[Backend support] Allow num_logits_to_keep as Tensor and change it to logits_to_keep + add flag
#35757
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ArthurZucker
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Jan 20, 2025
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ArthurZucker
approved these changes
Jan 23, 2025
num_logits_to_keep as Tensor + add flagnum_logits_to_keep as Tensor and change it to logits_to_keep + add flag
bursteratom
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to bursteratom/transformers
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Jan 31, 2025
…ggingface#35757) * support * Update modeling_utils.py * style * most models * Other models * fix-copies * tests + generation utils
dsikka
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Feb 11, 2025
## Purpose ##
* SparseGPT
* Fix behavior where `targets` specifies which modules to sparsity, not
which layers to target
* Fix broken behavior with `_infer_owl_layer_sparsity` and add test
* Fix owl argument validation
* Add type hints and abstract methods for clarity
* Pipelines
* Fix bug revealed by decorators added to the llama model definition in
the latest transformers release
* huggingface/transformers#35757
* For the sequential pipeline, this revealed a bug in
torch.fx._symbolic_trace where wrapped functions were not being handled
properly
* Future work could involve upstreaming a bug fix
* Fix issue caused by changes to llama model definition
* huggingface/transformers#34858
* For the layer sequential pipeline, this challenges the assumption that
each layer input is the previous layer's output (which was known to be a
fragile assumption)
* Fix issue related to basic pipeline slowdowns and inaccuracy
## Changes ##
* SparseGPT
* Fully separate `targets` and `sequential_targets`
* Modify hooks adding logic to reflect this change
* Fix behavior of `_infer_owl_layer_sparsity` and add test
* Code clarity
* Add additional type hints
* Designate `calibrate_module` as an abstract method on the sgpt mixin
* Pipelines
* Sequential pipeline: unwrap model forward function to avoid issues
with pytorch function patching
* Layer Sequential Pipeline: Add `maybe_inject_pos_embeddings` to
sequential pipeline to hackily support models with `position_embeddings`
* Basic Pipeline: Fix `on_sequential_batch_end` to call on the end of
epoch, rather than every batch
* Calling every batch was likely causing slowdowns
## Followups ##
* Remove deprecated `sequential_update` option from examples and tests
## Testing ##
* Added `tests/llmcompressor/transformers/obcq/test_obcq_owl.py`
* Tested OBCQ+llama with sequential, layer sequential, and basic
pipelines independently
## Regression Evaluations ##
Models were compressed using
`examples/sparse_2of4_quantization_fp8/llama3_8b_2of4.py` without fp8
option
<details><summary>sparsegpt</summary>
Main
```
vllm (pretrained=/home/kyle/llm-compressor/Meta-Llama-3-8B-InstructSparseGPTModifierMAIN,dtype=bfloat16,add_bos_token=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 1
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|----------|------:|------|-----:|------|---|-----:|---|-----:|
|winogrande| 1|none | 5|acc |↑ |0.6243|± |0.0136|
```
This branch
```
vllm (pretrained=/home/kyle/llm-compressor/Meta-Llama-3-8B-InstructSparseGPTModifierFEATURE,dtype=bfloat16,add_bos_token=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 1
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|----------|------:|------|-----:|------|---|-----:|---|-----:|
|winogrande| 1|none | 5|acc |↑ |0.6306|± |0.0136|
```
</details>
To test wanda, the `SparseGPTModifier` was replaced with the
`WandaPruningModifier`
<details><summary>wanda</summary>
Main
```
vllm (pretrained=/home/kyle/llm-compressor/Meta-Llama-3-8B-InstructWandaPruningModifierMAIN,dtype=bfloat16,add_bos_token=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 1
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|----------|------:|------|-----:|------|---|-----:|---|-----:|
|winogrande| 1|none | 5|acc |↑ |0.5912|± |0.0138|
```
This branch
```
vllm (pretrained=/home/kyle/llm-compressor/Meta-Llama-3-8B-InstructWandaPruningModifierFEATURE,dtype=bfloat16,add_bos_token=True), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 1
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|----------|------:|------|-----:|------|---|-----:|---|-----:|
|winogrande| 1|none | 5|acc |↑ |0.5817|± |0.0139|
```
</details>
---------
Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>
Co-authored-by: Dipika Sikka <dipikasikka1@gmail.com>
elvircrn
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to elvircrn/transformers
that referenced
this pull request
Feb 13, 2025
…ggingface#35757) * support * Update modeling_utils.py * style * most models * Other models * fix-copies * tests + generation utils
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What does this PR do?
As per the title. Allowing
num_logits_to_keepas a Tensor allow efficient slicing when using packed tensor format. It will be useful for us in the future as well as we integrate packed format for FA2 path.