'''simple docstring'''





import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase_	:		Tuple			=     logging.get_logger(__name__)

lowerCAmelCase_	:		Optional[int]			=     {
    """vocab_file""": """vocab.txt""",
    """merges_file""": """bpe.codes""",
}

lowerCAmelCase_	:		Dict			=     {
    """vocab_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt""",
    },
    """merges_file""": {
        """vinai/phobert-base""": """https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes""",
        """vinai/phobert-large""": """https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes""",
    },
}

lowerCAmelCase_	:		Optional[Any]			=     {
    """vinai/phobert-base""": 256,
    """vinai/phobert-large""": 256,
}
def 						__A							(     UpperCAmelCase					)     ->			Optional[int]:




						'''simple docstring'''
						_UpperCamelCase			:			List[Any]   			=						set()
						_UpperCamelCase			:			List[Any]   			=						word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)					)
												_UpperCamelCase			:			int   			=						char

						_UpperCamelCase			:			Optional[Any]   			=						set(UpperCAmelCase					)
						return pairs






class 		SCREAMING_SNAKE_CASE     (					SCREAMING_SNAKE_CASE	):







				'''simple docstring'''
				UpperCAmelCase__							=							VOCAB_FILES_NAMES
				UpperCAmelCase__							=							PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase__							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES





				def __init__(						self					:						int       ,		lowercase__					:						Optional[int]       ,		lowercase__					:						int       ,		lowercase__					:						int="<s>"       ,		lowercase__					:						Optional[int]="</s>"       ,		lowercase__					:						Any="</s>"       ,		lowercase__					:						Tuple="<s>"       ,		lowercase__					:						Optional[Any]="<unk>"       ,		lowercase__					:						List[Any]="<pad>"       ,		lowercase__					:						List[Any]="<mask>"       ,		**lowercase__					:						List[str]       ,		)							->Dict:


										'''simple docstring'''




										super().__init__(
										    bos_token=lowercase__       ,		eos_token=lowercase__       ,		unk_token=lowercase__       ,		sep_token=lowercase__       ,		cls_token=lowercase__       ,		pad_token=lowercase__       ,		mask_token=lowercase__       ,		**lowercase__       ,		)

										_UpperCamelCase			:			Dict   			=						vocab_file
										_UpperCamelCase			:			Optional[int]   			=						merges_file

										_UpperCamelCase			:			Any   			=						{}
										_UpperCamelCase			:			Union[str, Any]   			=						0
										_UpperCamelCase			:			Any   			=						1
										_UpperCamelCase			:			Dict   			=						2
										_UpperCamelCase			:			str   			=						3

										self.add_from_file(lowercase__					)

										_UpperCamelCase			:			Optional[Any]   			=						{v: k for k, v in self.encoder.items()}

										with open(lowercase__       ,		encoding="utf-8"					) as merges_handle:
																_UpperCamelCase			:			Any   			=						merges_handle.read().split("\n"					)[:-1]
										_UpperCamelCase			:			Union[str, Any]   			=						[tuple(merge.split()[:-1]					) for merge in merges]
										_UpperCamelCase			:			Any   			=						dict(zip(lowercase__       ,		range(len(lowercase__					)					)					)					)
										_UpperCamelCase			:			Dict   			=						{}





				def  snake_case__				(						self					:						List[Any]       ,		lowercase__					:						List[int]       ,		lowercase__					:						Optional[List[int]] = None					)							->List[int]:


										'''simple docstring'''




										if token_ids_a is None:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										_UpperCamelCase			:			str   			=						[self.cls_token_id]
										_UpperCamelCase			:			Optional[Any]   			=						[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep





				def  snake_case__				(						self					:						List[str]       ,		lowercase__					:						List[int]       ,		lowercase__					:						Optional[List[int]] = None       ,		lowercase__					:						bool = False					)							->List[int]:


										'''simple docstring'''




										if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=lowercase__       ,		token_ids_a=lowercase__       ,		already_has_special_tokens=lowercase__					)

										if token_ids_a is None:
																return [1] + ([0] * len(lowercase__					)) + [1]
										return [1] + ([0] * len(lowercase__					)) + [1, 1] + ([0] * len(lowercase__					)) + [1]





				def  snake_case__				(						self					:						Optional[Any]       ,		lowercase__					:						List[int]       ,		lowercase__					:						Optional[List[int]] = None					)							->List[int]:


										'''simple docstring'''




										_UpperCamelCase			:			Optional[Any]   			=						[self.sep_token_id]
										_UpperCamelCase			:			Any   			=						[self.cls_token_id]

										if token_ids_a is None:
																return len(cls + token_ids_a + sep					) * [0]
										return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]





				@property
				def  snake_case__				(						self					:						str					)							->Any:


										'''simple docstring'''




										return len(self.encoder					)





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


										'''simple docstring'''




										return dict(self.encoder       ,		**self.added_tokens_encoder					)





				def  snake_case__				(						self					:						Optional[Any]       ,		lowercase__					:						List[str]					)							->Optional[Any]:


