




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

from tokenizers import processors

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


if is_sentencepiece_available():
   from .tokenization_mbart import MBartTokenizer
else:
   lowercase__				:      List[str]	   = None


lowercase__				:      Any	   = logging.get_logger(__name__)


lowercase__				:      List[str]	   = {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase__				:      int	   = {
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

lowercase__				:      int	   = {
    "facebook/mbart-large-en-ro": 1_024,
    "facebook/mbart-large-cc25": 1_024,
}

# fmt: off
lowercase__				:      Optional[int]	   = ["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN"]




class       a__	( UpperCamelCase__				):
     a		:      int		 =     VOCAB_FILES_NAMES
     a		:      Any		 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     a		:      Optional[Any]		 =     PRETRAINED_VOCAB_FILES_MAP
     a		:      Optional[Any]		 =     ["""input_ids""", """attention_mask"""]
     a		:      Dict		 =     MBartTokenizer

     a		:      List[int]		 =     []
     a		:      List[int]		 =     []







     def __init__(     self  ,		A=None  ,		A=None  ,		A="<s>"  ,		A="</s>"  ,		A="</s>"  ,		A="<s>"  ,		A="<unk>"  ,		A="<pad>"  ,		A="<mask>"  ,		A=None  ,		A=None  ,		A=None  ,		**A  ,		)  ->   List[Any]:



          '''simple docstring'''



          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else mask_token

          super().__init__(
              vocab_file=A  ,		tokenizer_file=A  ,		bos_token=A  ,		eos_token=A  ,		sep_token=A  ,		cls_token=A  ,		unk_token=A  ,		pad_token=A  ,		mask_token=A  ,		src_lang=A  ,		tgt_lang=A  ,		additional_special_tokens=A  ,		**A  ,		)

          a     =				vocab_file
          a     =				False if not self.vocab_file else True

          a     =				FAIRSEQ_LANGUAGE_CODES.copy()

          if additional_special_tokens is not None:
               # Only add those special tokens if they are not already there.
               _additional_special_tokens.extend(
                   [t for t in additional_special_tokens if t not in _additional_special_tokens]			)

          self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}			)
          a     =				{
              lang_code: self.convert_tokens_to_ids(A			) for lang_code in FAIRSEQ_LANGUAGE_CODES
          }

          a     =				src_lang if src_lang is not None else "en_XX"
          a     =				self.convert_tokens_to_ids(self._src_lang			)
          a     =				tgt_lang
          self.set_src_lang_special_tokens(self._src_lang			)







     @property
     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



          return self._src_lang







     @src_lang.setter
     def       lowerCAmelCase_    (     self  ,		A			)  ->   None:



          '''simple docstring'''



          a     =				new_src_lang
          self.set_src_lang_special_tokens(self._src_lang			)







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   List[int]:



          '''simple docstring'''



          if token_ids_a is None:
               return self.prefix_tokens + token_ids_a + self.suffix_tokens
          # We don't expect to process pairs, but leave the pair logic for API consistency
          return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   List[int]:



          '''simple docstring'''



          a     =				[self.sep_token_id]
          a     =				[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]







     def       lowerCAmelCase_    (     self  ,		A  ,		A  ,		A  ,		A  ,		**A			)  ->   Dict:



          '''simple docstring'''



          if src_lang is None or tgt_lang is None:
               raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"			)
          a     =				src_lang
          a     =				self(A  ,		add_special_tokens=A  ,		return_tensors=A  ,		**A			)
          a     =				self.convert_tokens_to_ids(A			)
          a     =				tgt_lang_id
          return inputs







     def       lowerCAmelCase_    (     self  ,		A  ,		A = "en_XX"  ,		A = None  ,		A = "ro_RO"  ,		**A  ,		)  ->   BatchEncoding:



          '''simple docstring'''



          a     =				src_lang
          a     =				tgt_lang
          return super().prepare_seqaseq_batch(A  ,		A  ,		**A			)







     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



          return self.set_src_lang_special_tokens(self.src_lang			)







     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return self.set_tgt_lang_special_tokens(self.tgt_lang			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   None:



          '''simple docstring'''



          a     =				self.convert_tokens_to_ids(A			)
          a     =				[]
          a     =				[self.eos_token_id, self.cur_lang_code]

          a     =				self.convert_ids_to_tokens(self.prefix_tokens			)
          a     =				self.convert_ids_to_tokens(self.suffix_tokens			)

          a     =				processors.TemplateProcessing(
              single=prefix_tokens_str + ["$A"] + suffix_tokens_str  ,		pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str  ,		special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,		self.prefix_tokens + self.suffix_tokens			)			)  ,		)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   None:



          '''simple docstring'''



          a     =				self.convert_tokens_to_ids(A			)
          a     =				[]
          a     =				[self.eos_token_id, self.cur_lang_code]

          a     =				self.convert_ids_to_tokens(self.prefix_tokens			)
          a     =				self.convert_ids_to_tokens(self.suffix_tokens			)

          a     =				processors.TemplateProcessing(
              single=prefix_tokens_str + ["$A"] + suffix_tokens_str  ,		pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str  ,		special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,		self.prefix_tokens + self.suffix_tokens			)			)  ,		)







     def       lowerCAmelCase_    (     self  ,		A  ,		A = 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(A			):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''			)
               return
          a     =				os.path.join(
              A  ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]			)

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

          return (out_vocab_file,)







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


lowercase__				:      Tuple	   = logging.get_logger(__name__)

lowercase__				:      int	   = {
    "microsoft/resnet-50": "https://huggingface.co/microsoft/resnet-50/blob/main/config.json",
}




class       a__	( UpperCamelCase__       , UpperCamelCase__				):
     a		:      Any		 =     """resnet"""
     a		:      Tuple		 =     ["""basic""", """bottleneck"""]







     def __init__(     self  ,		A=3  ,		A=64  ,		A=[256, 512, 1024, 2048]  ,		A=[3, 4, 6, 3]  ,		A="bottleneck"  ,		A="relu"  ,		A=False  ,		A=None  ,		A=None  ,		**A  ,		)  ->   Any:



          '''simple docstring'''



          super().__init__(**A			)
          if layer_type not in self.layer_types:
               raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types			)}'''			)
          a     =				num_channels
          a     =				embedding_size
          a     =				hidden_sizes
          a     =				depths
          a     =				layer_type
          a     =				hidden_act
          a     =				downsample_in_first_stage
          a     =				["stem"] + [F'''stage{idx}''' for idx in range(1  ,		len(A			) + 1			)]
          a  ,				a     =				get_aligned_output_features_output_indices(
              out_features=A  ,		out_indices=A  ,		stage_names=self.stage_names			)







class       a__	( UpperCamelCase__				):
     a		:      Optional[int]		 =     version.parse("""1.11"""				)







     @property
     def       lowerCAmelCase_    (     self			)  ->   Mapping[str, Mapping[int, str]]:



          '''simple docstring'''



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







     @property
     def       lowerCAmelCase_    (     self			)  ->   float:



          '''simple docstring'''



          return 1e-3

