



from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
			import timm


if is_torch_available():
			from torch import Tensor
class 			_lowerCAmelCase   ( _UpperCAmelCase    ,					_UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  List[Any]      =			"""pixel_values"""
			lowercase__      :  Optional[int]      =			False
			lowercase__      :  Any      =			TimmBackboneConfig





			def __init__(				self	:       Optional[Any]			,     lowercase	:       Dict			,     **lowercase	:       Any   )						->					List[Any]:
									"""simple docstring"""







									requires_backends(self			,     """timm"""   )
									super().__init__(UpperCAmelCase__   )
									__lowercase					=				config

									if config.backbone is None:
															raise ValueError("""backbone is not set in the config. Please set it to a timm model name."""   )

									if config.backbone not in timm.list_models():
															raise ValueError(F"backbone {config.backbone} is not supported by timm."   )

									if hasattr(UpperCAmelCase__			,     """out_features"""   ) and config.out_features is not None:
															raise ValueError("""out_features is not supported by TimmBackbone. Please use out_indices instead."""   )

									__lowercase					=				getattr(UpperCAmelCase__			,     """use_pretrained_backbone"""			,     UpperCAmelCase__   )
									if pretrained is None:
															raise ValueError("""use_pretrained_backbone is not set in the config. Please set it to True or False."""   )

									# We just take the final layer by default. This matches the default for the transformers models.
									__lowercase					=				config.out_indices if getattr(UpperCAmelCase__			,     """out_indices"""			,     UpperCAmelCase__   ) is not None else (-1,)

									__lowercase					=				timm.create_model(
									    config.backbone			,     pretrained=UpperCAmelCase__			,     features_only=config.features_only			,     in_chans=config.num_channels			,     out_indices=UpperCAmelCase__			,     **UpperCAmelCase__			,     )
									# These are used to control the output of the model when called. If output_hidden_states is True, then
									# return_layers is modified to include all layers.
									__lowercase					=				self._backbone.return_layers
									__lowercase					=				{layer["""module"""]: str(UpperCAmelCase__   ) for i, layer in enumerate(self._backbone.feature_info.info   )}
									super()._init_backbone(UpperCAmelCase__   )





			@classmethod
			def 		snake_case__			(				cls	:       List[str]			,     lowercase	:       Optional[int]			,     *lowercase	:       Union[str, Any]			,     **lowercase	:       List[Any]   )						->					Union[str, Any]:
									"""simple docstring"""







									requires_backends(cls			,     ["""vision""", """timm"""]   )
									from ...models.timm_backbone import TimmBackboneConfig

									__lowercase					=				kwargs.pop("""config"""			,     TimmBackboneConfig()   )

									__lowercase					=				kwargs.pop("""use_timm_backbone"""			,     UpperCAmelCase__   )
									if not use_timm:
															raise ValueError("""use_timm_backbone must be True for timm backbones"""   )

									__lowercase					=				kwargs.pop("""num_channels"""			,     config.num_channels   )
									__lowercase					=				kwargs.pop("""features_only"""			,     config.features_only   )
									__lowercase					=				kwargs.pop("""use_pretrained_backbone"""			,     config.use_pretrained_backbone   )
									__lowercase					=				kwargs.pop("""out_indices"""			,     config.out_indices   )
									__lowercase					=				TimmBackboneConfig(
									    backbone=UpperCAmelCase__			,     num_channels=UpperCAmelCase__			,     features_only=UpperCAmelCase__			,     use_pretrained_backbone=UpperCAmelCase__			,     out_indices=UpperCAmelCase__			,     )
									return super()._from_config(UpperCAmelCase__			,     **UpperCAmelCase__   )





			def 		snake_case__			(				self	:       str			,     lowercase	:       int   )						->					List[str]:
									"""simple docstring"""







									pass







			def 		snake_case__			(				self	:       List[Any]			,     lowercase	:       str			,     lowercase	:       int=None			,     lowercase	:       Union[str, Any]=None			,     lowercase	:       Any=None			,     **lowercase	:       List[str]   )						->					Union[BackboneOutput, Tuple[Tensor, ...]]:
									"""simple docstring"""







									__lowercase					=				return_dict if return_dict is not None else self.config.use_return_dict
									__lowercase					=				(
									    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
									)
									__lowercase					=				output_attentions if output_attentions is not None else self.config.output_attentions

									if output_attentions:
															raise ValueError("""Cannot output attentions for timm backbones at the moment"""   )

									if output_hidden_states:
															# We modify the return layers to include all the stages of the backbone
															__lowercase					=				self._all_layers
															__lowercase					=				self._backbone(UpperCAmelCase__			,     **UpperCAmelCase__   )
															__lowercase					=				self._return_layers
															__lowercase					=				tuple(hidden_states[i] for i in self.out_indices   )
									else:
															__lowercase					=				self._backbone(UpperCAmelCase__			,     **UpperCAmelCase__   )
															__lowercase					=				None

