


import warnings
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE      :			Optional[int]      				=   logging.get_logger(__name__)

class   A__ (   snake_case__     ):







    """simple docstring"""

    __magic_name__        =		['input_ids', 'attention_mask']
    def __init__(	self      , __snake_case="</s>"      , __snake_case="<unk>"      , __snake_case="<pad>"      , __snake_case=1_2_5      , __snake_case=None      , **__snake_case      , ):
         # Add extra_ids to the special token list
         if extra_ids > 0 and additional_special_tokens is None:
              snake_case					=    [F'''<extra_id_{i}>''' for i in range(__snake_case   )]
         elif extra_ids > 0 and additional_special_tokens is not None:
              # Check that we have the right number of extra_id special tokens
              snake_case					=    len(set(filter(lambda __snake_case   : bool('''extra_id''' in str(__snake_case   )   )      , __snake_case   )   )   )
              if extra_tokens != extra_ids:
                   raise ValueError(
                       F'''Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'''
                       ''' provided to ByT5Tokenizer. In this case the additional_special_tokens must include the'''
                       ''' extra_ids tokens'''   )

         snake_case					=    AddedToken(__snake_case      , lstrip=__snake_case      , rstrip=__snake_case   ) if isinstance(__snake_case      , __snake_case   ) else pad_token
         snake_case					=    AddedToken(__snake_case      , lstrip=__snake_case      , rstrip=__snake_case   ) if isinstance(__snake_case      , __snake_case   ) else eos_token
         snake_case					=    AddedToken(__snake_case      , lstrip=__snake_case      , rstrip=__snake_case   ) if isinstance(__snake_case      , __snake_case   ) else unk_token

         super().__init__(
             eos_token=__snake_case      , unk_token=__snake_case      , pad_token=__snake_case      , extra_ids=__snake_case      , additional_special_tokens=__snake_case      , **__snake_case      , )

         snake_case					=    extra_ids

         snake_case					=    2**8  # utf is 8 bits

         # define special tokens dict
         snake_case					=    {
             self.pad_token: 0,
             self.eos_token: 1,
             self.unk_token: 2,
         }
         snake_case					=    len(self.special_tokens_encoder   )
         snake_case					=    len(__snake_case   )
         for i, token in enumerate(__snake_case   ):
              snake_case					=    self.vocab_size + i - n
         snake_case					=    {v: k for k, v in self.special_tokens_encoder.items()}
    @property
    def 		a_      (	self   ):
         return self._utf_vocab_size + self._num_special_tokens + self._extra_ids
    def 		a_      (	self      , __snake_case      , __snake_case = None      , __snake_case = False   ):
         if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=__snake_case      , token_ids_a=__snake_case      , already_has_special_tokens=__snake_case   )

         # normal case: some special tokens
         if token_ids_a is None:
              return ([0] * len(__snake_case   )) + [1]
         return ([0] * len(__snake_case   )) + [1] + ([0] * len(__snake_case   )) + [1]
    def 		a_      (	self      , __snake_case   ):
         if len(__snake_case   ) > 0 and token_ids[-1] == self.eos_token_id:
              warnings.warn(
                  F'''This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated'''
                  ''' eos tokens being added.'''   )
              return token_ids
         else:
              return token_ids + [self.eos_token_id]
    def 		a_      (	self      , __snake_case      , __snake_case = None   ):
         snake_case					=    [self.eos_token_id]

