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 __snake_case       (		lowerCamelCase_     ,	unittest.TestCase	):
   lowerCAmelCase_														=							LongformerTokenizer
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							LongformerTokenizerFast
   lowerCAmelCase_														=							True




   def 			__a		(					self    :       Dict   ):



     """simple docstring"""






     super().setUp()

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

     SCREAMING_SNAKE_CASE__    							=   os.path.join(self.tmpdirname ,			VOCAB_FILES_NAMES["""vocab_file"""]   )
     SCREAMING_SNAKE_CASE__    							=   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(_lowercase   ) + """\n"""   )
     with open(self.merges_file ,			"""w""" ,			encoding="""utf-8"""   ) as fp:
       fp.write("""\n""".join(_lowercase   )   )




   def 			__a		(					self    :       Optional[Any] ,			**_lowercase    :       Any   ):



     """simple docstring"""






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




   def 			__a		(					self    :       str ,			**_lowercase    :       Optional[int]   ):



     """simple docstring"""






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




   def 			__a		(					self    :       int ,			_lowercase    :       Tuple   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   """lower newer"""
     SCREAMING_SNAKE_CASE__    							=   """lower newer"""
     return input_text, output_text




   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.tokenizer_class(self.vocab_file ,			self.merges_file ,			**self.special_tokens_map   )
     SCREAMING_SNAKE_CASE__    							=   """lower newer"""
     SCREAMING_SNAKE_CASE__    							=   ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
     SCREAMING_SNAKE_CASE__    							=   tokenizer.tokenize(_lowercase   )  # , add_prefix_space=True)
     self.assertListEqual(_lowercase ,			_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   tokens + [tokenizer.unk_token]
     SCREAMING_SNAKE_CASE__    							=   [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   ) ,			_lowercase   )




   def 			__a		(					self    :       List[str]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.get_tokenizer()

     self.assertListEqual(tokenizer.encode("""Hello world!""" ,			add_special_tokens=_lowercase   ) ,			[0, 3_14_14, 2_32, 3_28, 2]   )
     self.assertListEqual(
         tokenizer.encode("""Hello world! cécé herlolip 418""" ,			add_special_tokens=_lowercase   ) ,			[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2] ,			)




   @slow
   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""   )

     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode("""sequence builders""" ,			add_special_tokens=_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode("""multi-sequence build""" ,			add_special_tokens=_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(
         """sequence builders""" ,			add_special_tokens=_lowercase ,			add_prefix_space=_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(
         """sequence builders""" ,			"""multi-sequence build""" ,			add_special_tokens=_lowercase ,			add_prefix_space=_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   tokenizer.build_inputs_with_special_tokens(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.build_inputs_with_special_tokens(_lowercase ,			_lowercase   )

     assert encoded_sentence == encoded_text_from_decode
     assert encoded_pair == encoded_pair_from_decode




   def 			__a		(					self    :       Optional[int]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.get_tokenizer()

     SCREAMING_SNAKE_CASE__    							=   """Encode this sequence."""
     SCREAMING_SNAKE_CASE__    							=   tokenizer.byte_encoder[""" """.encode("""utf-8"""   )[0]]

     # Testing encoder arguments
     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(_lowercase ,			add_special_tokens=_lowercase ,			add_prefix_space=_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
     self.assertNotEqual(_lowercase ,			_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(_lowercase ,			add_special_tokens=_lowercase ,			add_prefix_space=_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
     self.assertEqual(_lowercase ,			_lowercase   )

     tokenizer.add_special_tokens({"""bos_token""": """<s>"""}   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(_lowercase ,			add_special_tokens=_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
     self.assertNotEqual(_lowercase ,			_lowercase   )

     # Testing spaces after special tokens
     SCREAMING_SNAKE_CASE__    							=   """<mask>"""
     tokenizer.add_special_tokens(
         {"""mask_token""": AddedToken(_lowercase ,			lstrip=_lowercase ,			rstrip=_lowercase   )}   )  # mask token has a left space
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_tokens_to_ids(_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   """Encode <mask> sequence"""
     SCREAMING_SNAKE_CASE__    							=   """Encode <mask>sequence"""

     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   encoded.index(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
     self.assertEqual(_lowercase ,			_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   encoded.index(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
     self.assertNotEqual(_lowercase ,			_lowercase   )




   def 			__a		(					self    :       str   ):



     """simple docstring"""






     pass




   def 			__a		(					self    :       Optional[int]   ):



     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(_lowercase ,			**_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   self.tokenizer_class.from_pretrained(_lowercase ,			**_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   """A, <mask> AllenNLP sentence."""
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r.encode_plus(_lowercase ,			add_special_tokens=_lowercase ,			return_token_type_ids=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_p.encode_plus(_lowercase ,			add_special_tokens=_lowercase ,			return_token_type_ids=_lowercase   )

         # 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"""]   ) ,			)

         SCREAMING_SNAKE_CASE__    							=   tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]   )
         SCREAMING_SNAKE_CASE__    							=   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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )
         self.assertSequenceEqual(tokens_r["""input_ids"""] ,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )

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




   def 			__a		(					self    :       Union[str, Any]   ):



     """simple docstring"""






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

       SCREAMING_SNAKE_CASE__    							=   json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()   )
       SCREAMING_SNAKE_CASE__    							=   json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()   )