										'''simple docstring'''




										if token in self.cache:
																return self.cache[token]
										_UpperCamelCase			:			List[str]   			=						tuple(lowercase__					)
										_UpperCamelCase			:			Any   			=						tuple(list(word[:-1]					) + [word[-1] + "</w>"]					)
										_UpperCamelCase			:			str   			=						get_pairs(lowercase__					)

										if not pairs:
																return token

										while True:
																_UpperCamelCase			:			Union[str, Any]   			=						min(lowercase__       ,		key=lambda lowercase__					: self.bpe_ranks.get(lowercase__       ,		float("inf"					)					)					)
																if bigram not in self.bpe_ranks:
																						break
																_UpperCamelCase			,       _UpperCamelCase			:			Union[str, Any]   			=						bigram
																_UpperCamelCase			:			int   			=						[]
																_UpperCamelCase			:			Optional[int]   			=						0
																while i < len(lowercase__					):
																						try:
																												_UpperCamelCase			:			Optional[int]   			=						word.index(lowercase__       ,		lowercase__					)
																						except ValueError:
																												new_word.extend(word[i:]					)
																												break
																						else:
																												new_word.extend(word[i:j]					)
																												_UpperCamelCase			:			Optional[Any]   			=						j

																						if word[i] == first and i < len(lowercase__					) - 1 and word[i + 1] == second:
																												new_word.append(first + second					)
																												i += 2
																						else:
																												new_word.append(word[i]					)
																												i += 1
																_UpperCamelCase			:			int   			=						tuple(lowercase__					)
																_UpperCamelCase			:			Dict   			=						new_word
																if len(lowercase__					) == 1:
																						break
																else:
																						_UpperCamelCase			:			str   			=						get_pairs(lowercase__					)
										_UpperCamelCase			:			Optional[Any]   			=						"@@ ".join(lowercase__					)
										_UpperCamelCase			:			Optional[int]   			=						word[:-4]
										_UpperCamelCase			:			List[str]   			=						word
										return word





				def  snake_case__				(						self					:						Optional[int]       ,		lowercase__					:						List[str]					)							->Optional[int]:


										'''simple docstring'''




										_UpperCamelCase			:			str   			=						[]

										_UpperCamelCase			:			List[Any]   			=						re.findall(r"\S+\n?"       ,		lowercase__					)

										for token in words:
																split_tokens.extend(list(self.bpe(lowercase__					).split(" "					)					)					)
										return split_tokens





				def  snake_case__				(						self					:						List[Any]       ,		lowercase__					:						Tuple					)							->Union[str, Any]:


										'''simple docstring'''




										return self.encoder.get(lowercase__       ,		self.encoder.get(self.unk_token					)					)





				def  snake_case__				(						self					:						Optional[Any]       ,		lowercase__					:						List[str]					)							->List[Any]:


										'''simple docstring'''




										return self.decoder.get(lowercase__       ,		self.unk_token					)





				def  snake_case__				(						self					:						List[str]       ,		lowercase__					:						List[Any]					)							->Dict:


										'''simple docstring'''




										_UpperCamelCase			:			int   			=						" ".join(lowercase__					).replace("@@ "       ,		""					).strip()
										return out_string





				def  snake_case__				(						self					:						Tuple       ,		lowercase__					:						str       ,		lowercase__					:						Optional[str] = None					)							->Tuple[str]:


										'''simple docstring'''




										if not os.path.isdir(lowercase__					):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
																return
										_UpperCamelCase			:			Any   			=						os.path.join(
										    lowercase__       ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
										_UpperCamelCase			:			Any   			=						os.path.join(
										    lowercase__       ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]					)

										if os.path.abspath(self.vocab_file					) != os.path.abspath(lowercase__					):
																copyfile(self.vocab_file       ,		lowercase__					)

										if os.path.abspath(self.merges_file					) != os.path.abspath(lowercase__					):
																copyfile(self.merges_file       ,		lowercase__					)

										return out_vocab_file, out_merge_file







				def  snake_case__				(						self					:						str       ,		lowercase__					:						str					)							->Optional[Any]:


										'''simple docstring'''




										if isinstance(lowercase__       ,		lowercase__					):
																try:
																						with open(lowercase__       ,		"r"       ,		encoding="utf-8"					) as fd:
																												self.add_from_file(lowercase__					)
																except FileNotFoundError as fnfe:
																						raise fnfe
																except UnicodeError:
																						raise Exception(f'''Incorrect encoding detected in {f}, please rebuild the dataset'''					)
																return

										_UpperCamelCase			:			Optional[int]   			=						f.readlines()
										for lineTmp in lines:
																_UpperCamelCase			:			Any   			=						lineTmp.strip()
																_UpperCamelCase			:			Dict   			=						line.rfind(" "					)
																if idx == -1:
																						raise ValueError("Incorrect dictionary format, expected '<token> <cnt>'"					)
																_UpperCamelCase			:			Optional[Any]   			=						line[:idx]
																_UpperCamelCase			:			Tuple   			=						len(self.encoder					)



'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_tf_available,
    is_torch_available,
)


lowerCAmelCase_	:		Any			=     {
    """configuration_speech_to_text""": ["""SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Speech2TextConfig"""],
    """processing_speech_to_text""": ["""Speech2TextProcessor"""],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		int			=     ["""Speech2TextTokenizer"""]

try:
			if not is_speech_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		Optional[Any]			=     ["""Speech2TextFeatureExtractor"""]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		Optional[int]			=     [
			    """TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """TFSpeech2TextForConditionalGeneration""",
			    """TFSpeech2TextModel""",
			    """TFSpeech2TextPreTrainedModel""",
			]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		str			=     [
			    """SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """Speech2TextForConditionalGeneration""",
			    """Speech2TextModel""",
			    """Speech2TextPreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
			from .processing_speech_to_text import SpeechaTextProcessor

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_speech_to_text import SpeechaTextTokenizer

			try:
						if not is_speech_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_speech_to_text import (
						    TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFSpeechaTextForConditionalGeneration,
						    TFSpeechaTextModel,
						    TFSpeechaTextPreTrainedModel,
						)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_speech_to_text import (
						    SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SpeechaTextForConditionalGeneration,
						    SpeechaTextModel,
						    SpeechaTextPreTrainedModel,
						)

else:
			import sys

			lowerCAmelCase_	:		Union[str, Any]			=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


