REMEND / remend /edit_model.py

Add REMEND python module

7145fd6 over 1 year ago

2.09 kB

removed = ["encoder.layers.0.in_proj_weight", "encoder.layers.0.in_proj_bias", "encoder.layers.0.out_proj_weight", "encoder.layers.0.out_proj_bias", "encoder.layers.0.fc1_weight", "encoder.layers.0.fc1_bias", "encoder.layers.0.fc2_weight", "encoder.layers.0.fc2_bias", "encoder.layers.1.in_proj_weight", "encoder.layers.1.in_proj_bias", "encoder.layers.1.out_proj_weight", "encoder.layers.1.out_proj_bias", "encoder.layers.1.fc1_weight", "encoder.layers.1.fc1_bias", "encoder.layers.1.fc2_weight", "encoder.layers.1.fc2_bias", "encoder.layers.2.in_proj_weight", "encoder.layers.2.in_proj_bias", "encoder.layers.2.out_proj_weight", "encoder.layers.2.out_proj_bias", "encoder.layers.2.fc1_weight", "encoder.layers.2.fc1_bias", "encoder.layers.2.fc2_weight", "encoder.layers.2.fc2_bias", "encoder.layers.3.in_proj_weight", "encoder.layers.3.in_proj_bias", "encoder.layers.3.out_proj_weight", "encoder.layers.3.out_proj_bias", "encoder.layers.3.fc1_weight", "encoder.layers.3.fc1_bias", "encoder.layers.3.fc2_weight", "encoder.layers.3.fc2_bias", "encoder.layers.4.in_proj_weight", "encoder.layers.4.in_proj_bias", "encoder.layers.4.out_proj_weight", "encoder.layers.4.out_proj_bias", "encoder.layers.4.fc1_weight", "encoder.layers.4.fc1_bias", "encoder.layers.4.fc2_weight", "encoder.layers.4.fc2_bias", "encoder.layers.5.in_proj_weight", "encoder.layers.5.in_proj_bias", "encoder.layers.5.out_proj_weight", "encoder.layers.5.out_proj_bias", "encoder.layers.5.fc1_weight", "encoder.layers.5.fc1_bias", "encoder.layers.5.fc2_weight", "encoder.layers.5.fc2_bias"]

if __name__ == "__main__":
    import argparse
    import torch

    parser = argparse.ArgumentParser("Edit the checkpoint to remove extra dict weights")
    parser.add_argument("-c", "--checkpoint", required=True, help="Input checkpoint")
    parser.add_argument("-e", "--edited", required=True, help="Edited checkpoint")
    args = parser.parse_args()
    
    sd = torch.load(args.checkpoint, weights_only=False)
    for k in removed:
        if k in sd['model']:
            del sd['model'][k]
    torch.save(sd, args.edited)

	removed = ["encoder.layers.0.in_proj_weight", "encoder.layers.0.in_proj_bias", "encoder.layers.0.out_proj_weight", "encoder.layers.0.out_proj_bias", "encoder.layers.0.fc1_weight", "encoder.layers.0.fc1_bias", "encoder.layers.0.fc2_weight", "encoder.layers.0.fc2_bias", "encoder.layers.1.in_proj_weight", "encoder.layers.1.in_proj_bias", "encoder.layers.1.out_proj_weight", "encoder.layers.1.out_proj_bias", "encoder.layers.1.fc1_weight", "encoder.layers.1.fc1_bias", "encoder.layers.1.fc2_weight", "encoder.layers.1.fc2_bias", "encoder.layers.2.in_proj_weight", "encoder.layers.2.in_proj_bias", "encoder.layers.2.out_proj_weight", "encoder.layers.2.out_proj_bias", "encoder.layers.2.fc1_weight", "encoder.layers.2.fc1_bias", "encoder.layers.2.fc2_weight", "encoder.layers.2.fc2_bias", "encoder.layers.3.in_proj_weight", "encoder.layers.3.in_proj_bias", "encoder.layers.3.out_proj_weight", "encoder.layers.3.out_proj_bias", "encoder.layers.3.fc1_weight", "encoder.layers.3.fc1_bias", "encoder.layers.3.fc2_weight", "encoder.layers.3.fc2_bias", "encoder.layers.4.in_proj_weight", "encoder.layers.4.in_proj_bias", "encoder.layers.4.out_proj_weight", "encoder.layers.4.out_proj_bias", "encoder.layers.4.fc1_weight", "encoder.layers.4.fc1_bias", "encoder.layers.4.fc2_weight", "encoder.layers.4.fc2_bias", "encoder.layers.5.in_proj_weight", "encoder.layers.5.in_proj_bias", "encoder.layers.5.out_proj_weight", "encoder.layers.5.out_proj_bias", "encoder.layers.5.fc1_weight", "encoder.layers.5.fc1_bias", "encoder.layers.5.fc2_weight", "encoder.layers.5.fc2_bias"]

	if __name__ == "__main__":
	import argparse
	import torch

	parser = argparse.ArgumentParser("Edit the checkpoint to remove extra dict weights")
	parser.add_argument("-c", "--checkpoint", required=True, help="Input checkpoint")
	parser.add_argument("-e", "--edited", required=True, help="Edited checkpoint")
	args = parser.parse_args()

	sd = torch.load(args.checkpoint, weights_only=False)
	for k in removed:
	if k in sd['model']:
	del sd['model'][k]
	torch.save(sd, args.edited)