									__lowercase					=				tuple(UpperCAmelCase__   )
									__lowercase					=				tuple(UpperCAmelCase__   ) if hidden_states is not None else None

									if not return_dict:
															__lowercase					=				(feature_maps,)
															if output_hidden_states:
																					__lowercase					=				output + (hidden_states,)
															return output

									return BackboneOutput(feature_maps=UpperCAmelCase__			,     hidden_states=UpperCAmelCase__			,     attentions=UpperCAmelCase__   )










import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin
@require_phonemizer
class 			_lowerCAmelCase   ( _UpperCAmelCase    ,					unittest.TestCase			):






			"""simple docstring"""





			lowercase__      :  int      =			WavaVecaPhonemeCTCTokenizer
			lowercase__      :  Optional[int]      =			False





			def 		snake_case__			(				self	:       str   )						->					int:
									"""simple docstring"""







									super().setUp()

									__lowercase					=				(
									    """<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː """
									    """ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː """
									    """ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 """
									    """oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ """
									    """pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ """
									    """yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ """
									    """əʊ S ɡʲ onɡ2 u\" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ """
									    """ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ """
									    """ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ """
									    """uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ """
									    """ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ """
									    """ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ """
									    """ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4"""
									).split(""" """   )
									__lowercase					=				dict(zip(lowercase			,     range(len(lowercase   )   )   )   )

									__lowercase					=				{"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

									__lowercase					=				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(lowercase   ) + """\n"""   )





			def 		snake_case__			(				self	:       List[Any]			,     lowercase	:       Optional[Any]			,     lowercase	:       List[str]=False			,     lowercase	:       List[str]=20			,     lowercase	:       str=5   )						->					Tuple[str, list]:
									"""simple docstring"""







									__lowercase					=				[(i, tokenizer.decode([i]			,     clean_up_tokenization_spaces=lowercase   )) for i in range(len(lowercase   )   )]
									__lowercase					=				list(filter(lambda lowercase   : [t[0]] == tokenizer.encode(t[1]			,     do_phonemize=lowercase   )			,     lowercase   )   )
									if max_length is not None and len(lowercase   ) > max_length:
															__lowercase					=				toks[:max_length]
									if min_length is not None and len(lowercase   ) < min_length and len(lowercase   ) > 0:
															while len(lowercase   ) < min_length:
																					__lowercase					=				toks + toks
        # toks_str = [t[1] for t in toks]
									__lowercase					=				[t[0] for t in toks]

									# Ensure consistency
									__lowercase					=				tokenizer.decode(lowercase			,     clean_up_tokenization_spaces=lowercase   )
									if " " not in output_txt and len(lowercase   ) > 1:
															__lowercase					=				(
															    tokenizer.decode([toks_ids[0]]			,     clean_up_tokenization_spaces=lowercase   )
															    + """ """
															    + tokenizer.decode(toks_ids[1:]			,     clean_up_tokenization_spaces=lowercase   )
															)
									if with_prefix_space:
															__lowercase					=				""" """ + output_txt
									__lowercase					=				tokenizer.encode(lowercase			,     add_special_tokens=lowercase   )
									return output_txt, output_ids





			def 		snake_case__			(				self	:       Tuple			,     **lowercase	:       int   )						->					Union[str, Any]:
									"""simple docstring"""







									kwargs.update(self.special_tokens_map   )
									return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname			,     **lowercase   )





			def 		snake_case__			(				self	:       Any   )						->					List[Any]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )

									# check adding a single token
									tokenizer.add_tokens("""xxx"""   )
									__lowercase					=				tokenizer("""m xxx ɪ"""			,     do_phonemize=lowercase   ).input_ids
									self.assertEqual(lowercase			,     [13, 392, 17]   )  # xxx should be last token

									tokenizer.add_tokens(["""aaa""", """bbb""", """ccc"""]   )
									__lowercase					=				tokenizer("""m aaa ɪ ccc"""			,     do_phonemize=lowercase   ).input_ids
									self.assertEqual(lowercase			,     [13, 393, 17, 395]   )  # aaa and ccc should be after xxx and 2 after aaa

