

from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
      from ...feature_extraction_utils import FeatureExtractionMixin
      from ...tokenization_utils_base import PreTrainedTokenizerBase
      from ...utils import TensorType

lowerCAmelCase__       = logging.get_logger(__name__)

lowerCAmelCase__       = {
    "openai/whisper-base": "https://huggingface.co/openai/whisper-base/resolve/main/config.json",
}

# fmt: off
lowerCAmelCase__       = [
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 357, 366, 438, 532, 685,
    705, 796, 930, 1058, 1220, 1267, 1279, 1303, 1343, 1377,
    1391, 1635, 1782, 1875, 2162, 2361, 2488, 3467, 4008, 4211,
    4600, 4808, 5299, 5855, 6329, 7203, 9609, 9959, 10563, 10786,
    11420, 11709, 11907, 13163, 13697, 13700, 14808, 15306, 16410, 16791,
    17992, 19203, 19510, 20724, 22305, 22935, 27007, 30109, 30420, 33409,
    34949, 40283, 40493, 40549, 47282, 49146, 50257, 50359, 50360, 50361
]
lowerCAmelCase__       = [
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 359, 503, 522, 542, 873,
    893, 902, 918, 922, 931, 1350, 1853, 1982, 2460, 2627,
    3246, 3253, 3268, 3536, 3846, 3961, 4183, 4667, 6585, 6647,
    7273, 9061, 9383, 10428, 10929, 11938, 12033, 12331, 12562, 13793,
    14157, 14635, 15265, 15618, 16553, 16604, 18362, 18956, 20075, 21675,
    22520, 26130, 26161, 26435, 28279, 29464, 31650, 32302, 32470, 36865,
    42863, 47425, 49870, 50254, 50258, 50360, 50361, 50362
]






class 						__magic_name__    (       _snake_case    ):
 UpperCAmelCase							    =						"""whisper"""
 UpperCAmelCase							    =						["""past_key_values"""]
 UpperCAmelCase							    =						{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}


 def __init__(						self		: List[str]			,						lowerCAmelCase__		: List[str]=5_1_8_6_5			,						lowerCAmelCase__		: int=8_0			,						lowerCAmelCase__		: Optional[int]=6			,						lowerCAmelCase__		: Dict=4			,						lowerCAmelCase__		: Tuple=6			,						lowerCAmelCase__		: str=4			,						lowerCAmelCase__		: int=1_5_3_6			,						lowerCAmelCase__		: Any=1_5_3_6			,						lowerCAmelCase__		: Optional[Any]=0.0			,						lowerCAmelCase__		: str=0.0			,						lowerCAmelCase__		: Optional[Any]=5_0_2_5_7			,						lowerCAmelCase__		: Tuple=True			,						lowerCAmelCase__		: List[str]=True			,						lowerCAmelCase__		: Dict="gelu"			,						lowerCAmelCase__		: List[str]=2_5_6			,						lowerCAmelCase__		: str=0.0			,						lowerCAmelCase__		: Tuple=0.0			,						lowerCAmelCase__		: Dict=0.0			,						lowerCAmelCase__		: List[str]=0.02			,						lowerCAmelCase__		: Optional[Any]=False			,						lowerCAmelCase__		: Dict=1_5_0_0			,						lowerCAmelCase__		: List[Any]=4_4_8			,						lowerCAmelCase__		: str=5_0_2_5_6			,						lowerCAmelCase__		: Union[str, Any]=5_0_2_5_6			,						lowerCAmelCase__		: Any=5_0_2_5_6			,						lowerCAmelCase__		: Any=None			,						lowerCAmelCase__		: Tuple=[2_2_0, 5_0_2_5_6]			,						lowerCAmelCase__		: Tuple=False			,						lowerCAmelCase__		: List[Any]=2_5_6			,						lowerCAmelCase__		: Optional[int]=False			,						lowerCAmelCase__		: int=0.05			,						lowerCAmelCase__		: Any=1_0			,						lowerCAmelCase__		: Optional[int]=2			,						lowerCAmelCase__		: List[str]=0.0			,						lowerCAmelCase__		: Tuple=1_0			,						lowerCAmelCase__		: Optional[Any]=0			,						lowerCAmelCase__		: Optional[int]=7			,						**lowerCAmelCase__		: Tuple			,						)    ->      Optional[Any]:
   UpperCAmelCase					      =  vocab_size
   UpperCAmelCase					      =  num_mel_bins
   UpperCAmelCase					      =  d_model
   UpperCAmelCase					      =  encoder_layers
   UpperCAmelCase					      =  encoder_attention_heads
   UpperCAmelCase					      =  decoder_layers
   UpperCAmelCase					      =  decoder_attention_heads
   UpperCAmelCase					      =  decoder_ffn_dim
   UpperCAmelCase					      =  encoder_ffn_dim
   UpperCAmelCase					      =  dropout
   UpperCAmelCase					      =  attention_dropout
   UpperCAmelCase					      =  activation_dropout
   UpperCAmelCase					      =  activation_function
   UpperCAmelCase					      =  init_std
   UpperCAmelCase					      =  encoder_layerdrop
   UpperCAmelCase					      =  decoder_layerdrop
   UpperCAmelCase					      =  use_cache
   UpperCAmelCase					      =  encoder_layers
   UpperCAmelCase					      =  scale_embedding  # scale factor will be sqrt(d_model) if True
   UpperCAmelCase					      =  max_source_positions
   UpperCAmelCase					      =  max_target_positions

