added merging methods and scoring functions #165
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added merging methods and scoring functions
Author
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@microsoft-github-policy-service agree company="Microsoft" |
fverac
reviewed
Apr 14, 2025
| return grads * keep_mask | ||
| return hook | ||
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| def load_mask(f_name): |
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Is there a way we can avoid needing these functions save_mask and load_mask?
weight_mask should be included in state_dict by now so can be reloaded from checkpoints?
fverac
reviewed
Apr 14, 2025
mttl/models/modifiers/sparse_mask.py
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| keep_masks = torch.zeros_like(m.sparse_layer.weight) | ||
| m.revert_weight_grad_and_update_mask(keep_masks) | ||
| # based on gradient-magnitude | ||
| elif parameter_selection_procedure=='gradient_magnitude': |
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can you add tests for the new permutations of these parameters in test_sparse_mask.py?
fverac
reviewed
Apr 14, 2025
| self.sparse_layer.forward = types.MethodType(mod_forward, self.sparse_layer) | ||
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| @torch.no_grad() | ||
| def convert_sparse_weight_to_1D(self): |
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Is this ever used? ctrl+f doesn't find anything for me.
fverac
reviewed
Apr 14, 2025
| if m.sparse_cat == 'block_sparse': | ||
| keep_masks = get_block_mask(m) | ||
| elif m.sparse_cat == "regular_sparse": | ||
| # check: sample noise-block-idx |
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remove comments when ready. optionally add logging
moved merging model to separate folder, updated essential function and arguments for sparse-adapter training
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will make a new pr |
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Added merging methods:
Added different scoring functions