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Improved version of conversion script Flax → PyTorch
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#!/usr/bin/env python
import tempfile
import jax
from jax import numpy as jnp
from transformers import AutoTokenizer, FlaxRobertaForMaskedLM, RobertaForMaskedLM
def to_f32(t):
return jax.tree_map(lambda x: x.astype(jnp.float32) if x.dtype == jnp.bfloat16 else x, t)
def main():
# Saving extra files from config.json and tokenizer.json files
tokenizer = AutoTokenizer.from_pretrained("./")
# Temporary saving bfloat16 Flax model into float32
tmp = tempfile.mkdtemp()
flax_model = FlaxRobertaForMaskedLM.from_pretrained("./")
flax_model.params = to_f32(flax_model.params)
# Converting float32 Flax to PyTorch
model = RobertaForMaskedLM.from_pretrained(tmp, from_flax=True)
model.save_pretrained("./", save_config=False)
if __name__ == "__main__":