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generate inv hessian
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| import torch | |
| from argparse import ArgumentParser | |
| from vptq.utils.hessian import load_hessian | |
| import os | |
| if __name__ == "__main__": | |
| parser = ArgumentParser() | |
| parser.add_argument('--load_hessian_dir', type=str, default=None, | |
| help='Directory containing Hessian .pt files') | |
| parser.add_argument('--store_inv_hessian_dir', type=str, default=None, | |
| help='Directory to save inverted Hessian .pt files') | |
| args = parser.parse_args() | |
| # create folder | |
| os.makedirs(args.store_inv_hessian_dir, exist_ok=True) | |
| percdamp = 0.01 | |
| hessian_files = [f for f in os.listdir( | |
| args.load_hessian_dir) if f.endswith('.pt')] | |
| for hessian_file in hessian_files: | |
| hessian_path = os.path.join(args.load_hessian_dir, hessian_file) | |
| hessian, mu = load_hessian(hessian_path) | |
| dev = 'cuda' | |
| hessian = hessian.to(dev) | |
| zero_idx = torch.diag(hessian) == 0 | |
| hessian[zero_idx, zero_idx] = 1 | |
| # get permutation | |
| perm = torch.argsort(torch.diag(hessian), descending=True).to(dev) | |
| hessian = hessian[perm][:, perm] | |
| # add damping | |
| damp = percdamp * torch.mean(torch.diag(hessian)) | |
| diag = torch.arange(hessian.shape[0], device=dev) | |
| hessian[diag, diag] += damp | |
| # inverse Hessian | |
| hessian = torch.linalg.cholesky(hessian) | |
| hessian = torch.cholesky_inverse(hessian) | |
| hessian = torch.linalg.cholesky(hessian, upper=True) | |
| inv_hessian = hessian | |
| # Saving the inverted Hessian to the specified directory with the same file name | |
| save_path = os.path.join(args.store_inv_hessian_dir, hessian_file) | |
| torch.save({'invH': inv_hessian.to('cpu'), | |
| 'perm': perm.to('cpu'), | |
| 'zero_idx': zero_idx.to('cpu')}, save_path) | |
| print(f'Saved inverted Hessian to {save_path}') |
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