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import torch |
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import numpy as np |
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import jax |
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import jax.numpy as jnp |
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from transformers import AutoTokenizer |
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from transformers import FlaxGPT2LMHeadModel |
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from transformers import GPT2LMHeadModel |
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model_fx = FlaxGPT2LMHeadModel.from_pretrained("./") |
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model_pt = GPT2LMHeadModel.from_pretrained("./", from_flax=True) |
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model_pt.save_pretrained("./") |
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input_ids = np.asarray(2 * [128 * [0]], dtype=np.int32) |
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input_ids_pt = torch.tensor(input_ids) |
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logits_pt = model_pt(input_ids_pt).logits |
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print(logits_pt) |
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logits_fx = model_fx(input_ids).logits |
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print(logits_fx) |