* _get_padding_size module
* do not patchify images when processing multi image
* modify llava onevision image processor fast
* tensor to list of tensors
* backward compat
* reuse pad_to_square in llave & some clarification
* add to doc
* fix: consider no image cases (text only or video)
* add integration test
* style & repo_consistency
* accept custom device_mesh
* fix device_map
* assert that num_heads % tp_size == 0
* todo.
* ReplicateParallel
* handle tied weights
* handle dtensor in save_pretrained with safe_serialization
* tp test works
* doesnt work
* fix shard_and_distribute_module's rank should be local_rank
* tp=4 is correct
* dp+tp is broken
* todo allreduce with dtensors on another dim is annoying
* workaround to sync dp grads when using dtensors
* loading a checkpoint works
* wandb and compare losses with different tp/dp
* cleaning
* cleaning
* .
* .
* logs
* CP2 DP2 no mask works after commenting attn_mask and is_causal from scaled_dot_product_attention
* DP=2 TP=2 now works even with tied embeddings
* model.parameters() and model.module.parameters() are empty..
* reformat sanity_check_tensor_sync
* set atol=1e-4 for CP to pass
* try populate _parameters from named_modules
* refactors
TP2 DP2 works
CP2 DP2 works
* is_causal=True and pack sequences, no attn mask, and preshuffle dataset
* fix packing
* CP=4 doesn't work
* fix labels and position_ids for CP
* DP CP works with transformers 🥳🥳🥳
* refactor
* add example cp
* fixup
* revert sdpa changes
* example cleared
* add CP, DP to the mesh init
* nit
* clean
* use `ALL_PARALLEL_STYLES`
* style
* FSDP works
* log on 1 rank
* .
* fix?
* FSDP1 also has .parameters() bug
* reported gradnorm when using FSDP1 is wrong, but loss is correct so it's okay
* .
* style and fixup
* move stuff around
* fix tests
* style
* let's make it a check
* add missing licences
* warning should be an info
* tp plan should not be NONE
* test all
* god damn it
* test all
---------
Co-authored-by: nouamanetazi <nouamane98@gmail.com>
* add seq_idx and fa kwargs
* update tests
* docs and grad ckpt support
* fmt
* better names
* test_raise_missing_padding_free_kwarg_errs
* + seq_idx in doc strings
* padding free training docs
* add link to pr plots
* raise err on attn_mask with padding free
* rm raising missing padding free err test
* BambaFlashAttentionKwargs
* run modular util for modular_granitemoehybrid.py
* accept custom device_mesh
* fix device_map
* assert that num_heads % tp_size == 0
* todo.
* ReplicateParallel
* handle tied weights
* handle dtensor in save_pretrained with safe_serialization
* tp test works
* doesnt work
* fix shard_and_distribute_module's rank should be local_rank
* tp=4 is correct
* dp+tp is broken
* todo allreduce with dtensors on another dim is annoying
* workaround to sync dp grads when using dtensors
* loading a checkpoint works
* wandb and compare losses with different tp/dp
* cleaning
* cleaning
* .
* .
* logs
* CP2 DP2 no mask works after commenting attn_mask and is_causal from scaled_dot_product_attention
* DP=2 TP=2 now works even with tied embeddings
* model.parameters() and model.module.parameters() are empty..
* reformat sanity_check_tensor_sync
* set atol=1e-4 for CP to pass
* try populate _parameters from named_modules
* refactors
TP2 DP2 works
CP2 DP2 works
* is_causal=True and pack sequences, no attn mask, and preshuffle dataset
* fix packing
* CP=4 doesn't work
* fix labels and position_ids for CP
* DP CP works with transformers 🥳🥳🥳
* refactor
* add example cp
* fixup
* revert sdpa changes
* example cleared
* add CP, DP to the mesh init
* nit
* clean
* use `ALL_PARALLEL_STYLES`
* style
* FSDP works
* log on 1 rank
* .
* fix?
* FSDP1 also has .parameters() bug
* reported gradnorm when using FSDP1 is wrong, but loss is correct so it's okay
* .
* style and fixup
* move stuff around
* fix tests
* style
* let's make it a check
* warning should be an info
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
When preparing the causal attention mask at this point the mask comes
in as a float tensor with min value as a masked value.
It is not correct to convert it to bool and treat it as a bool mask as
this inverts the mask.
`torch.nn.functional.scaled_dot_product_attention` expects that a masked value is `False`.
I suspect that the `sdpa` implementation variant may not have been
thoroughly tested and that is why this error was not caught earlier.
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Add Llama4TextModel to AutoModel mapping
using Llama4TextConfig on AutoModel.from_config raises a ValueError when it is expected to instantiate a Llama4TextModel
bnb quant tests: remove obsolete trust_remote_code test
The MPT model is now natively integrated in Transformers and no longer requires trust_remote_code=True. This removes the failing test_get_keys_to_not_convert_trust_remote_code and related usage, which depended on remote code and caused CI issues due to missing dependencies (e.g., triton_pre_mlir).
* fix sliding attn
* make style
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* no a second throught, should default to `True` fo BC
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* use device agnostic APIs in tests
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* more
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* add reset_peak_memory_stats API
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update
---------
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Update modular_qwen2_5_omni.py
fix the error when loading quantized model by AuotAWQ.
* Update modeling_qwen2_5_omni.py
sync code to modular_qwen2_5_omni.py
* pipeline generation defaults
* add max_new_tokens=20 in test pipelines
* pop all kwargs that are used to parameterize generation config
* add class attr that tell us whether a pipeline calls generate
* tmp commit
* pt text gen pipeline tests passing
* remove failing tf tests
* fix text gen pipeline mixin test corner case
* update text_to_audio pipeline tests
* trigger tests
* a few more tests
* skips
* some more audio tests
* not slow
* broken
* lower severity of generation mode errors
* fix all asr pipeline tests
* nit
* skip
* image to text pipeline tests
* text2test pipeline
* last pipelines
* fix flaky
* PR comments
* handle generate attrs more carefully in models that cant generate
* same as above
* tmp commit (imports broken)
* working version; update tests
* remove line break
* shorter msg
* dola checks need num_beams=1; other minor PR comments
* update early trainer failing on bad gen config
* make fixup
* test msg
