"""simple docstring"""






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__  :  int						     =	logging.get_logger(__name__)

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

# fmt: off
lowerCAmelCase__  :  str						     =	[
    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, 1_058, 1_220, 1_267, 1_279, 1_303, 1_343, 1_377,
    1_391, 1_635, 1_782, 1_875, 2_162, 2_361, 2_488, 3_467, 4_008, 4_211,
    4_600, 4_808, 5_299, 5_855, 6_329, 7_203, 9_609, 9_959, 10_563, 10_786,
    11_420, 11_709, 11_907, 13_163, 13_697, 13_700, 14_808, 15_306, 16_410, 16_791,
    17_992, 19_203, 19_510, 20_724, 22_305, 22_935, 27_007, 30_109, 30_420, 33_409,
    34_949, 40_283, 40_493, 40_549, 47_282, 49_146, 50_257, 50_359, 50_360, 50_361
]
lowerCAmelCase__  :  Optional[Any]						     =	[
    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, 1_350, 1_853, 1_982, 2_460, 2_627,
    3_246, 3_253, 3_268, 3_536, 3_846, 3_961, 4_183, 4_667, 6_585, 6_647,
    7_273, 9_061, 9_383, 10_428, 10_929, 11_938, 12_033, 12_331, 12_562, 13_793,
    14_157, 14_635, 15_265, 15_618, 16_553, 16_604, 18_362, 18_956, 20_075, 21_675,
    22_520, 26_130, 26_161, 26_435, 28_279, 29_464, 31_650, 32_302, 32_470, 36_865,
    42_863, 47_425, 49_870, 50_254, 50_258, 50_360, 50_361, 50_362
]
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					snake_case__				    = "whisper"
					snake_case__				    = ["past_key_values"]
					snake_case__				    = {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}







					def __init__(				self   :	str    ,lowerCamelCase__   :	Tuple=51_865    ,lowerCamelCase__   :	Optional[Any]=80    ,lowerCamelCase__   :	Tuple=6    ,lowerCamelCase__   :	Optional[Any]=4    ,lowerCamelCase__   :	int=6    ,lowerCamelCase__   :	int=4    ,lowerCamelCase__   :	Union[str, Any]=1_536    ,lowerCamelCase__   :	Optional[int]=1_536    ,lowerCamelCase__   :	str=0.0    ,lowerCamelCase__   :	List[Any]=0.0    ,lowerCamelCase__   :	Dict=50_257    ,lowerCamelCase__   :	Union[str, Any]=True    ,lowerCamelCase__   :	Dict=True    ,lowerCamelCase__   :	List[str]="gelu"    ,lowerCamelCase__   :	Dict=256    ,lowerCamelCase__   :	Optional[Any]=0.0    ,lowerCamelCase__   :	List[str]=0.0    ,lowerCamelCase__   :	List[Any]=0.0    ,lowerCamelCase__   :	Union[str, Any]=0.0_2    ,lowerCamelCase__   :	Optional[Any]=False    ,lowerCamelCase__   :	Optional[Any]=1_500    ,lowerCamelCase__   :	Union[str, Any]=448    ,lowerCamelCase__   :	Tuple=50_256    ,lowerCamelCase__   :	List[str]=50_256    ,lowerCamelCase__   :	List[Any]=50_256    ,lowerCamelCase__   :	Tuple=None    ,lowerCamelCase__   :	Tuple=[220, 50_256]    ,lowerCamelCase__   :	List[Any]=False    ,lowerCamelCase__   :	Dict=256    ,lowerCamelCase__   :	List[str]=False    ,lowerCamelCase__   :	Tuple=0.0_5    ,lowerCamelCase__   :	Tuple=10    ,lowerCamelCase__   :	str=2    ,lowerCamelCase__   :	List[Any]=0.0    ,lowerCamelCase__   :	int=10    ,lowerCamelCase__   :	Any=0    ,lowerCamelCase__   :	Optional[Any]=7    ,**lowerCamelCase__   :	Dict    ,):
									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 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					@property
					def 		__lowerCAmelCase						(				self   :	Any			):
									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 		__lowerCAmelCase						(				self   :	Any    ,lowerCamelCase__   :	Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]    ,lowerCamelCase__   :	int = -1    ,lowerCamelCase__   :	int = -1    ,lowerCamelCase__   :	bool = False    ,lowerCamelCase__   :	Optional["TensorType"] = None    ,lowerCamelCase__   :	int = 22_050    ,lowerCamelCase__   :	float = 5.0    ,lowerCamelCase__   :	int = 220    ,):
									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 		__lowerCAmelCase						(				self   :	str			):
									return 1e-3




"""simple docstring"""






from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				snake_case       :




					"""simple docstring"""

					snake_case__				    = 42
					snake_case__				    = None
					snake_case__				    = None






lowerCAmelCase__  :  Union[str, Any]						     =	namedtuple('CoinsDistribResult', 'moves excess')



def   a_						(					lowerCamelCase       ):

				if root is None:
								return 0

				# Validation
				def count_nodes(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_nodes(node.left       ) + count_nodes(node.right       ) + 1

				def count_coins(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_coins(node.left       ) + count_coins(node.right       ) + node.data

				if count_nodes(lowerCamelCase       ) != count_coins(lowerCamelCase       ):
								raise ValueError('The nodes number should be same as the number of coins'       )

				# Main calculation
				def get_distrib(lowerCamelCase       ) -> CoinsDistribResult:

								if node is None:
												return CoinsDistribResult(0					,			1       )

								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.left       )
								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.right       )

								UpperCAmelCase__             =							1 - left_distrib_excess
								UpperCAmelCase__             =							1 - right_distrib_excess

								UpperCAmelCase__             =							(
								    left_distrib_moves
								    + right_distrib_moves
								    + abs(lowerCamelCase       )
								    + abs(lowerCamelCase       )
								)
								UpperCAmelCase__             =							node.data - coins_to_left - coins_to_right

								return CoinsDistribResult(lowerCamelCase					,			lowerCamelCase       )

				return get_distrib(lowerCamelCase       )[0]


if __name__ == "__main__":
						import doctest

						doctest.testmod()



