


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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
	from .tokenization_albert import AlbertTokenizer
else:
	_lowercase      :      Tuple            =					None

_lowercase      :      Union[str, Any]            =					logging.get_logger(__name__)
_lowercase      :      Tuple            =					{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_lowercase      :      List[Any]            =					{
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json""",
    },
}

_lowercase      :      Any            =					{
    """albert-base-v1""": 512,
    """albert-large-v1""": 512,
    """albert-xlarge-v1""": 512,
    """albert-xxlarge-v1""": 512,
    """albert-base-v2""": 512,
    """albert-large-v2""": 512,
    """albert-xlarge-v2""": 512,
    """albert-xxlarge-v2""": 512,
}

_lowercase      :      Dict            =					"""▁"""






class 	UpperCamelCase__(       lowerCAmelCase	):
				__magic_name__    :				Optional[int]  		=	VOCAB_FILES_NAMES
				__magic_name__    :				Optional[int]  		=	PRETRAINED_VOCAB_FILES_MAP
				__magic_name__    :				Any  		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__magic_name__    :				str  		=	AlbertTokenizer




				def __init__(		self      :			Union[str, Any]				,   lowerCAmelCase      :			Tuple=None				,   lowerCAmelCase      :			Tuple=None				,   lowerCAmelCase      :			List[str]=True				,   lowerCAmelCase      :			Tuple=True				,   lowerCAmelCase      :			List[Any]=False				,   lowerCAmelCase      :			Any="[CLS]"				,   lowerCAmelCase      :			int="[SEP]"				,   lowerCAmelCase      :			Any="<unk>"				,   lowerCAmelCase      :			List[str]="[SEP]"				,   lowerCAmelCase      :			Dict="<pad>"				,   lowerCAmelCase      :			Tuple="[CLS]"				,   lowerCAmelCase      :			List[Any]="[MASK]"				,   **lowerCAmelCase      :			Optional[int]				,   )->					List[Any]:

										"""simple docstring"""




										UpperCAmelCase					    =     (
										    AddedToken(lowerCAmelCase				,   lstrip=lowerCAmelCase				,   rstrip=lowerCAmelCase				,   normalized=lowerCAmelCase				)
										    if isinstance(lowerCAmelCase				,   lowerCAmelCase				)
										    else mask_token
										)

										super().__init__(
										    lowerCAmelCase				,   tokenizer_file=lowerCAmelCase				,   do_lower_case=lowerCAmelCase				,   remove_space=lowerCAmelCase				,   keep_accents=lowerCAmelCase				,   bos_token=lowerCAmelCase				,   eos_token=lowerCAmelCase				,   unk_token=lowerCAmelCase				,   sep_token=lowerCAmelCase				,   pad_token=lowerCAmelCase				,   cls_token=lowerCAmelCase				,   mask_token=lowerCAmelCase				,   **lowerCAmelCase				,   )

										UpperCAmelCase					    =     do_lower_case
										UpperCAmelCase					    =     remove_space
										UpperCAmelCase					    =     keep_accents
										UpperCAmelCase					    =     vocab_file
										UpperCAmelCase					    =     False if not self.vocab_file else True




				def 					a__(		self      :			List[str]				,   lowerCAmelCase      :			List[int]				,   lowerCAmelCase      :			Optional[List[int]] = None				)->					List[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     [self.sep_token_id]
										UpperCAmelCase					    =     [self.cls_token_id]
										if token_ids_a is None:
																return cls + token_ids_a + sep
										return cls + token_ids_a + sep + token_ids_a + sep




				def 					a__(		self      :			List[str]				,   lowerCAmelCase      :			List[int]				,   lowerCAmelCase      :			Optional[List[int]] = None				)->					List[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     [self.sep_token_id]
										UpperCAmelCase					    =     [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				) * [0] + len(token_ids_a + sep				) * [1]





				def 					a__(		self      :			str				,   lowerCAmelCase      :			str				,   lowerCAmelCase      :			Optional[str] = None				)->					Tuple[str]:

										"""simple docstring"""




										if not self.can_save_slow_tokenizer:
																raise ValueError(
																    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
																    '''tokenizer.'''				)

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

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

										return (out_vocab_file,)









'''simple docstring'''



# limitations under the License.

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from .pipelines import DiffusionPipeline, ImagePipelineOutput  # noqa: F401
from .utils import deprecate


deprecate(
    """pipelines_utils""",
    """0.22.0""",
    """Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.""",
    standard_warn=False,
    stacklevel=3,
)





