq * propagate to jax * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * adjust test * fix conversion script * change name * correct file names * update conversion script * Fix bos and eos token ids in the model configuration (#3) * update modelling * update conversion script * add static cache for gemma * fix sdpa generate * fix batched * multiple fixes * fix FA2 * final fix * Rename a few missing strings and filenames (#4) * merge with upstream main * fix copies * fix copies * fix fixup * fix fixup * fix * fix * final tests * fix fx gemma tests * fix fx bf16/fp16 tests * update slow fx tests * fx slow tests: one logits, one generation * move jit test standalone * Apply suggestions from code review * nits * tokenizer updates * more tokenization updates: custom GemmaSentencepieceExtrator * style * Update src/transformers/cache_utils.py * Update src/transformers/models/gemma/__init__.py * Update tests/models/gemma/test_modeling_flax_gemma.py * small nits * style * update tokenization test * fix the rotary embedding * with style * fix slow tests * WARNING this commit might be very important for precisions * Update tests/models/gemma/test_modeling_flax_gemma.py * Update src/transformers/models/gemma/configuration_gemma.py Co-authored-by: Lysandre Debut <hi@lysand.re> * Update src/transformers/models/gemma/modeling_flax_gemma.py Co-authored-by: Lysandre Debut <hi@lysand.re> * small nits here and there! * forgotten nit * remove on the fly computation of inv_freq * revert previous change, let's be safe and for now re-compute freq cis to make sure it's in float * Apply suggestions from code review Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_flax_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * nit conversion script link * fix some tests * add not doctest and pr doctest * repo consistency * fix last CIs 🚀 * update all readmes --------- Co-authored-by: younesbelkada <younesbelkada@gmail.com> Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: sanchit-gandhi <sanchit@huggingface.co> Co-authored-by: Lysandre Debut <hi@lysand.re> |
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amyeroberts
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ba3264b4e8
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Image Feature Extraction pipeline (#28216)
* Draft pipeline * Fixup * Fix docstrings * Update doctest * Update pipeline_model_mapping * Update docstring * Update tests * Update src/transformers/pipelines/image_feature_extraction.py Co-authored-by: Omar Sanseviero <osanseviero@gmail.com> * Fix docstrings - review comments * Remove pipeline mapping for composite vision models * Add to pipeline tests * Remove for flava (multimodal) * safe pil import * Add requirements for pipeline run * Account for super slow efficientnet * Review comments * Fix tests * Swap order of kwargs * Use build_pipeline_init_args * Add back FE pipeline for Vilt * Include image_processor_kwargs in docstring * Mark test as flaky * Update TODO * Update tests/pipelines/test_pipelines_image_feature_extraction.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Add license header --------- Co-authored-by: Omar Sanseviero <osanseviero@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Kian Sierra McGettigan
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f7076cd346
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Flax mistral (#26943)
* direct copy from llama work * mistral modules forward pass working * flax mistral forward pass with sliding window * added tests * added layer collection approach * Revert "added layer collection approach" This reverts commit |
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Yoach Lacombe
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d2cdefb9ec
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Add new meta w2v2-conformer BERT-like model (#28165)
* 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: Sanchit 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: amyeroberts <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: amyeroberts <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: amyeroberts <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: amyeroberts <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: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Matt
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2382706a1c
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Fix docstrings and update docstring checker error message (#28460)
* Fix TF Regnet docstring * Fix TF Regnet docstring * Make a change to the PyTorch Regnet too to make sure the CI is checking it * Add skips for TFRegnet * Update error message for docstring checker |
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Matt
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143451355c
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Fix docstring checker issues with PIL enums (#28450) | ||
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Sparty
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6c78bbcb83
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[docstring] Fix docstring for ErnieConfig, ErnieMConfig (#27029)
