

"""simple docstring"""
import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class       lowerCamelCase	(       lowerCAmelCase__					,					unittest.TestCase   ):


  '''simple docstring'''







  SCREAMING_SNAKE_CASE					      =  LongformerTokenizer
  SCREAMING_SNAKE_CASE					      =  True
  SCREAMING_SNAKE_CASE					      =  LongformerTokenizerFast
  SCREAMING_SNAKE_CASE					      =  True



  def  _a      (self	):


        """simple docstring"""

        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        UpperCAmelCase__			:							str							=    [
            """l""",
            """o""",
            """w""",
            """e""",
            """r""",
            """s""",
            """t""",
            """i""",
            """d""",
            """n""",
            """\u0120""",
            """\u0120l""",
            """\u0120n""",
            """\u0120lo""",
            """\u0120low""",
            """er""",
            """\u0120lowest""",
            """\u0120newer""",
            """\u0120wider""",
            """<unk>""",
        ]
        UpperCAmelCase__			:							Dict							=    dict(zip(_lowerCamelCase							,       range(len(_lowerCamelCase	)	)	)	)
        UpperCAmelCase__			:							Any							=    ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
        UpperCAmelCase__			:							List[Any]							=    {"""unk_token""": """<unk>"""}

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



  def  _a      (self							,       **_lowerCamelCase	):


        """simple docstring"""

        kwargs.update(self.special_tokens_map	)
        return self.tokenizer_class.from_pretrained(self.tmpdirname							,       **_lowerCamelCase	)



  def  _a      (self							,       **_lowerCamelCase	):


        """simple docstring"""

        kwargs.update(self.special_tokens_map	)
        return self.rust_tokenizer_class.from_pretrained(self.tmpdirname							,       **_lowerCamelCase	)



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							Dict							=    """lower newer"""
        UpperCAmelCase__			:							List[Any]							=    """lower newer"""
        return input_text, output_text



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[Any]							=    self.tokenizer_class(self.vocab_file							,       self.merges_file							,       **self.special_tokens_map	)
        UpperCAmelCase__			:							Optional[Any]							=    """lower newer"""
        UpperCAmelCase__			:							Union[str, Any]							=    ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
        UpperCAmelCase__			:							Optional[Any]							=    tokenizer.tokenize(_lowerCamelCase	)  # , add_prefix_space=True)
        self.assertListEqual(_lowerCamelCase							,       _lowerCamelCase	)

        UpperCAmelCase__			:							Optional[int]							=    tokens + [tokenizer.unk_token]
        UpperCAmelCase__			:							str							=    [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase	)							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[Any]							=    self.get_tokenizer()

        self.assertListEqual(tokenizer.encode("""Hello world!"""							,       add_special_tokens=_lowerCamelCase	)							,       [0, 31414, 232, 328, 2]	)
        self.assertListEqual(
            tokenizer.encode("""Hello world! cécé herlolip 418"""							,       add_special_tokens=_lowerCamelCase	)							,       [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]							,       )



  @slow
  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[int]							=    self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""	)

        UpperCAmelCase__			:							Any							=    tokenizer.encode("""sequence builders"""							,       add_special_tokens=_lowerCamelCase	)
        UpperCAmelCase__			:							str							=    tokenizer.encode("""multi-sequence build"""							,       add_special_tokens=_lowerCamelCase	)

        UpperCAmelCase__			:							int							=    tokenizer.encode(
            """sequence builders"""							,       add_special_tokens=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase	)
        UpperCAmelCase__			:							Optional[Any]							=    tokenizer.encode(
            """sequence builders"""							,       """multi-sequence build"""							,       add_special_tokens=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase	)

        UpperCAmelCase__			:							Union[str, Any]							=    tokenizer.build_inputs_with_special_tokens(_lowerCamelCase	)
        UpperCAmelCase__			:							List[str]							=    tokenizer.build_inputs_with_special_tokens(_lowerCamelCase							,       _lowerCamelCase	)

        assert encoded_sentence == encoded_text_from_decode
        assert encoded_pair == encoded_pair_from_decode



