




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		:				str       			=		logging.get_logger(__name__)

__lowerCAmelCase		:				List[str]       			=		{
    "openai/whisper-base": "https://huggingface.co/openai/whisper-base/resolve/main/config.json",
}

# fmt: off
__lowerCAmelCase		:				Optional[int]       			=		[
    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, 1_0563, 1_0786,
    1_1420, 1_1709, 1_1907, 1_3163, 1_3697, 1_3700, 1_4808, 1_5306, 1_6410, 1_6791,
    1_7992, 1_9203, 1_9510, 2_0724, 2_2305, 2_2935, 2_7007, 3_0109, 3_0420, 3_3409,
    3_4949, 4_0283, 4_0493, 4_0549, 4_7282, 4_9146, 5_0257, 5_0359, 5_0360, 5_0361
]
__lowerCAmelCase		:				Tuple       			=		[
    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, 1_0428, 1_0929, 1_1938, 1_2033, 1_2331, 1_2562, 1_3793,
    1_4157, 1_4635, 1_5265, 1_5618, 1_6553, 1_6604, 1_8362, 1_8956, 2_0075, 2_1675,
    2_2520, 2_6130, 2_6161, 2_6435, 2_8279, 2_9464, 3_1650, 3_2302, 3_2470, 3_6865,
    4_2863, 4_7425, 4_9870, 5_0254, 5_0258, 5_0360, 5_0361, 5_0362
]




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							List[Any]							 =					"""whisper"""
				SCREAMING_SNAKE_CASE_       :							Dict							 =					["""past_key_values"""]
				SCREAMING_SNAKE_CASE_       :							str							 =					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}





				def __init__(      self				:     Optional[int]					,      __lowerCamelCase				:     Union[str, Any]=5_18_65					,      __lowerCamelCase				:     Any=80					,      __lowerCamelCase				:     Tuple=6					,      __lowerCamelCase				:     Tuple=4					,      __lowerCamelCase				:     Dict=6					,      __lowerCamelCase				:     Union[str, Any]=4					,      __lowerCamelCase				:     int=15_36					,      __lowerCamelCase				:     Optional[Any]=15_36					,      __lowerCamelCase				:     List[str]=0.0					,      __lowerCamelCase				:     int=0.0					,      __lowerCamelCase				:     Union[str, Any]=5_02_57					,      __lowerCamelCase				:     Optional[int]=True					,      __lowerCamelCase				:     Any=True					,      __lowerCamelCase				:     List[str]="gelu"					,      __lowerCamelCase				:     Union[str, Any]=2_56					,      __lowerCamelCase				:     List[str]=0.0					,      __lowerCamelCase				:     Optional[int]=0.0					,      __lowerCamelCase				:     str=0.0					,      __lowerCamelCase				:     Tuple=0.02					,      __lowerCamelCase				:     Union[str, Any]=False					,      __lowerCamelCase				:     List[str]=15_00					,      __lowerCamelCase				:     Dict=4_48					,      __lowerCamelCase				:     List[str]=5_02_56					,      __lowerCamelCase				:     List[Any]=5_02_56					,      __lowerCamelCase				:     str=5_02_56					,      __lowerCamelCase				:     int=None					,      __lowerCamelCase				:     List[str]=[2_20, 5_02_56]					,      __lowerCamelCase				:     List[str]=False					,      __lowerCamelCase				:     Union[str, Any]=2_56					,      __lowerCamelCase				:     Dict=False					,      __lowerCamelCase				:     Any=0.05					,      __lowerCamelCase				:     List[str]=10					,      __lowerCamelCase				:     List[str]=2					,      __lowerCamelCase				:     Any=0.0					,      __lowerCamelCase				:     Optional[int]=10					,      __lowerCamelCase				:     Tuple=0					,      __lowerCamelCase				:     Tuple=7					,      **__lowerCamelCase				:     Dict					,      )					->     int:
							a    =			vocab_size
							a    =			num_mel_bins
							a    =			d_model
							a    =			encoder_layers
							a    =			encoder_attention_heads
							a    =			decoder_layers
							a    =			decoder_attention_heads
							a    =			decoder_ffn_dim
							a    =			encoder_ffn_dim
							a    =			dropout
							a    =			attention_dropout
							a    =			activation_dropout
							a    =			activation_function
							a    =			init_std
							a    =			encoder_layerdrop
							a    =			decoder_layerdrop
							a    =			use_cache
							a    =			encoder_layers
							a    =			scale_embedding  # scale factor will be sqrt(d_model) if True
							a    =			max_source_positions
							a    =			max_target_positions

