


# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

from ...utils.dataclasses import (
    ComputeEnvironment,
    DistributedType,
    DynamoBackend,
    PrecisionType,
    SageMakerDistributedType,
)
from ..menu import BulletMenu


snake_case__			 =						[
    '''EAGER''',
    '''AOT_EAGER''',
    '''INDUCTOR''',
    '''NVFUSER''',
    '''AOT_NVFUSER''',
    '''AOT_CUDAGRAPHS''',
    '''OFI''',
    '''FX2TRT''',
    '''ONNXRT''',
    '''IPEX''',
]


def 				lowerCamelCase__	(      a	:   Optional[Any]	,  a	:   Tuple=None	,  a	:   int=None	,  a	:   List[str]=None				)    ->	int:





			"""simple docstring"""
			a__ :Tuple						  =    True
			while ask_again:
						a__ :str						  =    input(a				)
						try:
									if default is not None and len(a				) == 0:
												return default
									return convert_value(a				) if convert_value is not None else result
						except Exception:
									if error_message is not None:
												print(a				)


def 				lowerCamelCase__	(      a	:   int	,  a	:   Union[str, Any]=[]	,  a	:   str=None	,  a	:   str=0				)    ->	List[str]:





			"""simple docstring"""
			a__ :str						  =    BulletMenu(a	,  a				)
			a__ :int						  =    menu.run(default_choice=a				)
			return convert_value(a				) if convert_value is not None else result


def 				lowerCamelCase__	(      a	:   Optional[Any]				)    ->	Dict:





			"""simple docstring"""
			a__ :str						  =    int(a				)
			return ComputeEnvironment(["LOCAL_MACHINE", "AMAZON_SAGEMAKER"][value]				)


def 				lowerCamelCase__	(      a	:   Tuple				)    ->	List[str]:





			"""simple docstring"""
			a__ :Union[str, Any]						  =    int(a				)
			return DistributedType(["NO", "MULTI_CPU", "MULTI_XPU", "MULTI_GPU", "MULTI_NPU", "TPU"][value]				)


def 				lowerCamelCase__	(      a	:   List[Any]				)    ->	str:





			"""simple docstring"""
			a__ :int						  =    int(a				)
			return DynamoBackend(DYNAMO_BACKENDS[value]				).value


def 				lowerCamelCase__	(      a	:   Any				)    ->	Union[str, Any]:





			"""simple docstring"""
			a__ :Optional[Any]						  =    int(a				)
			return PrecisionType(["no", "fp16", "bf16", "fp8"][value]				)


def 				lowerCamelCase__	(      a	:   List[Any]				)    ->	Union[str, Any]:





			"""simple docstring"""
			a__ :Optional[Any]						  =    int(a				)
			return SageMakerDistributedType(["NO", "DATA_PARALLEL", "MODEL_PARALLEL"][value]				)


def 				lowerCamelCase__	(      a	:   Union[str, Any]				)    ->	List[str]:





			"""simple docstring"""
			return {"yes": True, "no": False}[value.lower()]







class 					lowerCAmelCase_ (       argparse.RawDescriptionHelpFormatter):




						def  _snake_case					(	self						:   Tuple   ,     __A						:   Tuple   ,     __A						:   int   ,     __A						:   Tuple   ,     __A						:   Any						)      ->Union[str, Any]:






									"""simple docstring"""






									a__ :Optional[int]						  =    super()._format_usage(__A   ,     __A   ,     __A   ,     __A						)
									a__ :Any						  =    usage.replace("<command> [<args>] "   ,     ""						)
									return usage






import functools
import operator

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


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''asapp/sew-tiny-100k''': '''https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json''',
    # See all SEW models at https://huggingface.co/models?filter=sew
}


class 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     'sew'