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    self.get_tokenizer()

        UpperCAmelCase__			:							str							=    """Encode this sequence."""
        UpperCAmelCase__			:							List[str]							=    tokenizer.byte_encoder[""" """.encode("""utf-8"""	)[0]]

        # Testing encoder arguments
        UpperCAmelCase__			:							int							=    tokenizer.encode(_lowerCamelCase							,       add_special_tokens=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase	)
        UpperCAmelCase__			:							int							=    tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
        self.assertNotEqual(_lowerCamelCase							,       _lowerCamelCase	)

        UpperCAmelCase__			:							List[str]							=    tokenizer.encode(_lowerCamelCase							,       add_special_tokens=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase	)
        UpperCAmelCase__			:							Any							=    tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
        self.assertEqual(_lowerCamelCase							,       _lowerCamelCase	)

        tokenizer.add_special_tokens({"""bos_token""": """<s>"""}	)
        UpperCAmelCase__			:							List[str]							=    tokenizer.encode(_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
        UpperCAmelCase__			:							Optional[Any]							=    tokenizer.convert_ids_to_tokens(encoded[1]	)[0]
        self.assertNotEqual(_lowerCamelCase							,       _lowerCamelCase	)

        # Testing spaces after special tokens
        UpperCAmelCase__			:							Optional[Any]							=    """<mask>"""
        tokenizer.add_special_tokens(
            {"""mask_token""": AddedToken(_lowerCamelCase							,       lstrip=_lowerCamelCase							,       rstrip=_lowerCamelCase	)}	)  # mask token has a left space
        UpperCAmelCase__			:							Union[str, Any]							=    tokenizer.convert_tokens_to_ids(_lowerCamelCase	)

        UpperCAmelCase__			:							int							=    """Encode <mask> sequence"""
        UpperCAmelCase__			:							List[str]							=    """Encode <mask>sequence"""

        UpperCAmelCase__			:							List[Any]							=    tokenizer.encode(_lowerCamelCase	)
        UpperCAmelCase__			:							str							=    encoded.index(_lowerCamelCase	)
        UpperCAmelCase__			:							int							=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
        self.assertEqual(_lowerCamelCase							,       _lowerCamelCase	)

        UpperCAmelCase__			:							str							=    tokenizer.encode(_lowerCamelCase	)
        UpperCAmelCase__			:							Dict							=    encoded.index(_lowerCamelCase	)
        UpperCAmelCase__			:							Tuple							=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
        self.assertNotEqual(_lowerCamelCase							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        pass



  def  _a      (self	):


        """simple docstring"""

        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
                    UpperCAmelCase__			:							List[Any]							=    self.rust_tokenizer_class.from_pretrained(_lowerCamelCase							,       **_lowerCamelCase	)
                    UpperCAmelCase__			:							Dict							=    self.tokenizer_class.from_pretrained(_lowerCamelCase							,       **_lowerCamelCase	)
                    UpperCAmelCase__			:							List[Any]							=    """A, <mask> AllenNLP sentence."""
                    UpperCAmelCase__			:							Any							=    tokenizer_r.encode_plus(_lowerCamelCase							,       add_special_tokens=_lowerCamelCase							,       return_token_type_ids=_lowerCamelCase	)
                    UpperCAmelCase__			:							str							=    tokenizer_p.encode_plus(_lowerCamelCase							,       add_special_tokens=_lowerCamelCase							,       return_token_type_ids=_lowerCamelCase	)

                    # token_type_ids should put 0 everywhere
                    self.assertEqual(sum(tokens_r["""token_type_ids"""]	)							,       sum(tokens_p["""token_type_ids"""]	)	)

                    # attention_mask should put 1 everywhere, so sum over length should be 1
                    self.assertEqual(
                        sum(tokens_r["""attention_mask"""]	) / len(tokens_r["""attention_mask"""]	)							,       sum(tokens_p["""attention_mask"""]	) / len(tokens_p["""attention_mask"""]	)							,       )

