


import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
      from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
      snake_case__				:	Dict					       =					get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
      from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

snake_case__				:	Optional[int]					       =					12_8022
snake_case__				:	str					       =					12_8028





@require_sentencepiece
class   SCREAMING_SNAKE_CASE_			(a__						,       unittest.TestCase						):




       '''simple docstring'''



       _a   							=							MaMaaaTokenizer
       _a   							=							False
       _a   							=							False
       _a   							=							True



       def 				_lowerCAmelCase							(						self				:				Union[str, Any]							)					->str:
          super().setUp()

          lowerCamelCase_						:   Union[str, Any]		= ["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
          lowerCamelCase_						:   Union[str, Any]		= dict(zip(__a		,				range(len(__a							)							)							)							)
          lowerCamelCase_						:   str		= Path(self.tmpdirname							)
          save_json(__a		,				save_dir / VOCAB_FILES_NAMES["""vocab_file"""]							)
          if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
             copyfile(__a		,				save_dir / VOCAB_FILES_NAMES["""spm_file"""]							)

          lowerCamelCase_						:   str		= MaMaaaTokenizer.from_pretrained(self.tmpdirname							)
          tokenizer.save_pretrained(self.tmpdirname							)



       def 				_lowerCAmelCase							(						self				:				Union[str, Any]		,				**__a				:				str							)					->List[Any]:
          return MaMaaaTokenizer.from_pretrained(self.tmpdirname		,				**__a							)



       def 				_lowerCAmelCase							(						self				:				int		,				__a				:				Dict							)					->Optional[Any]:
          return (
              "This is a test",
              "This is a test",
          )



       def 				_lowerCAmelCase							(						self				:				Dict							)					->Union[str, Any]:
          lowerCamelCase_						:   int		= """</s>"""
          lowerCamelCase_						:   str		= 0

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



       def 				_lowerCAmelCase							(						self				:				List[str]							)					->int:
          lowerCamelCase_						:   Tuple		= self.get_tokenizer()
          lowerCamelCase_						:   Tuple		= list(tokenizer.get_vocab().keys()							)

          self.assertEqual(vocab_keys[0]		,				"""</s>"""							)
          self.assertEqual(vocab_keys[1]		,				"""<unk>"""							)
          self.assertEqual(vocab_keys[-1]		,				"""<s>"""							)
          self.assertEqual(len(__a							)		,				tokenizer.vocab_size + len(tokenizer.get_added_vocab()							)							)



       @unittest.skip("""Skip this test while all models are still to be uploaded."""							)
       def 				_lowerCAmelCase							(						self				:				Optional[int]							)					->str:
          pass



       def 				_lowerCAmelCase							(						self				:				str							)					->Optional[Any]:
          lowerCamelCase_						:   Union[str, Any]		= self.get_tokenizer()

          lowerCamelCase_						:   Optional[Any]		= tokenizer.tokenize("""This is a test"""							)
          self.assertListEqual(__a		,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(__a							)		,				[2, 3, 4, 5, 6]		,				)

          lowerCamelCase_						:   int		= tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]							)
          self.assertListEqual(__a		,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

          lowerCamelCase_						:   Dict		= tokenizer.convert_tokens_to_string(__a							)
          self.assertEqual(__a		,				"""This is a test"""							)




       @slow
       def 				_lowerCAmelCase							(						self				:				str							)					->Optional[Any]:
          # fmt: off
          lowerCamelCase_						:   Tuple		= {"""input_ids""": [[128_022, 110_108, 397, 11, 38_272, 2_247, 124_811, 285, 18_105, 1_586, 207, 7, 39_534, 4_428, 397, 1_019, 18_105, 1_586, 207, 7, 41_337, 16_786, 241, 7, 20_214, 17, 125_690, 10_398, 7, 44_378, 58_069, 68_342, 7_798, 7_343, 11, 299, 33_310, 4, 158, 37_350, 94_077, 4_569, 299, 33_310, 90, 4, 52_840, 290, 4, 31_270, 112, 299, 682, 4, 52_840, 39_953, 14_079, 193, 52_519, 90_894, 17_894, 120_697, 11, 40_445, 551, 17, 1_019, 52_519, 90_894, 17_756, 963, 11, 40_445, 480, 17, 9_792, 1_120, 5_173, 1_393, 6_240, 16_786, 241, 120_996, 28, 1_245, 1_393, 118_240, 11_123, 1_019, 93_612, 2_691, 10_618, 98_058, 120_409, 1_928, 279, 4, 40_683, 367, 178, 207, 1_019, 103, 103_121, 506, 65_296, 5, 2], [128_022, 21_217, 367, 117, 125_450, 128, 719, 7, 7_308, 40, 93_612, 12_669, 1_116, 16_704, 71, 17_785, 3_699, 15_592, 35, 144, 9_584, 241, 11_943, 713, 950, 799, 2_247, 88_427, 150, 149, 118_813, 120_706, 1_019, 106_906, 81_518, 28, 1_224, 22_799, 397, 5, 2, 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], [128_022, 1_658, 123_311, 5_155, 5_578, 4_722, 279, 14_947, 2_366, 1_120, 1_197, 14, 1_348, 9_232, 5, 2, 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]], """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, 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], [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, 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=__a		,				model_name="""facebook/m2m100_418M"""		,				revision="""c168bae485c864188cf9aa0e4108b0b6934dc91e"""		,				)