* Remove ErnieConfig, ErnieMConfig check_docstrings * Run fix_and_overwrite for ErnieConfig, ErnieMConfig * Replace <fill_type> and <fill_docstring> in configuration_ernie, configuration_ernie_m.py with type and docstring values --------- Co-authored-by: vignesh-raghunathan <vignesh_raghunathan@intuit.com> |
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Alex McKinney
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75336c1794
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Add Llama Flax Implementation (#24587)
* Copies `modeling_flax_gpt_neo.py` to start * MLP Block. WIP Attention and Block * Adds Flax implementation of `LlamaMLP` Validated with in-file test. Some slight numeric differences, but assuming it isn't an issue * Adds `FlaxLlamaRMSNorm` layer `flax.linen` includes `RMSNorm` layer but not necessarily in all versions. Hence, we add in-file. * Adds FlaxLlamaAttention Copied from GPT-J as it has efficient caching implementation as well as rotary embeddings. Notice numerically different, but not by a huge amount. Needs investigating * Adds `FlaxLlamaDecoderLayer` numerically inaccurate, debugging.. * debugging rotary mismatch gptj uses interleaved whilst llama uses contiguous i think they match now but still final result is wrong. maybe drop back to just debugging attention layer? * fixes bug with decoder layer still somewhat numerically inaccurate, but close enough for now * adds markers for what to implement next the structure here diverges a lot from the PT version. not a big fan of it, but just get something working for now * implements `FlaxLlamaBlockCollection`] tolerance must be higher than expected, kinda disconcerting * Adds `FlaxLlamaModule` equivalent PyTorch model is `LlamaModel` yay! a language model🤗 * adds `FlaxLlamaForCausalLMModule` equivalent to `LlamaForCausalLM` still missing returning dict or tuple, will add later * start porting pretrained wrappers realised it probably needs return dict as a prereq * cleanup, quality, style * readds `return_dict` and model output named tuples * (tentatively) pretrained wrappers work 🔥 * fixes numerical mismatch in `FlaxLlamaRMSNorm` seems `jax.lax.rsqrt` does not match `torch.sqrt`. manually computing `1 / jax.numpy.sqrt` results in matching values. * [WIP] debugging numerics * numerical match I think issue was accidental change of backend. forcing CPU fixes test. We expect some mismatch on GPU. * adds in model and integration tests for Flax Llama summary of failing: - mul invalid combination of dimensions - one numerical mismatch - bf16 conversion (maybe my local backend issue) - params are not FrozenDict * adds missing TYPE_CHECKING import and `make fixup` * adds back missing docstrings needs review on quality of docstrings, not sure what is required. Furthermore, need to check if `CHECKPOINT_FOR_DOC` is valid. See TODO * commenting out equivalence test as can just use common * debugging * Fixes bug where mask and pos_ids were swapped in pretrained models This results in all tests passing now 🔥 * cleanup of modeling file * cleanup of test file * Resolving simpler review comments * addresses more minor review comments * fixing introduced pytest errors from review * wip additional slow tests * wip tests need to grab a GPU machine to get real logits for comparison otherwise, slow tests should be okay * `make quality`, `make style` * adds slow integration tests - checking logits - checking hidden states - checking generation outputs * `make fix-copies` * fix mangled function following `make fix-copies` * adds missing type checking imports * fixes missing parameter checkpoint warning * more finegrained 'Copied from' tags avoids issue of overwriting `LLAMA_INPUTS_DOCSTRING` * swaps import guards ??? how did these get swapped initially? * removing `inv_freq` again as pytorch version has now removed * attempting to get CI to pass * adds doc entries for llama flax models * fixes typo in __init__.py imports * adds back special equivalence tests these come from the gpt neo flax tests. there is special behaviour for these models that needs to override the common version * overrides tests with dummy to see if CI passes need to fill in these tests later * adds my contribution to docs * `make style; make quality` * replaces random masking with fixed to work with flax version * `make quality; make style` * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * updates `x`->`tensor` in `rotate_half` * addresses smaller review comments * Update docs/source/en/model_doc/llama.md Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * adds integration test class * adds `dtype` to rotary embedding to cast outputs * adds type to flax llama rotary layer * `make style` * `make fix-copies` * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * applies suggestions from review * Update modeling_flax_llama.py * `make fix-copies` * Update tests/models/llama/test_modeling_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * fixes shape mismatch in FlaxLlamaMLP * applies some suggestions from reviews * casts attn output logits to f32 regardless of dtype * adds attn bias using `LlamaConfig.attention_bias` * adds Copied From comments to Flax Llama test * mistral and persimmon test change -copy from llama * updates docs index * removes Copied from in tests it was preventing `make fix-copies` from succeeding * quality and style * ignores FlaxLlama input docstring * adds revision to `_CHECKPOINT_FOR_DOC` * repo consistency and quality * removes unused import * removes copied from from Phi test now diverges from llama tests following FlaxLlama changes * adds `_REAL_CHECKPOINT_FOR_DOC` * removes refs from pr tests * reformat to make ruff happy --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Yoach Lacombe
