update convert_safetensors.py
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20
backend-python/convert_safetensors.py
vendored
20
backend-python/convert_safetensors.py
vendored
@ -25,7 +25,7 @@ def rename_key(rename, name):
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return name
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def convert_file(pt_filename: str, sf_filename: str, transpose_names=[], rename={}):
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def convert_file(pt_filename: str, sf_filename: str, rename={}, transpose_names=[]):
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loaded = torch.load(pt_filename, map_location="cpu")
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if "state_dict" in loaded:
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loaded = loaded["state_dict"]
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@ -34,12 +34,14 @@ def convert_file(pt_filename: str, sf_filename: str, transpose_names=[], rename=
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# for k, v in loaded.items():
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# print(f'{k}\t{v.shape}\t{v.dtype}')
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loaded = {rename_key(rename, k).lower(): v.contiguous() for k, v in loaded.items()}
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# For tensors to be contiguous
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for k, v in loaded.items():
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for transpose_name in transpose_names:
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if transpose_name in k:
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loaded[k] = v.transpose(0, 1)
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loaded = {rename_key(rename, k).lower(): v.contiguous() for k, v in loaded.items()}
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loaded = {k: v.clone().half().contiguous() for k, v in loaded.items()}
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for k, v in loaded.items():
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print(f"{k}\t{v.shape}\t{v.dtype}")
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@ -60,8 +62,18 @@ if __name__ == "__main__":
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convert_file(
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args.input,
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args.output,
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["lora_A"],
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{"time_faaaa": "time_first", "lora_A": "lora.0", "lora_B": "lora.1"},
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rename={
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"time_faaaa": "time_first",
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"time_maa": "time_mix",
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"lora_A": "lora.0",
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"lora_B": "lora.1",
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},
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transpose_names=[
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"time_mix_w1",
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"time_mix_w2",
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"time_decay_w1",
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"time_decay_w2",
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],
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)
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print(f"Saved to {args.output}")
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except Exception as e:
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