                    UpperCAmelCase__			:							List[Any]							=    tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]	)
                    UpperCAmelCase__			:							Optional[Any]							=    tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]	)

                    # Rust correctly handles the space before the mask while python doesnt
                    self.assertSequenceEqual(tokens_p["""input_ids"""]							,       [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]	)
                    self.assertSequenceEqual(tokens_r["""input_ids"""]							,       [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]	)

                    self.assertSequenceEqual(
                        _lowerCamelCase							,       ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)
                    self.assertSequenceEqual(
                        _lowerCamelCase							,       ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)



  def  _a      (self	):


        """simple docstring"""

        for trim_offsets, add_prefix_space in itertools.product([True, False]							,       repeat=2	):
              UpperCAmelCase__			:							int							=    self.rust_tokenizer_class.from_pretrained(
                  self.tmpdirname							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)

              UpperCAmelCase__			:							List[Any]							=    json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
              UpperCAmelCase__			:							Union[str, Any]							=    json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()	)

              self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]							,       _lowerCamelCase	)

              self.assertEqual(post_processor_state["""add_prefix_space"""]							,       _lowerCamelCase	)
              self.assertEqual(post_processor_state["""trim_offsets"""]							,       _lowerCamelCase	)




  def  _a      (self	):


        """simple docstring"""

        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
                    UpperCAmelCase__			:							List[str]							=    """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                    UpperCAmelCase__			:							Optional[Any]							=    F"""{text_of_1_token} {text_of_1_token}"""

                    UpperCAmelCase__			:							Any							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							Optional[Any]							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (len(_lowerCamelCase	) + 1, len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							List[str]							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							Dict							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (len(_lowerCamelCase	) + 1, len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							Any							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							Any							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (len(_lowerCamelCase	), len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							Any							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							Dict							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (len(_lowerCamelCase	), len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							Optional[Any]							=    F""" {text}"""

                    # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                    #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                    # )
                    # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                    # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                    # self.assertEqual(
                    #     encoding.offset_mapping[1],
                    #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                    # )

                    UpperCAmelCase__			:							int							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							str							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (1, 1 + len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (1 + len(_lowerCamelCase	) + 1, 1 + len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							int							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							List[str]							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, 1 + len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (1 + len(_lowerCamelCase	), 1 + len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )

                    UpperCAmelCase__			:							Dict							=    self.rust_tokenizer_class.from_pretrained(
                        _lowerCamelCase							,       use_fast=_lowerCamelCase							,       add_prefix_space=_lowerCamelCase							,       trim_offsets=_lowerCamelCase	)
                    UpperCAmelCase__			:							Optional[Any]							=    tokenizer_r(_lowerCamelCase							,       return_offsets_mapping=_lowerCamelCase							,       add_special_tokens=_lowerCamelCase	)
                    self.assertEqual(encoding.offset_mapping[0]							,       (0, 1 + len(_lowerCamelCase	))	)
                    self.assertEqual(
                        encoding.offset_mapping[1]							,       (1 + len(_lowerCamelCase	), 1 + len(_lowerCamelCase	) + 1 + len(_lowerCamelCase	))							,       )




"""simple docstring"""
import cmath
import math




def 					a__						(						lowerCAmelCase			,	lowerCAmelCase			,	lowerCAmelCase			,	lowerCAmelCase    )	-> complex:
      UpperCAmelCase__			:							str							=    math.radians(lowerCAmelCase    )
      UpperCAmelCase__			:							Optional[int]							=    math.radians(lowerCAmelCase    )

      # Convert voltage and current to rectangular form
      UpperCAmelCase__			:							Union[str, Any]							=    cmath.rect(lowerCAmelCase			,	lowerCAmelCase    )
      UpperCAmelCase__			:							List[str]							=    cmath.rect(lowerCAmelCase			,	lowerCAmelCase    )

      # Calculate apparent power
      return voltage_rect * current_rect


if __name__ == "__main__":
    import doctest

    doctest.testmod()