									__lowercase					=				tokenizer("""maɪ c"""			,     do_phonemize=lowercase   ).input_ids
									self.assertEqual(lowercase			,     [3, 200]   )  # mai should be <unk> (=3)





			def 		snake_case__			(				self	:       int   )						->					Tuple:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )
									self.assertEqual(lowercase			,     """h ə l oʊ h aʊ ɑːɹ j uː"""   )





			def 		snake_case__			(				self	:       List[Any]   )						->					Optional[int]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )
									self.assertEqual(tokenizer(lowercase   ).input_ids			,     tokenizer(lowercase			,     do_phonemize=lowercase   ).input_ids   )





			def 		snake_case__			(				self	:       Union[str, Any]   )						->					Optional[int]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )
									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )

									__lowercase					=				tokenizer.decode(tokenizer(lowercase   ).input_ids   )

									self.assertEqual(lowercase			,     lowercase   )





			def 		snake_case__			(				self	:       str   )						->					List[str]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )

									__lowercase					=				[
									    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
									    [24, 22, 5, 24, 22, 5, 77],
									]
									__lowercase					=				tokenizer.decode(sample_ids[0]   )
									__lowercase					=				tokenizer.batch_decode(lowercase   )
									self.assertEqual(lowercase			,     batch_tokens[0]   )
									self.assertEqual(lowercase			,     ["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]   )





			def 		snake_case__			(				self	:       int   )						->					Optional[Any]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )
									self.assertEqual(lowercase			,     """h ə l oʊ | h aʊ | ɑːɹ | j uː |"""   )





			def 		snake_case__			(				self	:       Union[str, Any]   )						->					Any:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )
									self.assertEqual(tokenizer(lowercase   ).input_ids			,     tokenizer(lowercase			,     do_phonemize=lowercase   ).input_ids   )





			def 		snake_case__			(				self	:       List[Any]   )						->					Tuple:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									# fmt: off
									__lowercase					=				[
									    [11, 5, 15, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 15, 8, tokenizer.word_delimiter_token_id, 98],
									    [tokenizer.word_delimiter_token_id, 24, 22, tokenizer.word_delimiter_token_id, 5, 24, 22, 5, 77],
									]
									# fmt: on

									# decode with word_del_token filter
									__lowercase					=				tokenizer.decode(sample_ids[0]   )
									__lowercase					=				tokenizer.batch_decode(lowercase   )
									self.assertEqual(lowercase			,     batch_tokens[0]   )
									self.assertEqual(lowercase			,     ["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]   )

									# decode with no word_del_token filter
									__lowercase					=				tokenizer.decode(sample_ids[0]			,     filter_word_delimiter_token=lowercase   )
									__lowercase					=				tokenizer.batch_decode(lowercase			,     filter_word_delimiter_token=lowercase   )
									self.assertEqual(lowercase			,     batch_tokens[0]   )
									self.assertEqual(lowercase			,     ["""k s ɾ | ɾ l | ɭʲ""", """| j ð | s j ð s oːɹ"""]   )





			def 		snake_case__			(				self	:       int   )						->					str:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )

									__lowercase					=				tokenizer.decode(tokenizer(lowercase   ).input_ids			,     filter_word_delimiter_token=lowercase   )

									self.assertEqual(lowercase			,     lowercase   )





			def 		snake_case__			(				self	:       Optional[int]   )						->					Any:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									__lowercase					=				"""Hello how are you"""
									__lowercase					=				tokenizer.phonemize(lowercase			,     phonemizer_lang="""en-us"""   )

									__lowercase					=				tokenizer.decode(tokenizer(lowercase   ).input_ids			,     filter_word_delimiter_token=lowercase   )

									self.assertEqual(""" """.join([p.strip() for p in phonemes.split(""" |"""   )]   ).strip()			,     lowercase   )





			def 		snake_case__			(				self	:       str   )						->					List[str]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained(
									    """facebook/wav2vec2-lv-60-espeak-cv-ft"""			,     word_delimiter_token=lowercase   )
									__lowercase					=				"""Hello how are you"""

									__lowercase					=				tokenizer(lowercase			,     phonemizer_lang="""en-us"""   ).input_ids
									__lowercase					=				tokenizer(lowercase			,     phonemizer_lang="""fr-fr"""   ).input_ids

									self.assertNotEqual(lowercase			,     lowercase   )

									__lowercase					=				tokenizer.decode(lowercase   )
									__lowercase					=				tokenizer.decode(lowercase   )

									self.assertEqual(lowercase			,     """h ə l oʊ h aʊ ɑːɹ j uː"""   )
									self.assertEqual(lowercase			,     """ɛ l o h aʊ a ʁ j u"""   )





			def 		snake_case__			(				self	:       int   )						->					int:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )
									__lowercase					=				"""Hello how Are you"""
									__lowercase					=				"""hello how are you"""

