




'''simple docstring'''


from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


UpperCAmelCase_ 		=      logging.get_logger(__name__)

UpperCAmelCase_ 		=      {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCAmelCase_ 		=      {
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

UpperCAmelCase_ 		=      {
    "facebook/blenderbot_small-90M": 5_12,
}





class    __lowercase						(  snake_case__ ):
   _a							=      VOCAB_FILES_NAMES
   _a							=      PRETRAINED_VOCAB_FILES_MAP
   _a							=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _a							=      BlenderbotSmallTokenizer







   def __init__(	self      ,							UpperCamelCase=None      ,							UpperCamelCase=None      ,							UpperCamelCase="<|endoftext|>"      ,							UpperCamelCase="<|endoftext|>"      ,							UpperCamelCase="<|endoftext|>"      ,							UpperCamelCase=False      ,							UpperCamelCase=True      ,							**UpperCamelCase      ,							)				->    str:
     super().__init__(
         ByteLevelBPETokenizer(
             vocab=lowercase_      ,							merges=lowercase_      ,							add_prefix_space=lowercase_      ,							trim_offsets=lowercase_      ,							)      ,							bos_token=lowercase_      ,							eos_token=lowercase_      ,							unk_token=lowercase_      ,							**lowercase_      ,							)
     __a			=					add_prefix_space







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase=None      )				->    Tuple:
     __a			=					[self.bos_token_id] + token_ids_a + [self.eos_token_id]
     if token_ids_a is None:
       return output

     return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase = None      )				->    str:
     __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]









'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_ 		=      logging.get_logger(__name__)

UpperCAmelCase_ 		=      {
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}





class    __lowercase						(  __magic_name__ ):
   _a							=      """distilbert"""
   _a							=      {
       """hidden_size""": """dim""",
       """num_attention_heads""": """n_heads""",
       """num_hidden_layers""": """n_layers""",
   }







   def __init__(	self      ,							UpperCamelCase=3_0522      ,							UpperCamelCase=512      ,							UpperCamelCase=False      ,							UpperCamelCase=6      ,							UpperCamelCase=12      ,							UpperCamelCase=768      ,							UpperCamelCase=4 * 768      ,							UpperCamelCase=0.1      ,							UpperCamelCase=0.1      ,							UpperCamelCase="gelu"      ,							UpperCamelCase=0.02      ,							UpperCamelCase=0.1      ,							UpperCamelCase=0.2      ,							UpperCamelCase=0      ,							**UpperCamelCase      ,							)				->    int:
     __a			=					vocab_size
     __a			=					max_position_embeddings
     __a			=					sinusoidal_pos_embds
     __a			=					n_layers
     __a			=					n_heads
     __a			=					dim
     __a			=					hidden_dim
     __a			=					dropout
     __a			=					attention_dropout
     __a			=					activation
     __a			=					initializer_range
     __a			=					qa_dropout
     __a			=					seq_classif_dropout
     super().__init__(**UpperCamelCase      ,							pad_token_id=UpperCamelCase      )





class    __lowercase						(  __magic_name__ ):







   @property
   def 		UpperCamelCase__			(	self      )				->    Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
       __a			=					{0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
       __a			=					{0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
         ]      )



