[from_pretrained] Make from_pretrained fast again
#27709
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LysandreJik
approved these changes
Dec 11, 2023
Co-authored-by: Lysandre Debut <hi@lysand.re>
Co-authored-by: Lysandre Debut <hi@lysand.re>
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iantbutler01
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Dec 16, 2023
* Skip nn.Module.reset_parameters * Actually skip * Check quality * Maybe change all inits * Fix init issues: only modify public functions * Add a small test for now * Style * test updates * style * nice tes * style * make it even faster * one more second * remove fx icompatible * Update tests/test_modeling_common.py Co-authored-by: Lysandre Debut <hi@lysand.re> * Update tests/test_modeling_common.py Co-authored-by: Lysandre Debut <hi@lysand.re> * skip * fix quality * protect the import --------- Co-authored-by: Lysandre Debut <hi@lysand.re>
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staghado
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Jan 15, 2024
* Skip nn.Module.reset_parameters * Actually skip * Check quality * Maybe change all inits * Fix init issues: only modify public functions * Add a small test for now * Style * test updates * style * nice tes * style * make it even faster * one more second * remove fx icompatible * Update tests/test_modeling_common.py Co-authored-by: Lysandre Debut <hi@lysand.re> * Update tests/test_modeling_common.py Co-authored-by: Lysandre Debut <hi@lysand.re> * skip * fix quality * protect the import --------- Co-authored-by: Lysandre Debut <hi@lysand.re>
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what does this PR do
Skips all layer initialization when loading from pretrained without accelerate.
From ~20seconds to 5 seconds for a 7B model like llama.
The Weights are effectively initialized in « init_weights_ » of the pretrained method. All internal calls are skipped
AutoModelForCausalLMfromAutoModelfixes #26258 and fixes #18505
model = XXXX.from_pretrained(model_id, torch_dtype=torch.float16, low_cpu_mem_usage=True")might fail