   # Audio Classification-specific parameters. Feel free to ignore for other classes.
   UpperCAmelCase					      =  classifier_proj_size
   UpperCAmelCase					      =  use_weighted_layer_sum

   # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
   UpperCAmelCase					      =  apply_spec_augment
   UpperCAmelCase					      =  mask_time_prob
   UpperCAmelCase					      =  mask_time_length
   UpperCAmelCase					      =  mask_time_min_masks
   UpperCAmelCase					      =  mask_feature_prob
   UpperCAmelCase					      =  mask_feature_length
   UpperCAmelCase					      =  mask_feature_min_masks

   UpperCAmelCase					      =  median_filter_width

   super().__init__(
       pad_token_id=lowerCAmelCase__			,						bos_token_id=lowerCAmelCase__			,						eos_token_id=lowerCAmelCase__			,						is_encoder_decoder=lowerCAmelCase__			,						decoder_start_token_id=lowerCAmelCase__			,						suppress_tokens=lowerCAmelCase__			,						begin_suppress_tokens=lowerCAmelCase__			,						**lowerCAmelCase__			,						)






class 						__magic_name__    (       _snake_case    ):


 @property
 def _UpperCamelCase	(						self		: Optional[Any]    )    ->      Mapping[str, Mapping[int, str]]:
   UpperCAmelCase					      =  OrderedDict(
       [
           ("input_features", {0: "batch", 1: "feature_size", 2: "encoder_sequence"}),
       ]    )
   if self.use_past:
     UpperCAmelCase					      =  {0: "batch"}
   else:
     UpperCAmelCase					      =  {0: "batch", 1: "decoder_sequence"}

   if self.use_past:
     self.fill_with_past_key_values_(lowerCAmelCase__			,						direction="inputs"    )

   return common_inputs


 def _UpperCamelCase	(						self		: List[str]			,						lowerCAmelCase__		: Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]			,						lowerCAmelCase__		: int = -1			,						lowerCAmelCase__		: int = -1			,						lowerCAmelCase__		: bool = False			,						lowerCAmelCase__		: Optional["TensorType"] = None			,						lowerCAmelCase__		: int = 2_2_0_5_0			,						lowerCAmelCase__		: float = 5.0			,						lowerCAmelCase__		: int = 2_2_0			,						)    ->      Mapping[str, Any]:
   UpperCAmelCase					      =  OrderedDict()
   UpperCAmelCase					      =  OnnxConfig.generate_dummy_inputs(
       self			,						preprocessor=preprocessor.feature_extractor			,						batch_size=lowerCAmelCase__			,						framework=lowerCAmelCase__			,						sampling_rate=lowerCAmelCase__			,						time_duration=lowerCAmelCase__			,						frequency=lowerCAmelCase__			,						)
   UpperCAmelCase					      =  encoder_inputs["input_features"].shape[2]
   UpperCAmelCase					      =  encoder_sequence_length // 2 if self.use_past else seq_length

   UpperCAmelCase					      =  super().generate_dummy_inputs(
       preprocessor.tokenizer			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__    )

   UpperCAmelCase					      =  encoder_inputs.pop("input_features"    )
   UpperCAmelCase					      =  decoder_inputs.pop("decoder_input_ids"    )

   if "past_key_values" in decoder_inputs:
     UpperCAmelCase					      =  decoder_inputs.pop("past_key_values"    )

   return dummy_inputs


 @property
 def _UpperCamelCase	(						self		: List[str]    )    ->      float:
   return 1e-3






def      _lowerCAmelCase(	__A			):
  assert column_title.isupper()
  UpperCAmelCase					      =  0
  UpperCAmelCase					      =  len(__A			) - 1
  UpperCAmelCase					      =  0

  while index >= 0:
    UpperCAmelCase					      =  (ord(column_title[index]			) - 64) * pow(26   ,       __A			)
    answer += value
    power += 1
    index -= 1

  return answer


if __name__ == "__main__":
      from doctest import testmod

      testmod()



