"""simple docstring"""



import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
				import onnxruntime as ort


_UpperCamelCase								=		logging.get_logger(__name__)

_UpperCamelCase								=		{
    '''tensor(bool)''': np.bool_,
    '''tensor(int8)''': np.inta,
    '''tensor(uint8)''': np.uinta,
    '''tensor(int16)''': np.intaa,
    '''tensor(uint16)''': np.uintaa,
    '''tensor(int32)''': np.intaa,
    '''tensor(uint32)''': np.uintaa,
    '''tensor(int64)''': np.intaa,
    '''tensor(uint64)''': np.uintaa,
    '''tensor(float16)''': np.floataa,
    '''tensor(float)''': np.floataa,
    '''tensor(double)''': np.floataa,
}
class 						__UpperCAmelCase    :







			'''simple docstring'''





			def __init__(			self   ,      snake_case_=None   ,      **snake_case_							):







										'''simple docstring'''


										logger.info("""`diffusers.OnnxRuntimeModel` is experimental and might change in the future."""							)
										A__       :     List[str]								=			model
										A__       :     Optional[Any]								=			kwargs.get("""model_save_dir"""   ,      lowercase_							)
										A__       :     str								=			kwargs.get("""latest_model_name"""   ,      lowercase_							)





			def __call__(			self   ,      **snake_case_							):







										'''simple docstring'''


										A__       :     List[Any]								=			{k: np.array(lowercase_							) for k, v in kwargs.items()}
										return self.model.run(lowercase_   ,      lowercase_							)





			@staticmethod
			def 		lowerCamelCase					(			snake_case_   ,      snake_case_=None   ,      snake_case_=None							):







										'''simple docstring'''


										if provider is None:
																	logger.info("""No onnxruntime provider specified, using CPUExecutionProvider"""							)
																	A__       :     Optional[Any]								=			'''CPUExecutionProvider'''

										return ort.InferenceSession(lowercase_   ,      providers=[provider]   ,      sess_options=lowercase_							)





			def 		lowerCamelCase					(			self   ,      snake_case_   ,      snake_case_ = None   ,      **snake_case_							):







										'''simple docstring'''


										A__       :     Any								=			file_name if file_name is not None else ONNX_WEIGHTS_NAME

										A__       :     Tuple								=			self.model_save_dir.joinpath(self.latest_model_name							)
										A__       :     List[Any]								=			Path(lowercase_							).joinpath(lowercase_							)
										try:
																	shutil.copyfile(lowercase_   ,      lowercase_							)
										except shutil.SameFileError:
																	pass

										# copy external weights (for models >2GB)
										A__       :     Dict								=			self.model_save_dir.joinpath(lowercase_							)
										if src_path.exists():
																	A__       :     Union[str, Any]								=			Path(lowercase_							).joinpath(lowercase_							)
																	try:
																								shutil.copyfile(lowercase_   ,      lowercase_							)
																	except shutil.SameFileError:
																								pass





			def 		lowerCamelCase					(			self   ,      snake_case_   ,      **snake_case_   ,      ):







										'''simple docstring'''


										if os.path.isfile(lowercase_							):
																	logger.error(F'''Provided path ({save_directory}) should be a directory, not a file'''							)
																	return

										os.makedirs(lowercase_   ,      exist_ok=lowercase_							)

										# saving model weights/files
										self._save_pretrained(lowercase_   ,      **lowercase_							)





			@classmethod
			def 		lowerCamelCase					(			cls   ,      snake_case_   ,      snake_case_ = None   ,      snake_case_ = None   ,      snake_case_ = False   ,      snake_case_ = None   ,      snake_case_ = None   ,      snake_case_ = None   ,      snake_case_ = None   ,      **snake_case_   ,      ):







										'''simple docstring'''


										A__       :     Optional[Any]								=			file_name if file_name is not None else ONNX_WEIGHTS_NAME
										# load model from local directory
										if os.path.isdir(lowercase_							):
																	A__       :     str								=			OnnxRuntimeModel.load_model(
																	    os.path.join(lowercase_   ,      lowercase_							)   ,      provider=lowercase_   ,      sess_options=lowercase_							)
																	A__       :     Any								=			Path(lowercase_							)
										# load model from hub
										else:
																	# download model
																	A__       :     Optional[Any]								=			hf_hub_download(
																	    repo_id=lowercase_   ,      filename=lowercase_   ,      use_auth_token=lowercase_   ,      revision=lowercase_   ,      cache_dir=lowercase_   ,      force_download=lowercase_   ,      )
																	A__       :     str								=			Path(lowercase_							).parent
																	A__       :     Union[str, Any]								=			Path(lowercase_							).name
																	A__       :     Optional[Any]								=			OnnxRuntimeModel.load_model(lowercase_   ,      provider=lowercase_   ,      sess_options=lowercase_							)
										return cls(model=lowercase_   ,      **lowercase_							)





