




import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 		__A   (      UpperCamelCase__       ,    unittest.TestCase      ):
						UpperCamelCase      =       MgpstrTokenizer
						UpperCamelCase      =       False
						UpperCamelCase      =       {}
						UpperCamelCase      =       False

						def      A__    (		self :Tuple			):
										'''simple docstring'''

										super().setUp()

										# fmt: off
										__magic_name__						:						int										=["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
										# fmt: on
										__magic_name__						:						Union[str, Any]										=dict(zip(__snake_case     ,			range(len(__snake_case			)			)			)			)

										__magic_name__						:						Optional[int]										=os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES["""vocab_file"""]			)
										with open(self.vocab_file     ,			"""w"""     ,			encoding="""utf-8"""			) as fp:
														fp.write(json.dumps(__snake_case			) + """\n"""			)

						def      A__    (		self :str     ,			**__snake_case :Tuple			):
										'''simple docstring'''

										return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,			**__snake_case			)

						def      A__    (		self :List[str]     ,			__snake_case :List[str]			):
										'''simple docstring'''

										__magic_name__						:						Optional[int]										="""tester"""
										__magic_name__						:						Any										="""tester"""
										return input_text, output_text

						@unittest.skip("""MGP-STR always lower cases letters."""			)
						def      A__    (		self :Dict			):
										'''simple docstring'''

										pass

						def      A__    (		self :Dict			):
										'''simple docstring'''

										__magic_name__						:						Tuple										=self.get_tokenizers(do_lower_case=__snake_case			)
										for tokenizer in tokenizers:
														with self.subTest(f"{tokenizer.__class__.__name__}"			):
																		__magic_name__						:						Union[str, Any]										="""[SPECIAL_TOKEN]"""

																		tokenizer.add_special_tokens({"""cls_token""": special_token}			)
																		__magic_name__						:						Optional[Any]										=tokenizer.encode([special_token]     ,			add_special_tokens=__snake_case			)
																		self.assertEqual(len(__snake_case			)     ,			1			)

																		__magic_name__						:						int										=tokenizer.decode(__snake_case     ,			skip_special_tokens=__snake_case			)
																		self.assertTrue(special_token not in decoded			)

						def      A__    (		self :List[Any]			):
										'''simple docstring'''

										__magic_name__						:						int										=self.get_tokenizers()
										for tokenizer in tokenizers:
														with self.subTest(f"{tokenizer.__class__.__name__}"			):
																		__magic_name__					,			__magic_name__						:						List[str]										=self.get_input_output_texts(__snake_case			)

																		__magic_name__						:						Dict										=tokenizer.tokenize(__snake_case			)
																		__magic_name__						:						Union[str, Any]										=tokenizer.convert_tokens_to_ids(__snake_case			)
																		__magic_name__						:						Dict										=tokenizer.encode(__snake_case     ,			add_special_tokens=__snake_case			)
																		self.assertListEqual(__snake_case     ,			__snake_case			)

																		__magic_name__						:						Tuple										=tokenizer.convert_ids_to_tokens(__snake_case			)
																		self.assertNotEqual(len(__snake_case			)     ,			0			)
																		__magic_name__						:						Optional[Any]										=tokenizer.decode(__snake_case			)
																		self.assertIsInstance(__snake_case     ,			__snake_case			)

																		self.assertEqual(text_a.replace(""" """     ,			""""""			)     ,			__snake_case			)

						@unittest.skip("""MGP-STR tokenizer only handles one sequence."""			)
						def      A__    (		self :Tuple			):
										'''simple docstring'''

										pass


						@unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""			)
						def      A__    (		self :Union[str, Any]			):
										'''simple docstring'''

										pass






"""simple docstring"""




def     __magic_name__		(					UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		UpperCamelCase     :		float							,		)     ->						float:
    a__		=			[redshift, radiation_density, matter_density, dark_energy]
    if any(p < 0 for p in parameters     ):
        raise ValueError('All input parameters must be positive'     )

    if any(p > 1 for p in parameters[1:4]     ):
        raise ValueError('Relative densities cannot be greater than one'     )
    else:
        a__		=			1 - (matter_density + radiation_density + dark_energy)

        a__		=			(
            radiation_density * (redshift + 1) ** 4
            + matter_density * (redshift + 1) ** 3
            + curvature * (redshift + 1) ** 2
            + dark_energy
        )

        a__		=			hubble_constant * e_a ** (1 / 2)
        return hubble


if __name__ == "__main__":
    import doctest

    # run doctest
    doctest.testmod()

    # demo LCDM approximation
    a		:       Any     						=       0.3

    print(
        hubble_parameter(
            hubble_constant=68.3,
            radiation_density=1e-4,
            matter_density=matter_density,
            dark_energy=1 - matter_density,
            redshift=0,
        )
    )