@require_torch
@require_sentencepiece
@require_tokenizers
class   SCREAMING_SNAKE_CASE_			(unittest.TestCase						):




       '''simple docstring'''



       _a   							=							"facebook/m2m100_418M"
       _a   							=							[
           "In my opinion, there are two levels of response from the French government.",
           "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
       ]
       _a   							=							[
           "Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.",
           "L'affaire NSA souligne l'absence totale de débat sur le renseignement",
       ]

       # fmt: off
       _a   							=							[EN_CODE, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]



       @classmethod
       def 				_lowerCAmelCase							(						cls				:				Tuple							)					->int:
          lowerCamelCase_						:   MaMaaaTokenizer		= MaMaaaTokenizer.from_pretrained(
              cls.checkpoint_name		,				src_lang="""en"""		,				tgt_lang="""fr"""							)
          lowerCamelCase_						:   Union[str, Any]		= 1
          return cls



       def 				_lowerCAmelCase							(						self				:				List[Any]							)					->Optional[int]:
          self.assertEqual(self.tokenizer.get_lang_id("""ar"""							)		,				128_006							)
          self.assertEqual(self.tokenizer.get_lang_id("""en"""							)		,				128_022							)
          self.assertEqual(self.tokenizer.get_lang_id("""ro"""							)		,				128_076							)
          self.assertEqual(self.tokenizer.get_lang_id("""mr"""							)		,				128_063							)



       def 				_lowerCAmelCase							(						self				:				List[Any]							)					->Any:
          lowerCamelCase_						:   Dict		= self.tokenizer.get_vocab()
          self.assertEqual(len(__a							)		,				self.tokenizer.vocab_size							)
          self.assertEqual(vocab["""<unk>"""]		,				3							)
          self.assertIn(self.tokenizer.get_lang_token("""en"""							)		,				__a							)



       def 				_lowerCAmelCase							(						self				:				Optional[Any]							)					->List[Any]:
          lowerCamelCase_						:   Union[str, Any]		= """en"""
          lowerCamelCase_						:   List[str]		= self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
          self.assertListEqual(self.expected_src_tokens		,				__a							)



       def 				_lowerCAmelCase							(						self				:				Optional[int]							)					->Dict:
          self.assertIn(__a		,				self.tokenizer.all_special_ids							)
          # fmt: off
          lowerCamelCase_						:   Optional[Any]		= [FR_CODE, 5_364, 82, 8_642, 4, 294, 47, 8, 14_028, 136, 3_286, 9_706, 6, 90_797, 6, 144_012, 162, 88_128, 30_061, 5, 2]
          # fmt: on
          lowerCamelCase_						:   Tuple		= self.tokenizer.decode(__a		,				skip_special_tokens=__a							)
          lowerCamelCase_						:   Union[str, Any]		= self.tokenizer.decode(generated_ids[1:]		,				skip_special_tokens=__a							)
          self.assertEqual(__a		,				__a							)
          self.assertNotIn(self.tokenizer.eos_token		,				__a							)



       def 				_lowerCAmelCase							(						self				:				Dict							)					->Optional[int]:
          lowerCamelCase_						:   Optional[int]		= tempfile.mkdtemp()
          lowerCamelCase_						:   Tuple		= self.tokenizer.lang_token_to_id
          self.tokenizer.save_pretrained(__a							)
          lowerCamelCase_						:   Any		= MaMaaaTokenizer.from_pretrained(__a							)
          self.assertDictEqual(new_tok.lang_token_to_id		,				__a							)