									__lowercase					=				tokenizer(lowercase   ).input_ids
									__lowercase					=				tokenizer(lowercase   ).input_ids

									self.assertEqual(lowercase			,     lowercase   )





			def 		snake_case__			(				self	:       int   )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )
									tokenizer.add_tokens(["""!""", """?"""]   )
									tokenizer.add_special_tokens({"""cls_token""": """$$$"""}   )

									# fmt: off
									__lowercase					=				[
									    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 392, 392, 393, 392, 392, 393, 394, 394],
									    [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 394, 394],
									]
									# fmt: on

									__lowercase					=				tokenizer.batch_decode(lowercase   )
									self.assertEqual(lowercase			,     ["""k s ɾ ɾ l ɭʲ!?!? $$$""", """j ð s j ð s oːɹ $$$"""]   )





			@staticmethod
			def 		snake_case__			(				lowercase	:       List[str]			,     lowercase	:       Optional[int]   )						->					List[Any]:
									"""simple docstring"""







									__lowercase					=				[d[key] for d in offsets]
									return retrieved_list





			def 		snake_case__			(				self	:       str   )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase					=				self.get_tokenizer(word_delimiter_token="""|"""   )
									tokenizer.add_tokens("""|"""   )

									# fmt: off
									# ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
									__lowercase					=				[11, 5, 5, 5, 15, 15, tokenizer.pad_token_id, 15, 15, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 15, 8, 8, 8, tokenizer.word_delimiter_token_id, 98]
									# fmt: on

									__lowercase					=				tokenizer.decode(lowercase			,     output_char_offsets=lowercase			,     filter_word_delimiter_token=lowercase   )
									# check Wav2Vec2CTCTokenizerOutput keys for char
									self.assertEqual(len(outputs.keys()   )			,     2   )
									self.assertTrue("""text""" in outputs   )
									self.assertTrue("""char_offsets""" in outputs   )
									self.assertTrue(isinstance(lowercase			,     lowercase   )   )

									# check that order of chars is correct and identical for both outputs
									self.assertEqual(""" """.join(self.get_from_offsets(outputs["""char_offsets"""]			,     """char"""   )   )			,     outputs.text   )
									self.assertListEqual(
									    self.get_from_offsets(outputs["""char_offsets"""]			,     """char"""   )			,     ["""k""", """s""", """ɾ""", """ɾ""", """|""", """ɾ""", """l""", """|""", """ɭʲ"""]   )

									# check that offsets are actually correct for char
									# 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
									# 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
									self.assertListEqual(
									    self.get_from_offsets(outputs["""char_offsets"""]			,     """start_offset"""   )			,     [0, 1, 4, 7, 9, 11, 12, 15, 16]   )
									self.assertListEqual(
									    self.get_from_offsets(outputs["""char_offsets"""]			,     """end_offset"""   )			,     [1, 4, 6, 9, 10, 12, 15, 16, 17]   )





			def 		snake_case__			(				self	:       List[Any]   )						->					Dict:
									"""simple docstring"""







									__lowercase					=				self.get_tokenizer(word_delimiter_token="""|"""   )

									def check_list_tuples_equal(lowercase	:       List[str]			,     lowercase	:       Dict   ):
															self.assertTrue(isinstance(lowercase			,     lowercase   )   )
															self.assertTrue(isinstance(outputs_list[0]			,     lowercase   )   )

															# transform list to ModelOutput
															__lowercase					=				WavaVecaPhonemeCTCTokenizerOutput(
															    {k: [d[k] for d in outputs_list] for k in outputs_list[0]}   )

															self.assertListEqual(outputs_batch["""text"""]			,     outputs_batch_a["""text"""]   )

															def recursive_check(lowercase	:       List[Any]			,     lowercase	:       Optional[int]   ):
																					if isinstance(lowercase			,     lowercase   ):
																											[recursive_check(lowercase			,     lowercase   ) for la, la in zip(lowercase			,     lowercase   )]
																					self.assertEqual(lowercase			,     lowercase   )

															if "char_offsets" in outputs_batch:
																					recursive_check(outputs_batch["""char_offsets"""]			,     outputs_batch_a["""char_offsets"""]   )

        # fmt: off
									__lowercase					=				[
									    [11, 5, 15, tokenizer.pad_token_id, 15, 4, 8, 98, 32, 32, 32, 32, 4, 33, tokenizer.word_delimiter_token_id, 32, 32, 33, 34, 34],
									    [24, 22, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 24, 22, 22, 22, 4, 5, 77, tokenizer.pad_token_id, 22, 22, 4, 34, 34, 34, 34],
									]
									# fmt: on

