


"""simple docstring"""







from typing import Union

import fire
import torch
from tqdm import tqdm
def 					a__			(				SCREAMING_SNAKE_CASE    :    str				,      SCREAMING_SNAKE_CASE    :    str = "cpu"				,      SCREAMING_SNAKE_CASE    :    Union[str, None] = None				):


  '''simple docstring'''







  lowerCAmelCase     :     List[str]								=							torch.load(SCREAMING_SNAKE_CASE				,      map_location=SCREAMING_SNAKE_CASE				)
  for k, v in tqdm(state_dict.items()				):
    if not isinstance(SCREAMING_SNAKE_CASE				,      torch.Tensor				):
      raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"				)
    lowerCAmelCase     :     Optional[Any]								=							v.half()
  if save_path is None:  # overwrite src_path
    lowerCAmelCase     :     Union[str, Any]								=							src_path
  torch.save(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)


if __name__ == "__main__":
     fire.Fire(convert)







import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
			import jax.numpy as jnp

			from transformers import FlaxXLMRobertaModel




@require_sentencepiece
@require_tokenizers
@require_flax
class    SCREAMING_SNAKE_CASE__     (	unittest.TestCase					):





	'''simple docstring'''



	@slow
	def  A							(  self	:    int	):


				'''simple docstring'''


				_snake_case		=			FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base'	)
				_snake_case		=			AutoTokenizer.from_pretrained('xlm-roberta-base'	)
				_snake_case		=			'The dog is cute and lives in the garden house'
				_snake_case		=			jnp.array([tokenizer.encode(lowercase	)]	)

				_snake_case		=			(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
				_snake_case		=			jnp.array(
				    [[-0.0101, 0.1218, -0.0803, 0.0801, 0.1327, 0.0776, -0.1215, 0.2383, 0.3338, 0.3106, 0.0300, 0.0252]]	)

				_snake_case		=			model(lowercase	)['last_hidden_state']
				self.assertEqual(output.shape			,  lowercase	)
				# compare the actual values for a slice of last dim
				self.assertTrue(jnp.allclose(output[:, :, -1]			,  lowercase			,  atol=1E-3	)	)