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29f1aee3b6
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Add SeamlessM4T v2 (#27779)
* 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: Arthur <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: Arthur <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: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Yih-Dar
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7293fdc5b9
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Deprecate TransfoXL (#27607)
* fix * fix * trigger * Apply suggestions from code review Co-authored-by: Lysandre Debut <hi@lysand.re> * tic * revert * revert --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> Co-authored-by: Lysandre Debut <hi@lysand.re> |
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Andi Powers Holmes
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f8afb2b2ec
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Add TensorFlow implementation of ConvNeXTv2 (#25558)
* Add type annotations to TFConvNextDropPath * Use tf.debugging.assert_equal for TFConvNextEmbeddings shape check * Add TensorFlow implementation of ConvNeXTV2 * check_docstrings: add TFConvNextV2Model to exclusions TFConvNextV2Model and TFConvNextV2ForImageClassification have docstrings which are equivalent to their PyTorch cousins, but a parsing issue prevents them from passing the test. Adding exclusions for these two classes as discussed in #25558. |
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Akshar Goyal
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9234caefb0
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[docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig (#27128)
* [docstring] Fix docstring for AltCLIPVisionConfig, AltCLIPTextConfig + cleaned some docstring * Removed entries from check_docstring.py * Removed entries from check_docstring.py * Removed entry from check_docstring.py * [docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig |
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Younes Belkada
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c34c50cdc0
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[docs] Add MaskGenerationPipeline in docs (#27063)
* add `MaskGenerationPipeline` in docs * Update __init__.py * fix repo consistency and clarify docstring * add on check docstirngs * actually we do have a tf sam * oops |
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Yoach Lacombe
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cb45f71c4d
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Add Seamless M4T model (#25693)
* first raw commit * still POC * tentative convert script * almost working speech encoder conversion scripts * intermediate code for encoder/decoders * add modeling code * first version of speech encoder * make style * add new adapter layer architecture * add adapter block * add first tentative config * add working speech encoder conversion * base model convert works now * make style * remove unnecessary classes * remove unecessary functions * add modeling code speech encoder * rework logics * forward pass of sub components work * add modeling codes * some config modifs and modeling code modifs * save WIP * new edits * same output speech encoder * correct attention mask * correct attention mask * fix generation * new generation logics * erase comments * make style * fix typo * add some descriptions * new state * clean imports * add tests * make style * make beam search and num_return_sequences>1 works * correct edge case issue * correct SeamlessM4TConformerSamePadLayer copied from * replace ACT2FN relu by nn.relu * remove unecessary return variable * move back a class * change name conformer_attention_mask ->conv_attention_mask * better nit code * add some Copied from statements * small nits * small nit in dict.get * rename t2u model -> conditionalgeneration * ongoing refactoring of structure * update models architecture * remove SeamlessM4TMultiModal classes * add tests * adapt tests * some non-working code for vocoder * add seamlessM4T vocoder * remove buggy line * fix some hifigan related bugs * remove hifigan specifc config * change * add WIP tokenization * add seamlessM4T working tokenzier * update tokenization * add tentative feature extractor * Update converting script * update working FE * refactor input_values -> input_features * update FE * changes in generation, tokenizer and modeling * make style and add t2u_decoder_input_ids * add intermediate outputs for ToSpeech models * add vocoder to speech models * update valueerror * update FE with languages * add vocoder convert * update config