									# We assume that `decode` works as expected. All we will check now is
									# the output type is correct and the output is identical to `decode`

									# char
									__lowercase					=				tokenizer.batch_decode(lowercase			,     output_char_offsets=lowercase   )
									__lowercase					=				[tokenizer.decode(lowercase			,     output_char_offsets=lowercase   ) for ids in sample_ids]
									check_list_tuples_equal(lowercase			,     lowercase   )





			@unittest.skip("""Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes"""   )
			def 		snake_case__			(				self	:       List[Any]   )						->					int:
									"""simple docstring"""







									pass





			@unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"""   )
			def 		snake_case__			(				self	:       List[str]   )						->					List[str]:
									"""simple docstring"""







									pass





			@unittest.skip("""encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency"""   )
			def 		snake_case__			(				self	:       Optional[Any]   )						->					int:
									"""simple docstring"""







									pass





			@unittest.skip("""Wav2Vec2PhonemeModel has no max model length => no testing"""   )
			def 		snake_case__			(				self	:       str   )						->					int:
									"""simple docstring"""







									pass





			def 		snake_case__			(				self	:       Any   )						->					int:
									"""simple docstring"""







									__lowercase					=				self.get_tokenizers(do_lower_case=lowercase   )
									for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																					__lowercase					=				tokenizer.vocab_size
																					__lowercase					=				len(lowercase   )

																					self.assertNotEqual(lowercase			,     0   )

																					# We usually have added tokens from the start in tests because our vocab fixtures are
																					# smaller than the original vocabs - let's not assert this
																					# self.assertEqual(vocab_size, all_size)

																					__lowercase					=				["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
																					__lowercase					=				tokenizer.add_tokens(lowercase   )
																					__lowercase					=				tokenizer.vocab_size
																					__lowercase					=				len(lowercase   )

																					self.assertNotEqual(lowercase			,     0   )
																					self.assertEqual(lowercase			,     lowercase   )
																					self.assertEqual(lowercase			,     len(lowercase   )   )
																					self.assertEqual(lowercase			,     all_size + len(lowercase   )   )

																					__lowercase					=				tokenizer.encode("""aaaaa bbbbbb low cccccccccdddddddd l"""			,     add_special_tokens=lowercase   )

																					self.assertGreaterEqual(len(lowercase   )			,     4   )
																					self.assertGreater(tokens[0]			,     tokenizer.vocab_size - 1   )
																					self.assertGreater(tokens[-3]			,     tokenizer.vocab_size - 1   )

																					__lowercase					=				{"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
																					__lowercase					=				tokenizer.add_special_tokens(lowercase   )
																					__lowercase					=				tokenizer.vocab_size
																					__lowercase					=				len(lowercase   )

																					self.assertNotEqual(lowercase			,     0   )
																					self.assertEqual(lowercase			,     lowercase   )
																					self.assertEqual(lowercase			,     len(lowercase   )   )
																					self.assertEqual(lowercase			,     all_size_a + len(lowercase   )   )

																					__lowercase					=				tokenizer.encode(
																					    """>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l"""			,     add_special_tokens=lowercase   )

																					self.assertGreaterEqual(len(lowercase   )			,     6   )
																					self.assertGreater(tokens[0]			,     tokenizer.vocab_size - 1   )
																					self.assertGreater(tokens[0]			,     tokens[1]   )
																					self.assertGreater(tokens[-3]			,     tokenizer.vocab_size - 1   )
																					self.assertGreater(tokens[-3]			,     tokens[-4]   )
																					self.assertEqual(tokens[0]			,     tokenizer.eos_token_id   )
																					self.assertEqual(tokens[-3]			,     tokenizer.pad_token_id   )





			@unittest.skip("""The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode."""   )
			def 		snake_case__			(				self	:       str   )						->					int:
									"""simple docstring"""







									pass





			@unittest.skip("""The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode."""   )
			def 		snake_case__			(				self	:       List[Any]   )						->					Dict:
									"""simple docstring"""







									pass







			def 		snake_case__			(				self	:       Dict   )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase					=				self.get_tokenizers(fast=lowercase			,     do_lower_case=lowercase   )
									for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"   ):
																					__lowercase					=				["""ð""", """ɪ""", """s""", """ɪ""", """z""", """ɐ""", """t""", """ɛ""", """k""", """s""", """t"""]
																					__lowercase					=				tokenizer.convert_tokens_to_string(lowercase   )

																					self.assertIsInstance(output["""text"""]			,     lowercase   )





