






"""simple docstring"""





import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase							=  get_tests_dir('fixtures/spiece.model')



@require_sentencepiece
@require_tokenizers
class       __A		(   SCREAMING_SNAKE_CASE_     ,unittest.TestCase			):
					UpperCAmelCase__								=				AlbertTokenizer
					UpperCAmelCase__								=				AlbertTokenizerFast
					UpperCAmelCase__								=				True
					UpperCAmelCase__								=				True
					UpperCAmelCase__								=				True

					def   lowerCamelCase__   (			self  :      Optional[Any]					)			->							Optional[int]:
											super().setUp()

											# We have a SentencePiece fixture for testing
											__magic_name__:	Optional[Any]							=       AlbertTokenizer(__snake_case					)
											tokenizer.save_pretrained(self.tmpdirname					)

					def   lowerCamelCase__   (			self  :      Union[str, Any]     ,		__snake_case  :      Optional[int]					)			->							Any:
											__magic_name__:	str							=       """this is a test"""
											__magic_name__:	Any							=       """this is a test"""
											return input_text, output_text

					def   lowerCamelCase__   (			self  :      List[str]					)			->							List[str]:
											__magic_name__:	Any							=       """<pad>"""
											__magic_name__:	Dict							=       0

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case					)     ,		__snake_case					)
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case					)     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							int:
											__magic_name__:	str							=       list(self.get_tokenizer().get_vocab().keys()					)

											self.assertEqual(vocab_keys[0]     ,		"""<pad>"""					)
											self.assertEqual(vocab_keys[1]     ,		"""<unk>"""					)
											self.assertEqual(vocab_keys[-1]     ,		"""▁eloquent"""					)
											self.assertEqual(len(__snake_case					)     ,		3_0_0_0_0					)

					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							Optional[Any]:
											self.assertEqual(self.get_tokenizer().vocab_size     ,		3_0_0_0_0					)

					def   lowerCamelCase__   (			self  :      List[Any]					)			->							Optional[Any]:
											if not self.test_rust_tokenizer:
																	return

											__magic_name__:	Optional[int]							=       self.get_tokenizer()
											__magic_name__:	str							=       self.get_rust_tokenizer()

											__magic_name__:	Union[str, Any]							=       """I was born in 92000, and this is falsé."""

											__magic_name__:	Dict							=       tokenizer.tokenize(__snake_case					)
											__magic_name__:	str							=       rust_tokenizer.tokenize(__snake_case					)
											self.assertListEqual(__snake_case     ,		__snake_case					)

											__magic_name__:	Any							=       tokenizer.encode(__snake_case     ,		add_special_tokens=__snake_case					)
											__magic_name__:	int							=       rust_tokenizer.encode(__snake_case     ,		add_special_tokens=__snake_case					)
											self.assertListEqual(__snake_case     ,		__snake_case					)

											__magic_name__:	List[Any]							=       self.get_rust_tokenizer()
											__magic_name__:	Dict							=       tokenizer.encode(__snake_case					)
											__magic_name__:	Union[str, Any]							=       rust_tokenizer.encode(__snake_case					)
											self.assertListEqual(__snake_case     ,		__snake_case					)

					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							Optional[Any]:
											__magic_name__:	Dict							=       AlbertTokenizer(__snake_case     ,		keep_accents=__snake_case					)

											__magic_name__:	Optional[Any]							=       tokenizer.tokenize("""This is a test"""					)
											self.assertListEqual(__snake_case     ,		["""▁this""", """▁is""", """▁a""", """▁test"""]					)

											self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case					)     ,		[4_8, 2_5, 2_1, 1_2_8_9]					)

											__magic_name__:	Dict							=       tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
											self.assertListEqual(
											    __snake_case     ,		["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """é""", """."""]					)
											__magic_name__:	Dict							=       tokenizer.convert_tokens_to_ids(__snake_case					)
											self.assertListEqual(__snake_case     ,		[3_1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]					)

											__magic_name__:	str							=       tokenizer.convert_ids_to_tokens(__snake_case					)
											self.assertListEqual(
											    __snake_case     ,		["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """."""]     ,		)

					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							int:
											__magic_name__:	Optional[int]							=       AlbertTokenizer(__snake_case					)

											__magic_name__:	Tuple							=       tokenizer.encode("""sequence builders"""					)
											__magic_name__:	List[str]							=       tokenizer.encode("""multi-sequence build"""					)

											__magic_name__:	Union[str, Any]							=       tokenizer.build_inputs_with_special_tokens(__snake_case					)
											__magic_name__:	Optional[Any]							=       tokenizer.build_inputs_with_special_tokens(__snake_case     ,		__snake_case					)

											assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
											assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
											    tokenizer.sep_token_id
											]






					@slow
					def   lowerCamelCase__   (			self  :      Optional[Any]					)			->							List[str]:
											# fmt: off
											__magic_name__:	Union[str, Any]							=       {"""attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """input_ids""": [[2, 2_1_9_7_0, 1_3, 5, 6_0_9_2, 1_6_7, 2_8, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 7_0_2_8, 1_2_0_5_1, 1_8, 1_7, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 3_5_1_5, 1_8_6_8_4, 8, 4_4_6_1, 6, 1_9_2_7, 2_9_7, 8, 1_2_0_6_0, 2_6_0_7, 1_8, 1_3, 5, 4_4_6_1, 1_5, 1_0_5_3_8, 3_8, 8, 1_3_5, 1_5, 8_2_2, 5_8, 1_5, 9_9_3, 1_0_3_6_3, 1_5, 1_4_6_0, 8_0_0_5, 4_4_6_1, 1_5, 9_9_3, 2_5_5, 2_3_2_8, 9, 9, 9, 6, 2_6, 1_1_1_2, 8_1_6, 3_2_6_0, 1_3, 5, 1_0_3, 2_3_7_7, 6, 1_7, 1_1_1_2, 8_1_6, 2_7_8_2, 1_3, 5, 1_0_3, 1_0_6_4_1, 6, 2_9, 8_4, 2_5_1_2, 2_4_3_0, 7_8_2, 1_8_6_8_4, 2_7_6_1, 1_9, 8_0_8, 2_4_3_0, 2_5_5_6, 1_7, 8_5_5, 1_4_8_0, 9_4_7_7, 4_0_9_1, 1_2_8, 1_1_7_1_2, 1_5, 7_1_0_3, 2_1_5_3, 6_7_3, 1_7, 2_4_8_8_3, 9_9_9_0, 9, 3], [2, 1_1_5_0_2, 2_5, 1_0_0_6, 2_0, 7_8_2, 8, 1_1_8_0_9, 8_5_5, 1_7_3_2, 1_9_3_9_3, 1_8_6_6_7, 3_7, 3_6_7, 2_1_0_1_8, 6_9, 1_8_5_4, 3_4, 1_1_8_6_0, 1_9_1_2_4, 2_7, 1_5_6, 2_2_5, 1_7, 1_9_3, 4_1_4_1, 1_9, 6_5, 9_1_2_4, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 1_4, 2_2_3_1, 8_8_6, 2_3_8_5, 1_7_6_5_9, 8_4, 1_4, 1_6_7_9_2, 1_9_5_2, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=__snake_case     ,		model_name="""albert-base-v2"""     ,		revision="""6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"""     ,		)











"""simple docstring"""





from typing import Union

import fire
import torch
from tqdm import tqdm



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


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