         if token_ids_a is None:
              return len(token_ids_a + eos   ) * [0]
         return len(token_ids_a + eos + token_ids_a + eos   ) * [0]
    def 		a_      (	self      , __snake_case      , __snake_case = None   ):
         snake_case					=    self._add_eos_if_not_present(__snake_case   )
         if token_ids_a is None:
              return token_ids_a
         else:
              snake_case					=    self._add_eos_if_not_present(__snake_case   )
              return token_ids_a + token_ids_a
    def 		a_      (	self      , __snake_case   ):
         snake_case					=    [chr(__snake_case   ) for i in text.encode('''utf-8'''   )]
         return tokens
    def 		a_      (	self      , __snake_case   ):
         if token in self.special_tokens_encoder:
              snake_case					=    self.special_tokens_encoder[token]
         elif token in self.added_tokens_encoder:
              snake_case					=    self.added_tokens_encoder[token]
         elif len(__snake_case   ) != 1:
              snake_case					=    self.unk_token_id
         else:
              snake_case					=    ord(__snake_case   ) + self._num_special_tokens
         return token_id
    def 		a_      (	self      , __snake_case   ):
         if index in self.special_tokens_decoder:
              snake_case					=    self.special_tokens_decoder[index]
         else:
              snake_case					=    chr(index - self._num_special_tokens   )
         return token
    def 		a_      (	self      , __snake_case   ):
         snake_case					=    b''''''
         for token in tokens:
              if token in self.special_tokens_decoder:
                   snake_case					=    self.special_tokens_decoder[token].encode('''utf-8'''   )
              elif token in self.added_tokens_decoder:
                   snake_case					=    self.special_tokens_decoder[token].encode('''utf-8'''   )
              elif token in self.special_tokens_encoder:
                   snake_case					=    token.encode('''utf-8'''   )
              elif token in self.added_tokens_encoder:
                   snake_case					=    token.encode('''utf-8'''   )
              else:
                   snake_case					=    bytes([ord(__snake_case   )]   )
              bstring += tok_string
         snake_case					=    bstring.decode('''utf-8'''      , errors='''ignore'''   )
         return string




    def 		a_      (	self      , __snake_case      , __snake_case = None   ):
         return ()








from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


_SCREAMING_SNAKE_CASE      :			List[str]      				=   logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      :			Optional[int]      				=   {
    "google/efficientnet-b7": "https://huggingface.co/google/efficientnet-b7/resolve/main/config.json",
}

class   A__ (   snake_case__     ):







    """simple docstring"""

    __magic_name__        =		'efficientnet'
    def __init__(	self      , __snake_case = 3      , __snake_case = 6_0_0      , __snake_case = 2.0      , __snake_case = 3.1      , __snake_case = 8      , __snake_case = [3, 3, 5, 3, 5, 5, 3]      , __snake_case = [3_2, 1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2]      , __snake_case = [1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2, 3_2_0]      , __snake_case = []      , __snake_case = [1, 2, 2, 2, 1, 2, 1]      , __snake_case = [1, 2, 2, 3, 3, 4, 1]      , __snake_case = [1, 6, 6, 6, 6, 6, 6]      , __snake_case = 0.25      , __snake_case = "swish"      , __snake_case = 2_5_6_0      , __snake_case = "mean"      , __snake_case = 0.02      , __snake_case = 0.001      , __snake_case = 0.99      , __snake_case = 0.5      , __snake_case = 0.2      , **__snake_case      , ):
         super().__init__(**__snake_case   )

         snake_case					=    num_channels
         snake_case					=    image_size
         snake_case					=    width_coefficient
         snake_case					=    depth_coefficient
         snake_case					=    depth_divisor
         snake_case					=    kernel_sizes
         snake_case					=    in_channels
         snake_case					=    out_channels
         snake_case					=    depthwise_padding
         snake_case					=    strides
         snake_case					=    num_block_repeats
         snake_case					=    expand_ratios
         snake_case					=    squeeze_expansion_ratio
         snake_case					=    hidden_act
         snake_case					=    hidden_dim
         snake_case					=    pooling_type
         snake_case					=    initializer_range
         snake_case					=    batch_norm_eps
         snake_case					=    batch_norm_momentum
         snake_case					=    dropout_rate
         snake_case					=    drop_connect_rate
         snake_case					=    sum(__snake_case   ) * 4






class   A__ (   snake_case__     ):







    """simple docstring"""

    __magic_name__        =		version.parse('1.11'     )
    @property
    def 		a_      (	self   ):
         return OrderedDict(
             [
                 ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
             ]   )




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