docstrings and names * update generation code and configuration * remove todos and update config.pad_token_id to generation_config.pad_token_id * move block vocoder * remove unecessary code and uniformize tospeech code * add feature extractor import * make style and fix some copies from * correct consistency + make fix-copies * add processor code * remove comments * add fast tokenizer support * correct pad_token_id in M4TModel * correct config * update tests and codes + make style * make some suggested correstion - correct comments and change naming * rename some attributes * rename some attributes * remove unecessary sequential * remove option to use dur predictor * nit * refactor hifigan * replace normalize_mean and normalize_var with do_normalize + save lang ids to generation config * add tests * change tgt_lang logic * update generation ToSpeech * add support import SeamlessM4TProcessor * fix generate * make tests * update integration tests, add option to only return text and update tokenizer fast * fix wrong function call * update import and convert script * update integration tests + update repo id * correct paths and add first test * update how new attention masks are computed * update tests * take first care of batching in vocoder code * add batching with the vocoder * add waveform lengths to model outputs * make style * add generate kwargs + forward kwargs of M4TModel * add docstrings forward methods * reformate docstrings * add docstrings t2u model * add another round of modeling docstrings + reformate speaker_id -> spkr_id * make style * fix check_repo * make style * add seamlessm4t to toctree * correct check_config_attributes * write config docstrings + some modifs * make style * add docstrings tokenizer * add docstrings to processor, fe and tokenizers * make style * write first version of model docs * fix FE + correct FE test * fix tokenizer + add correct integration tests * fix most tokenization tests * make style * correct most processor test * add generation tests and fix num_return_sequences > 1 * correct integration tests -still one left * make style * correct position embedding * change numbeams to 1 * refactor some modeling code and correct one test * make style * correct typo * refactor intermediate fnn * refactor feedforward conformer * make style * remove comments * make style * fix tokenizer tests * make style * correct processor tests * make style * correct S2TT integration * Apply suggestions from Sanchit code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * correct typo * replace torch.nn->nn + make style * change Output naming (waveforms -> waveform) and ordering * nit renaming and formating * remove return None when not necessary * refactor SeamlessM4TConformerFeedForward * nit typo * remove almost copied from comments * add a copied from comment and remove an unecessary dropout * remove inputs_embeds from speechencoder * remove backward compatibiliy function * reformate class docstrings for a few components * remove unecessary methods * split over 2 lines smthg hard to read * make style * replace two steps offset by one step as suggested * nice typo * move warnings * remove useless lines from processor * make generation non-standard test more robusts * remove torch.inference_mode from tests * split integration tests * enrich md * rename control_symbol_vocoder_offset->vocoder_offset * clean convert file * remove tgt_lang and src_lang from FE * change generate docstring of ToText models * update generate docstring of tospeech models * unify how to deal withtext_decoder_input_ids * add default spkr_id * unify tgt_lang for t2u_model * simplify tgt_lang verification * remove a todo * change config docstring * make style * simplify t2u_tgt_lang_id * make style * enrich/correct comments * enrich .md * correct typo in docstrings * add torchaudio dependency * update tokenizer * make style and fix copies * modify SeamlessM4TConverter with new tokenizer behaviour * make style * correct small typo docs * fix import * update docs and add requirement to tests * add convert_fairseq2_to_hf in utils/not_doctested.txt * update FE * fix imports and make style * remove torchaudio in FE test * add seamless_m4t.md to utils/not_doctested.txt * nits and change the way docstring dataset is loaded * move checkpoints from ylacombe/ to facebook/ orga * refactor warning/error to be in the 119 line width limit * round overly precised floats * add stereo audio behaviour * refactor .md and make style * enrich docs with more precised architecture description * readd undocumented models * make fix-copies * apply some suggestions * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * correct bug from previous commit * refactor a parameter allowing to clean the code + some small nits * clean tokenizer * make style and fix * make style * clean tokenizers arguments * add precisions for some tests * move docs from not_tested to slow * modify tokenizer according to last comments * add copied from statements in tests * correct convert script * correct parameter docstring style * correct tokenization * correct multi gpus * make style * clean modeling code * make style * add copied from statements * add copied statements * add support with ASR pipeline * remove file added inadvertently * fix docstrings seamlessM4TModel * add seamlessM4TConfig to OBJECTS_TO_IGNORE due of unconventional markdown * add seamlessm4t to assisted generation ignored models --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Adam Ross