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

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

							a    =			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 							__UpperCAmelCase							(      self				:     List[Any]							)					->     Tuple:
							a    =			OrderedDict(
							    [
							        ("input_features", {0: "batch", 1: "feature_size", 2: "encoder_sequence"}),
							    ]							)
							if self.use_past:
										a    =			{0: "batch"}
							else:
										a    =			{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[Any]					,      __lowerCamelCase				:     str					,      __lowerCamelCase				:     List[Any] = -1					,      __lowerCamelCase				:     int = -1					,      __lowerCamelCase				:     str = False					,      __lowerCamelCase				:     int = None					,      __lowerCamelCase				:     List[Any] = 2_20_50					,      __lowerCamelCase				:     Tuple = 5.0					,      __lowerCamelCase				:     List[str] = 2_20					,      )					->     List[str]:
							a    =			OrderedDict()
							a    =			OnnxConfig.generate_dummy_inputs(
							    self					,      preprocessor=preprocessor.feature_extractor					,      batch_size=lowerCamelCase_					,      framework=lowerCamelCase_					,      sampling_rate=lowerCamelCase_					,      time_duration=lowerCamelCase_					,      frequency=lowerCamelCase_					,      )
							a    =			encoder_inputs["input_features"].shape[2]
							a    =			encoder_sequence_length // 2 if self.use_past else seq_length

							a    =			super().generate_dummy_inputs(
							    preprocessor.tokenizer					,      lowerCamelCase_					,      lowerCamelCase_					,      lowerCamelCase_					,      lowerCamelCase_							)

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

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

							return dummy_inputs





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











from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase: str      			=		logging.get_logger(__name__)

_lowercase: List[str]      			=		{
    "microsoft/trocr-base-handwritten": (
        "https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}



class 	_lowercase							(   lowerCAmelCase	):





	"""simple docstring"""
	__A							=							"trocr"
	__A							=							["past_key_values"]
	__A							=							{
	    "num_attention_heads": "decoder_attention_heads",
	    "hidden_size": "d_model",
	    "num_hidden_layers": "decoder_layers",
	}




	def __init__(self		,       lowerCamelCase_=50265		,       lowerCamelCase_=1024		,       lowerCamelCase_=12		,       lowerCamelCase_=16		,       lowerCamelCase_=4096		,       lowerCamelCase_="gelu"		,       lowerCamelCase_=512		,       lowerCamelCase_=0.1		,       lowerCamelCase_=0.0		,       lowerCamelCase_=0.0		,       lowerCamelCase_=2		,       lowerCamelCase_=0.02		,       lowerCamelCase_=0.0		,       lowerCamelCase_=True		,       lowerCamelCase_=False		,       lowerCamelCase_=True		,       lowerCamelCase_=True		,       lowerCamelCase_=1		,       lowerCamelCase_=0		,       lowerCamelCase_=2		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						a					     =   vocab_size
						a					     =   d_model
						a					     =   decoder_layers
						a					     =   decoder_attention_heads
						a					     =   decoder_ffn_dim
						a					     =   activation_function
						a					     =   max_position_embeddings
						a					     =   dropout
						a					     =   attention_dropout
						a					     =   activation_dropout
						a					     =   init_std
						a					     =   decoder_layerdrop
						a					     =   use_cache
						a					     =   scale_embedding
						a					     =   use_learned_position_embeddings
						a					     =   layernorm_embedding

						super().__init__(
						    pad_token_id=lowerCamelCase_		,       bos_token_id=lowerCamelCase_		,       eos_token_id=lowerCamelCase_		,       decoder_start_token_id=lowerCamelCase_		,       **lowerCamelCase_		,       )