			@classmethod
			def 		lowerCamelCase					(			cls   ,      snake_case_   ,      snake_case_ = True   ,      snake_case_ = None   ,      snake_case_ = None   ,      **snake_case_   ,      ):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			None
										if len(str(lowercase_							).split("""@"""							)							) == 2:
																	A__       :     str								=			model_id.split("""@"""							)

										return cls._from_pretrained(
										    model_id=lowercase_   ,      revision=lowercase_   ,      cache_dir=lowercase_   ,      force_download=lowercase_   ,      use_auth_token=lowercase_   ,      **lowercase_   ,      )








"""simple docstring"""





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:
							__UpperCamelCase    : Any				 =						None

__UpperCamelCase    : Optional[int]				 =						logging.get_logger(__name__)
__UpperCamelCase    : List[Any]				 =						{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCamelCase    : str				 =						{
    '''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''',
    },
}

__UpperCamelCase    : Any				 =						{
    '''albert-base-v1''': 5_1_2,
    '''albert-large-v1''': 5_1_2,
    '''albert-xlarge-v1''': 5_1_2,
    '''albert-xxlarge-v1''': 5_1_2,
    '''albert-base-v2''': 5_1_2,
    '''albert-large-v2''': 5_1_2,
    '''albert-xlarge-v2''': 5_1_2,
    '''albert-xxlarge-v2''': 5_1_2,
}

__UpperCamelCase    : Union[str, Any]				 =						'''▁'''







class 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					lowercase__												=			VOCAB_FILES_NAMES
					lowercase__												=			PRETRAINED_VOCAB_FILES_MAP
					lowercase__												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__												=			AlbertTokenizer







					def __init__(			self     :							Union[str, Any]  ,lowercase_     :							List[str]=None  ,lowercase_     :							Union[str, Any]=None  ,lowercase_     :							str=True  ,lowercase_     :							Optional[Any]=True  ,lowercase_     :							str=False  ,lowercase_     :							Tuple="[CLS]"  ,lowercase_     :							Optional[int]="[SEP]"  ,lowercase_     :							Optional[Any]="<unk>"  ,lowercase_     :							List[Any]="[SEP]"  ,lowercase_     :							Optional[int]="<pad>"  ,lowercase_     :							List[Any]="[CLS]"  ,lowercase_     :							Optional[int]="[MASK]"  ,**lowercase_     :							Optional[int]  ,):
						# Mask token behave like a normal word, i.e. include the space before it and
						# is included in the raw text, there should be a match in a non-normalized sentence.
						lowerCAmelCase__      :		Optional[Any]    							=      (
						    AddedToken(lowercase_  ,lstrip=lowercase_  ,rstrip=lowercase_  ,normalized=lowercase_						)
						    if isinstance(lowercase_  ,lowercase_						)
						    else mask_token
						)

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

						lowerCAmelCase__      :		List[Any]    							=      do_lower_case
						lowerCAmelCase__      :		str    							=      remove_space
						lowerCAmelCase__      :		Optional[int]    							=      keep_accents
						lowerCAmelCase__      :		Dict    							=      vocab_file
						lowerCAmelCase__      :		Optional[int]    							=      False if not self.vocab_file else True







					def 			__lowerCAmelCase					(			self     :							Dict  ,lowercase_     :							List[int]  ,lowercase_     :							Optional[List[int]] = None						):
						lowerCAmelCase__      :		List[Any]    							=      [self.sep_token_id]
						lowerCAmelCase__      :		Dict    							=      [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 			__lowerCAmelCase					(			self     :							Union[str, Any]  ,lowercase_     :							List[int]  ,lowercase_     :							Optional[List[int]] = None						):
						lowerCAmelCase__      :		List[str]    							=      [self.sep_token_id]
						lowerCAmelCase__      :		List[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						) * [0] + len(token_ids_a + sep						) * [1]







					def 			__lowerCAmelCase					(			self     :							Optional[int]  ,lowercase_     :							str  ,lowercase_     :							Optional[str] = None						):
						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(lowercase_						):
							logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
							return
						lowerCAmelCase__      :		Union[str, Any]    							=      os.path.join(
						    lowercase_  ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

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

						return (out_vocab_file,)




