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T5: Change default dtype to bfloat16 (#147)
* T5: Change default to bfloat16 * Add myself to contributors * t5: Change convert.py default to float32
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@ -6,3 +6,5 @@ with a short description of your contribution(s) below. For example:
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- Jane Smith: Added the `foo` example.
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MLX Examples was developed with contributions from the following individuals:
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- Juarez Bochi: Added support for T5 models.
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@ -44,13 +44,15 @@ def replace_key(key: str) -> str:
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return key
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def convert(model_name):
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def convert(model_name, dtype):
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dtype = getattr(np, dtype)
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model = T5ForConditionalGeneration.from_pretrained(model_name, torch_dtype="auto")
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weights = {
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replace_key(k): v.numpy().astype(np.float16)
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replace_key(k): v.numpy().astype(dtype)
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for k, v in model.state_dict().items()
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}
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file_name = model_name.replace("/", "-")
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print(f"Saving weights to {file_name}.npz")
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np.savez(f"{file_name}.npz", **weights)
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@ -64,5 +66,12 @@ if __name__ == "__main__":
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help="Name of the T5 model.",
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default="t5-small",
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)
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parser.add_argument(
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"--dtype",
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help="The model data type.",
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type=str,
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choices=["float16", "float32"],
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default="float32",
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)
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args = parser.parse_args()
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convert(args.model)
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convert(args.model, args.dtype)
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4
t5/t5.py
4
t5/t5.py
@ -337,7 +337,7 @@ class Tokenizer:
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self._tokenizer = T5Tokenizer.from_pretrained(
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args.model,
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legacy=False,
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model_max_length=config.n_positions,
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model_max_length=getattr(config, 'n_positions', 512)
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)
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@property
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@ -430,7 +430,7 @@ if __name__ == "__main__":
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help="The model data type.",
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type=str,
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choices=["float16", "bfloat16", "float32"],
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default="float32",
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default="bfloat16",
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)
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parser.add_argument("--seed", type=int, default=0, help="The PRNG seed")
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