



"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase:  Tuple			     =				logging.get_logger(__name__)

UpperCAmelCase:  Any			     =				{
    """facebook/convnext-tiny-224""": """https://huggingface.co/facebook/convnext-tiny-224/resolve/main/config.json""",
    # See all ConvNeXT models at https://huggingface.co/models?filter=convnext
}





class   UpperCamelCase	(     snake_case					,   snake_case       ):




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       List[str]						       =  "convnext"






	def __init__(     self				,UpperCAmelCase_=3				,UpperCAmelCase_=4				,UpperCAmelCase_=4				,UpperCAmelCase_=None				,UpperCAmelCase_=None				,UpperCAmelCase_="gelu"				,UpperCAmelCase_=0.02				,UpperCAmelCase_=1E-12				,UpperCAmelCase_=1E-6				,UpperCAmelCase_=0.0				,UpperCAmelCase_=2_24				,UpperCAmelCase_=None				,UpperCAmelCase_=None				,**UpperCAmelCase_				,):
			super().__init__(**UpperCAmelCase_   )

			_lowercase				: str     =   num_channels
			_lowercase				: Dict     =   patch_size
			_lowercase				: Union[str, Any]     =   num_stages
			_lowercase				: Optional[int]     =   [96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
			_lowercase				: List[str]     =   [3, 3, 9, 3] if depths is None else depths
			_lowercase				: str     =   hidden_act
			_lowercase				: Union[str, Any]     =   initializer_range
			_lowercase				: List[str]     =   layer_norm_eps
			_lowercase				: Union[str, Any]     =   layer_scale_init_value
			_lowercase				: Optional[Any]     =   drop_path_rate
			_lowercase				: Optional[int]     =   image_size
			_lowercase				: Tuple     =   ["""stem"""] + [f"""stage{idx}""" for idx in range(1				,len(self.depths   ) + 1   )]
			_lowercase     ,  _lowercase				: Dict     =   get_aligned_output_features_output_indices(
			    out_features=UpperCAmelCase_				,out_indices=UpperCAmelCase_				,stage_names=self.stage_names   )







class   UpperCamelCase	(     snake_case       ):




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       str						       =  version.parse("1.11"       )






	@property
	def    lowerCamelCase__					(     self   ):
			return OrderedDict(
			    [
			        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
			    ]   )






	@property
	def    lowerCamelCase__					(     self   ):
			return 1E-5





'''simple docstring'''


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

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


if is_sentencepiece_available():
	from .tokenization_xglm import XGLMTokenizer
else:
	__SCREAMING_SNAKE_CASE						=      None


__SCREAMING_SNAKE_CASE						=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE						=      {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__SCREAMING_SNAKE_CASE						=      {
    "vocab_file": {
        "facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_file": {
        "facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json",
    },
}

__SCREAMING_SNAKE_CASE						=      {
    "facebook/xglm-564M": 2048,
}




class     __snake_case			(    _a	):
		a_          =					VOCAB_FILES_NAMES
		a_          =					PRETRAINED_VOCAB_FILES_MAP
		a_          =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a_          =					["input_ids", "attention_mask"]
		a_          =					XGLMTokenizer




		def __init__(  self					:str			,    _SCREAMING_SNAKE_CASE					:Dict=None			,    _SCREAMING_SNAKE_CASE					:List[str]=None			,    _SCREAMING_SNAKE_CASE					:Dict="<s>"			,    _SCREAMING_SNAKE_CASE					:Dict="</s>"			,    _SCREAMING_SNAKE_CASE					:List[Any]="</s>"			,    _SCREAMING_SNAKE_CASE					:Tuple="<s>"			,    _SCREAMING_SNAKE_CASE					:int="<unk>"			,    _SCREAMING_SNAKE_CASE					:List[str]="<pad>"			,    **_SCREAMING_SNAKE_CASE					:Optional[int]			,    )					->			Optional[int]:






								'''simple docstring'''






								UpperCamelCase_     :	Tuple					     =     7
								UpperCamelCase_     :	int					     =     [F"""<madeupword{i}>""" for i in range(self.num_madeup_words)]

								UpperCamelCase_     :	Optional[Any]					     =     kwargs.get("""additional_special_tokens"""			,    [])
								kwargs["additional_special_tokens"] += [
								    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    _SCREAMING_SNAKE_CASE			,    tokenizer_file=_SCREAMING_SNAKE_CASE			,    bos_token=_SCREAMING_SNAKE_CASE			,    eos_token=_SCREAMING_SNAKE_CASE			,    sep_token=_SCREAMING_SNAKE_CASE			,    cls_token=_SCREAMING_SNAKE_CASE			,    unk_token=_SCREAMING_SNAKE_CASE			,    pad_token=_SCREAMING_SNAKE_CASE			,    **_SCREAMING_SNAKE_CASE			,    )

								UpperCamelCase_     :	int					     =     vocab_file
								UpperCamelCase_     :	Any					     =     False if not self.vocab_file else True




		def 	_snake_case	(  self					:Dict			,    _SCREAMING_SNAKE_CASE					:List[int]			,    _SCREAMING_SNAKE_CASE					:Optional[List[int]] = None)					->			List[int]:






								'''simple docstring'''






								if token_ids_a is None:
														return [self.sep_token_id] + token_ids_a
								UpperCamelCase_     :	str					     =     [self.sep_token_id]
								return sep + token_ids_a + sep + sep + token_ids_a




		def 	_snake_case	(  self					:int			,    _SCREAMING_SNAKE_CASE					:List[int]			,    _SCREAMING_SNAKE_CASE					:Optional[List[int]] = None)					->			List[int]:






								'''simple docstring'''






								UpperCamelCase_     :	Optional[Any]					     =     [self.sep_token_id]

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





		def 	_snake_case	(  self					:List[Any]			,    _SCREAMING_SNAKE_CASE					:str			,    _SCREAMING_SNAKE_CASE					: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(_SCREAMING_SNAKE_CASE):
														logger.error(F"""Vocabulary path ({save_directory}) should be a directory.""")
														return
								UpperCamelCase_     :	Dict					     =     os.path.join(
								    _SCREAMING_SNAKE_CASE			,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])

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

								return (out_vocab_file,)




