"""simple docstring"""







import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
	import jieba

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


_a  :  Tuple=				logging.get_logger(__name__)

_a  :  List[Any]=				{"vocab_file": "vocab.txt"}

_a  :  Optional[int]=				{
    "vocab_file": {
        "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt",
    },
}

_a  :  Union[str, Any]=				{
    "openbmb/cpm-ant-10b": 1_024,
}
def 						__UpperCAmelCase       (					UpperCAmelCase_					:       Tuple						)							->    List[Any]:

	'''simple docstring'''





	__snake_case    :							Tuple   	=				collections.OrderedDict()
	with open(UpperCAmelCase_    ,							'r'    ,							encoding='utf-8'						) as reader:
		__snake_case    :							Any   	=				reader.readlines()
	for index, token in enumerate(UpperCAmelCase_						):
		__snake_case    :							int   	=				token.rstrip('\n'						)
		__snake_case    :							Tuple   	=				index
	return vocab

class 	UpperCamelCase    (					__a		):



				def __init__(self       :   List[Any]			,						_A       :   List[Any]			,						_A       :   int="<unk>"			,						_A       :   Optional[int]=2_00)					->			Any:
					__snake_case    :							int   	=				vocab
					__snake_case    :							Any   	=				unk_token
					__snake_case    :							List[str]   	=				max_input_chars_per_word






				def       _lowercase  (self       :   Optional[int]			,						_A       :   Tuple)					->			str:
					__snake_case    :							str   	=				list(A__)
					if len(A__) > self.max_input_chars_per_word:
						return [self.unk_token]

					__snake_case    :							Optional[Any]   	=				0
					__snake_case    :							str   	=				[]
					while start < len(A__):
						__snake_case    :							Optional[Any]   	=				len(A__)
						__snake_case    :							Optional[Any]   	=				None
						while start < end:
							__snake_case    :							Dict   	=				''.join(chars[start:end])
							if substr in self.vocab:
								__snake_case    :							str   	=				substr
								break
							end -= 1
						if cur_substr is None:
							sub_tokens.append(self.unk_token)
							start += 1
						else:
							sub_tokens.append(A__)
							__snake_case    :							Optional[Any]   	=				end

					return sub_tokens







class 	UpperCamelCase    (					__a		):
				UpperCAmelCase       :   Dict					=	VOCAB_FILES_NAMES
				UpperCAmelCase       :   str					=	PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase       :   Union[str, Any]					=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase       :   Union[str, Any]					=	["""input_ids""", """attention_mask"""]
				UpperCAmelCase       :   List[Any]					=	False



				def __init__(self       :   List[str]			,						_A       :   List[Any]			,						_A       :   Union[str, Any]="<d>"			,						_A       :   Any="</d>"			,						_A       :   int="<s>"			,						_A       :   Union[str, Any]="</s>"			,						_A       :   Any="<pad>"			,						_A       :   Union[str, Any]="<unk>"			,						_A       :   int="</n>"			,						_A       :   Any="</_>"			,						_A       :   str="left"			,						**_A       :   Tuple			,						)					->			Dict:
					requires_backends(self			,						['jieba'])
					super().__init__(
					    bod_token=A__			,						eod_token=A__			,						bos_token=A__			,						eos_token=A__			,						pad_token=A__			,						unk_token=A__			,						line_token=A__			,						space_token=A__			,						padding_side=A__			,						**A__			,						)
					__snake_case    :							Tuple   	=				bod_token
					__snake_case    :							Optional[int]   	=				eod_token
					__snake_case    :							Any   	=				load_vocab(A__)
					__snake_case    :							Union[str, Any]   	=				self.encoder[space_token]
					__snake_case    :							str   	=				self.encoder[line_token]

					del self.encoder[space_token]
					del self.encoder[line_token]

					__snake_case    :							int   	=				collections.OrderedDict(sorted(self.encoder.items()			,						key=lambda _A: x[1]))
					__snake_case    :							List[Any]   	=				{v: k for k, v in self.encoder.items()}