						def __init__(	self						:   Any   ,     __A						:   str=32   ,     __A						:   Dict=768   ,     __A						:   int=12   ,     __A						:   Dict=12   ,     __A						:   Dict=3072   ,     __A						:   int=2   ,     __A						:   Union[str, Any]="gelu"   ,     __A						:   Union[str, Any]=0.1   ,     __A						:   Optional[Any]=0.1   ,     __A						:   Union[str, Any]=0.1   ,     __A						:   str=0.0   ,     __A						:   Union[str, Any]=0.1   ,     __A						:   Optional[Any]=0.1   ,     __A						:   Tuple=0.02   ,     __A						:   Any=1E-5   ,     __A						:   Optional[Any]="group"   ,     __A						:   str="gelu"   ,     __A						:   Dict=(64, 128, 128, 128, 128, 256, 256, 256, 256, 512, 512, 512, 512)   ,     __A						:   Tuple=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)   ,     __A						:   int=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)   ,     __A						:   List[str]=False   ,     __A						:   Tuple=128   ,     __A						:   Tuple=16   ,     __A						:   Optional[int]=True   ,     __A						:   Union[str, Any]=0.05   ,     __A						:   List[str]=10   ,     __A						:   Optional[int]=2   ,     __A						:   List[Any]=0.0   ,     __A						:   Optional[Any]=10   ,     __A						:   Tuple=0   ,     __A						:   Tuple="mean"   ,     __A						:   Any=False   ,     __A						:   str=False   ,     __A						:   Dict=256   ,     __A						:   Union[str, Any]=0   ,     __A						:   Optional[int]=1   ,     __A						:   Optional[Any]=2   ,     **__A						:   Tuple   ,     )      ->Tuple:






									"""simple docstring"""






									super().__init__(**__A   ,     pad_token_id=__A   ,     bos_token_id=__A   ,     eos_token_id=__A						)
									a__ :List[Any]						  =    hidden_size
									a__ :List[Any]						  =    feat_extract_norm
									a__ :List[str]						  =    feat_extract_activation
									a__ :Any						  =    list(__A						)
									a__ :Dict						  =    list(__A						)
									a__ :Optional[int]						  =    list(__A						)
									a__ :Any						  =    conv_bias
									a__ :List[str]						  =    num_conv_pos_embeddings
									a__ :str						  =    num_conv_pos_embedding_groups
									a__ :Optional[int]						  =    len(self.conv_dim						)
									a__ :List[Any]						  =    num_hidden_layers
									a__ :str						  =    intermediate_size
									a__ :Dict						  =    squeeze_factor
									a__ :List[Any]						  =    hidden_act
									a__ :Optional[Any]						  =    num_attention_heads
									a__ :Tuple						  =    hidden_dropout
									a__ :Tuple						  =    attention_dropout
									a__ :List[Any]						  =    activation_dropout
									a__ :str						  =    feat_proj_dropout
									a__ :Any						  =    final_dropout
									a__ :Dict						  =    layerdrop
									a__ :List[str]						  =    layer_norm_eps
									a__ :Tuple						  =    initializer_range
									a__ :Dict						  =    vocab_size

									if (
									    (len(self.conv_stride						) != self.num_feat_extract_layers)
									    or (len(self.conv_kernel						) != self.num_feat_extract_layers)
									    or (len(self.conv_dim						) != self.num_feat_extract_layers)
									):
												raise ValueError(
												    "Configuration for convolutional layers is incorrect."
												    "It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,"
												    F'''but is `len(config.conv_dim) = {len(self.conv_dim						)}`, `len(config.conv_stride)'''
												    F'''= {len(self.conv_stride						)}`, `len(config.conv_kernel) = {len(self.conv_kernel						)}`.'''						)

									# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
									a__ :int						  =    apply_spec_augment
									a__ :Optional[Any]						  =    mask_time_prob
									a__ :List[Any]						  =    mask_time_length
									a__ :Any						  =    mask_time_min_masks
									a__ :Any						  =    mask_feature_prob
									a__ :Dict						  =    mask_feature_length
									a__ :Union[str, Any]						  =    mask_feature_min_masks

									# ctc loss
									a__ :Dict						  =    ctc_loss_reduction
									a__ :Any						  =    ctc_zero_infinity

									# sequence classification
									a__ :Optional[int]						  =    use_weighted_layer_sum
									a__ :Tuple						  =    classifier_proj_size






						@property
						def  _snake_case					(	self						:   Dict						)      ->Union[str, Any]:






									"""simple docstring"""






									return functools.reduce(operator.mul   ,     self.conv_stride   ,     1						)