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

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




   def 			__a		(					self    :       Optional[int]   ):



     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
         SCREAMING_SNAKE_CASE__    							=   """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
         SCREAMING_SNAKE_CASE__    							=   f"""{text_of_1_token} {text_of_1_token}"""

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(len(_lowercase   ) + 1, len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(len(_lowercase   ) + 1, len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(len(_lowercase   ), len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(len(_lowercase   ), len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   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)),
         # )

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(1, 1 + len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(1 + len(_lowercase   ) + 1, 1 + len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, 1 + len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(1 + len(_lowercase   ), 1 + len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

         SCREAMING_SNAKE_CASE__    							=   self.rust_tokenizer_class.from_pretrained(
             _lowercase ,			use_fast=_lowercase ,			add_prefix_space=_lowercase ,			trim_offsets=_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   tokenizer_r(_lowercase ,			return_offsets_mapping=_lowercase ,			add_special_tokens=_lowercase   )
         self.assertEqual(encoding.offset_mapping[0] ,			(0, 1 + len(_lowercase   ))   )
         self.assertEqual(
             encoding.offset_mapping[1] ,			(1 + len(_lowercase   ), 1 + len(_lowercase   ) + 1 + len(_lowercase   )) ,			)

from typing import List, Optional

import numpy as np

from ...processing_utils import ProcessorMixin
from ...utils import to_numpy







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"EncodecFeatureExtractor"
   lowerCAmelCase_														=							("T5Tokenizer", "T5TokenizerFast")




   def __init__(					self    :       List[Any] ,			_lowercase    :       int ,			_lowercase    :       Any   ):



     """simple docstring"""






     super().__init__(_lowercase ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   self.feature_extractor
     SCREAMING_SNAKE_CASE__    							=   False




   def 			__a		(					self    :       Tuple ,			_lowercase    :       str=None ,			_lowercase    :       int=None ,			_lowercase    :       Any=True   ):



     """simple docstring"""






     return self.tokenizer.get_decoder_prompt_ids(task=_lowercase ,			language=_lowercase ,			no_timestamps=_lowercase   )




   def __call__(					self    :       Tuple ,			*_lowercase    :       Tuple ,			**_lowercase    :       Union[str, Any]   ):



     """simple docstring"""






     if self._in_target_context_manager:
       return self.current_processor(*_lowercase ,			**_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""sampling_rate""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""text""" ,			_lowercase   )
     if len(_lowercase   ) > 0:
       SCREAMING_SNAKE_CASE__    							=   args[0]
       SCREAMING_SNAKE_CASE__    							=   args[1:]

     if audio is None and text is None:
       raise ValueError("""You need to specify either an `audio` or `text` input to process."""   )

     if text is not None:
       SCREAMING_SNAKE_CASE__    							=   self.tokenizer(_lowercase ,			**_lowercase   )

     if audio is not None:
       SCREAMING_SNAKE_CASE__    							=   self.feature_extractor(_lowercase ,			*_lowercase ,			sampling_rate=_lowercase ,			**_lowercase   )

     if audio is None:
       return inputs

     elif text is None:
       return audio_inputs

     else:
       SCREAMING_SNAKE_CASE__    							=   audio_inputs["""input_values"""]
       if "padding_mask" in audio_inputs:
         SCREAMING_SNAKE_CASE__    							=   audio_inputs["""padding_mask"""]
       return inputs




   def 			__a		(					self    :       Dict ,			*_lowercase    :       Any ,			**_lowercase    :       Optional[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""padding_mask""" ,			_lowercase   )

     if len(_lowercase   ) > 0:
       SCREAMING_SNAKE_CASE__    							=   args[0]
       SCREAMING_SNAKE_CASE__    							=   args[1:]

     if audio_values is not None:
       return self._decode_audio(_lowercase ,			padding_mask=_lowercase   )
     else:
       return self.tokenizer.batch_decode(*_lowercase ,			**_lowercase   )




   def 			__a		(					self    :       List[str] ,			*_lowercase    :       Tuple ,			**_lowercase    :       Optional[Any]   ):



     """simple docstring"""






     return self.tokenizer.decode(*_lowercase ,			**_lowercase   )




   def 			__a		(					self    :       List[str] ,			_lowercase    :       Tuple ,			_lowercase    :       Optional = None   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   to_numpy(_lowercase   )
     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   audio_values.shape

     if padding_mask is None:
       return list(_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   to_numpy(_lowercase   )

     # match the sequence length of the padding mask to the generated audio arrays by padding with the **non-padding**
     # token (so that the generated audio values are **not** treated as padded tokens)
     SCREAMING_SNAKE_CASE__    							=   seq_len - padding_mask.shape[-1]
     SCREAMING_SNAKE_CASE__    							=   1 - self.feature_extractor.padding_value
     SCREAMING_SNAKE_CASE__    							=   np.pad(_lowercase ,			((0, 0), (0, difference)) ,			"""constant""" ,			constant_values=_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   audio_values.tolist()
     for i in range(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   np.asarray(audio_values[i]   )[
           padding_mask[i][None, :] != self.feature_extractor.padding_value
       ]
       SCREAMING_SNAKE_CASE__    							=   sliced_audio.reshape(_lowercase ,			-1   )

     return audio_values