					__snake_case    :							Tuple   	=				WordpieceTokenizer(vocab=self.encoder			,						unk_token=self.unk_token)



				@property
				def       _lowercase  (self       :   List[Any])					->			Any:
					return self.encoder[self.bod_token]



				@property
				def       _lowercase  (self       :   Optional[Any])					->			int:
					return self.encoder[self.eod_token]



				@property
				def       _lowercase  (self       :   int)					->			List[str]:
					return self.encoder["\n"]



				@property
				def       _lowercase  (self       :   Dict)					->			int:
					return len(self.encoder)



				def       _lowercase  (self       :   Dict)					->			int:
					return dict(self.encoder			,						**self.added_tokens_encoder)



				def       _lowercase  (self       :   List[str]			,						_A       :   Tuple)					->			List[Any]:
					__snake_case    :							List[Any]   	=				[]
					for x in jieba.cut(A__			,						cut_all=A__):
						output_tokens.extend(self.wordpiece_tokenizer.tokenize(A__))
					return output_tokens



				def       _lowercase  (self       :   Optional[int]			,						_A       :   List[Any]			,						**_A       :   Tuple)					->			Optional[Any]:
					__snake_case    :							Optional[int]   	=				[i for i in token_ids if i >= 0]
					__snake_case    :							str   	=				[
					    x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
					]
					return super()._decode(A__			,						**A__)



				def       _lowercase  (self       :   Optional[int]			,						_A       :   List[str])					->			Dict:
					return token in self.encoder



				def       _lowercase  (self       :   List[Any]			,						_A       :   Any)					->			str:
					return "".join(A__)



				def       _lowercase  (self       :   Dict			,						_A       :   List[Any])					->			int:
					return self.encoder.get(A__			,						self.encoder.get(self.unk_token))



				def       _lowercase  (self       :   int			,						_A       :   Dict)					->			int:
					return self.decoder.get(A__			,						self.unk_token)



				def       _lowercase  (self       :   int			,						_A       :   str			,						_A       :   Optional[int] = None)					->			Tuple[str]:
					if os.path.isdir(A__):
						__snake_case    :							Dict   	=				os.path.join(
						    A__			,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
					else:
						__snake_case    :							int   	=				(filename_prefix + '-' if filename_prefix else '') + save_directory
					__snake_case    :							List[Any]   	=				0
					if " " in self.encoder:
						__snake_case    :							int   	=				self.encoder[' ']
						del self.encoder[" "]
					if "\n" in self.encoder:
						__snake_case    :							List[Any]   	=				self.encoder['\n']
						del self.encoder["\n"]
					__snake_case    :							Optional[Any]   	=				collections.OrderedDict(sorted(self.encoder.items()			,						key=lambda _A: x[1]))
					with open(A__			,						'w'			,						encoding='utf-8') as writer:
						for token, token_index in self.encoder.items():
							if index != token_index:
								logger.warning(
								    f"Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."
								    ' Please check that the vocabulary is not corrupted!')
								__snake_case    :							Union[str, Any]   	=				token_index
							writer.write(token + '\n')
							index += 1
					return (vocab_file,)



				def       _lowercase  (self       :   Optional[Any]			,						_A       :   Tuple			,						_A       :   int = None)					->			List[int]:
					if token_ids_a is None:
						return [self.bos_token_id] + token_ids_a
					return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a






				def       _lowercase  (self       :   List[str]			,						_A       :   Any			,						_A       :   Dict = None			,						_A       :   Optional[int] = False)					->			List[int]:

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

					if token_ids_a is not None:
						return [1] + ([0] * len(A__)) + [1] + ([0] * len(A__))
					return [1] + ([0] * len(A__))






"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_a  :  Any=				{"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_a  :  Union[str, Any]=				["SpeechEncoderDecoderModel"]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_a  :  Tuple=				["FlaxSpeechEncoderDecoderModel"]

if TYPE_CHECKING:
	from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
	import sys

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