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929134bf65
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[docstring] Fix docstring for speech-to-text config (#26883)
* Fix docstring for speech-to-text config * Refactor doc line len <= 119 char * Remove Speech2TextConfig from OBJECTS_TO_IGNORE * Fix Speech2TextConfig doc str * Fix Speech2TextConfig doc using doc-builder * Refactor Speech2TextConfig doc |
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Daniil
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ad08137e47
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[docstring] Fix docstrings for CodeGen (#26821)
* remove docstrings CodeGen from objects_to_ignore * autofix codegen docstrings * fill in the missing types and docstrings * fixup * change descriptions to be in a separate line * apply docstring suggestions from code review Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com> * update n_ctx description in CodeGenConfig --------- Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com> |
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Sparty
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816c2237c1
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[docstring] Fix docstring for ChineseCLIP (#26880)
* Remove ChineseCLIPImageProcessor, ChineseCLIPTextConfig, ChineseCLIPVisionConfig from check_docstrings * Run fix_and_overwrite for ChineseCLIPImageProcessor, ChineseCLIPTextConfig, ChineseCLIPVisionConfig * Replace <fill_type> and <fill_docstring> in configuration_chinese_clip.py, image_processing_chinese_clip.py with type and docstring values --------- Co-authored-by: vignesh-raghunathan <vignesh_raghunathan@intuit.com> |
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louietouie
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51042ae8e5
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[docstring] Fix docstring for LukeConfig (#26858)
* Deleted LukeConfig and ran check_docstrings.py * Filled docstring information --------- Co-authored-by: louie <louisparizeau@Chicken.local> |
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przemL
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5c6b83cb69
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[docstring] Fix bert generation tokenizer (#26820)
* Remove BertGenerationTokenizer from objects to ignore The file BertGenerationTokenizer is removed from objects to ignore as a first step to fix docstring. * Docstrings fix for BertGenerationTokenizer Docstring fix is generated for BertGenerationTokenizer by using check_docstrings.py. * Fix docstring for BertGenerationTokenizer Added sep_token type and docstring in BertGenerationTokenizer. |
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Bojun-Feng
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5c081e2993
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[docstring] Fix docstring for CodeLlamaTokenizerFast (#26666)
* remove from OBJECTS_TO_IGNORE * run check_docstrings.py * fill in information * ignore CodeLlamaTokenizer |
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Sparty
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0e52af4d7b
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[docstring] Fix docstring for CanineConfig (#26771)
* Remove CanineConfig from check_docstrings * Run fix_and_overwrite for CanineConfig * Replace <fill_type> and <fill_docstring> in configuration_canine.py with type and docstring values --------- Co-authored-by: vignesh-raghunathan <vignesh_raghunathan@intuit.com> |
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NielsRogge
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762af3e3c7
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Add OWLv2, bis (#26668)
* First draft * Update conversion script * Update copied from statements * Fix style * Add copied from to config * Add copied from to processor * Run make fixup * Add docstring * Update docstrings * Add method * Improve docstrings * Fix docstrings * Improve docstrings * Remove onnx * Add flag * Address comments * Add copied from to model tests * Add flag to conversion script * Add code snippet * Address more comments * Address comment * Improve conversion script * More improvements * Add expected objectness logits * Skip test * Improve conversion script * Extend conversion script * Convert large checkpoint * Fix doc tests * Convert all checkpoints, update integration tests * Add checkpoint_path arg * Fix repo_id |
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dekomori_sanae09
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5bfda28dd3
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[docstring] fix docstring DPRConfig (#26674)
* fix docstring dpr config * fix style * Update descp Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com> --------- Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com> |