       @require_torch
       def 				_lowerCAmelCase							(						self				:				Optional[Any]							)					->List[str]:
          lowerCamelCase_						:   str		= """en"""
          lowerCamelCase_						:   str		= """fr"""

          lowerCamelCase_						:   Dict		= self.tokenizer(self.src_text		,				text_target=self.tgt_text		,				padding=__a		,				return_tensors="""pt"""							)

          lowerCamelCase_						:   List[Any]		= shift_tokens_right(
              batch["""labels"""]		,				self.tokenizer.pad_token_id		,				self.tokenizer.eos_token_id							)

          for k in batch:
             lowerCamelCase_						:   int		= batch[k].tolist()
          # batch = {k: v.tolist() for k,v in batch.items()}
          # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
          # batch.decoder_inputs_ids[0][0] ==
          assert batch.input_ids[1][0] == EN_CODE
          assert batch.input_ids[1][-1] == 2
          assert batch.labels[1][0] == FR_CODE
          assert batch.labels[1][-1] == 2
          assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]



       @require_torch
       def 				_lowerCAmelCase							(						self				:				Optional[int]							)					->Union[str, Any]:
          lowerCamelCase_						:   Tuple		= """mr"""
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id("""mr"""							)]							)
          self.assertListEqual(self.tokenizer.suffix_tokens		,				[self.tokenizer.eos_token_id]							)

          lowerCamelCase_						:   List[str]		= """zh"""
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id("""zh"""							)]							)
          self.assertListEqual(self.tokenizer.suffix_tokens		,				[self.tokenizer.eos_token_id]							)



       @require_torch
       def 				_lowerCAmelCase							(						self				:				Dict							)					->Union[str, Any]:
          lowerCamelCase_						:   List[Any]		= """mr"""
          self.tokenizer._switch_to_target_mode()
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id("""mr"""							)]							)
          self.assertListEqual(self.tokenizer.suffix_tokens		,				[self.tokenizer.eos_token_id]							)
          self.tokenizer._switch_to_input_mode()
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id(self.tokenizer.src_lang							)]							)

          lowerCamelCase_						:   Any		= """zh"""
          self.tokenizer._switch_to_target_mode()
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id("""zh"""							)]							)
          self.assertListEqual(self.tokenizer.suffix_tokens		,				[self.tokenizer.eos_token_id]							)
          self.tokenizer._switch_to_input_mode()
          self.assertListEqual(self.tokenizer.prefix_tokens		,				[self.tokenizer.get_lang_id(self.tokenizer.src_lang							)]							)




       @require_torch
       def 				_lowerCAmelCase							(						self				:				Optional[int]							)					->Dict:
          lowerCamelCase_						:   List[Any]		= self.tokenizer._build_translation_inputs("""A test"""		,				return_tensors="""pt"""		,				src_lang="""en"""		,				tgt_lang="""ar"""							)

          self.assertEqual(
              nested_simplify(__a							)		,				{
                  # en_XX, A, test, EOS
                  """input_ids""": [[128_022, 58, 4_183, 2]],
                  """attention_mask""": [[1, 1, 1, 1]],
                  # ar_AR
                  """forced_bos_token_id""": 128_006,
              }		,				)









def    __lowerCamelCase   (      A__						: float						,						A__						: float						,						A__						: float						,						A__						: float						,						A__						: float						,						)     ->    float:
   lowerCamelCase_						:   List[str]		= [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:
      lowerCamelCase_						:   Union[str, Any]		= 1 - (matter_density + radiation_density + dark_energy)

      lowerCamelCase_						:   int		= (
          radiation_density * (redshift + 1) ** 4
          + matter_density * (redshift + 1) ** 3
          + curvature * (redshift + 1) ** 2
          + dark_energy
      )

      lowerCamelCase_						:   Dict		= hubble_constant * e_a ** (1 / 2)
      return hubble


if __name__ == "__main__":
      import doctest

      # run doctest
      doctest.testmod()

      # demo LCDM approximation
      snake_case__				:	str					       =					0.3

      print(
          hubble_parameter(
              hubble_constant=6_8.3,
              radiation_density=1e-4,
              matter_density=matter_density,
              dark_energy=1 - matter_density,
              redshift=0,
          )
      )





