
'''simple docstring'''
import os

import pytest
from attr import dataclass


lowerCAmelCase					:    Dict           = 'us-east-1'  # defaults region


@dataclass
class 			SCREAMING_SNAKE_CASE__      :
				lowerCAmelCase_     			=							42
				lowerCAmelCase_     			=							"""arn:aws:iam::558105141721:role/sagemaker_execution_role"""
				lowerCAmelCase_     			=							{
				    """task_name""": """mnli""",
				    """per_device_train_batch_size""": 16,
				    """per_device_eval_batch_size""": 16,
				    """do_train""": True,
				    """do_eval""": True,
				    """do_predict""": True,
				    """output_dir""": """/opt/ml/model""",
				    """overwrite_output_dir""": True,
				    """max_steps""": 5_00,
				    """save_steps""": 55_00,
				}
				lowerCAmelCase_     			=							{**hyperparameters, """max_steps""": 10_00}







				@property
				def 						UpperCAmelCase_    (       self     )->		str:







											'''simple docstring'''






											if self.framework == "pytorch":
																		return [
																		    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																		    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
																		    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
																		]
											else:
																		return [
																		    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																		    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
																		    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
																		]







				@property
				def 						UpperCAmelCase_    (       self     )->		str:







											'''simple docstring'''






											return F'''{self.framework}-transfromers-test'''







				@property
				def 						UpperCAmelCase_    (       self     )->		str:







											'''simple docstring'''






											return F'''./tests/sagemaker/scripts/{self.framework}'''







				@property
				def 						UpperCAmelCase_    (       self     )->		str:







											'''simple docstring'''






											if self.framework == "pytorch":
																		return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
											else:
																		return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"







@pytest.fixture(scope='class')
def 		A_(     A						:		Optional[int]):
							UpperCamelCase   			=     SageMakerTestEnvironment(framework=request.cls.framework)






'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging


lowerCAmelCase					:    Optional[Any]           = logging.get_logger(__name__)

lowerCAmelCase					:    Dict           = {
    'speechbrain/m-ctc-t-large': 'https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json',
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}


class 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							"""mctct"""







				def __init__(       self						,				A_=8065						,				A_=1536						,				A_=36						,				A_=6144						,				A_=4						,				A_=384						,				A_=920						,				A_=1e-5						,				A_=0.3						,				A_="relu"						,				A_=0.02						,				A_=0.3						,				A_=0.3						,				A_=1						,				A_=0						,				A_=2						,				A_=1						,				A_=0.3						,				A_=1						,				A_=(7,)						,				A_=(3,)						,				A_=80						,				A_=1						,				A_=None						,				A_="sum"						,				A_=False						,				**A_						,				)->		str:







											'''simple docstring'''






											super().__init__(**A_						,				pad_token_id=A_						,				bos_token_id=A_						,				eos_token_id=A_     )
											UpperCamelCase   			=     vocab_size
											UpperCamelCase   			=     hidden_size
											UpperCamelCase   			=     num_hidden_layers
											UpperCamelCase   			=     intermediate_size
											UpperCamelCase   			=     num_attention_heads
											UpperCamelCase   			=     attention_head_dim
											UpperCamelCase   			=     max_position_embeddings
											UpperCamelCase   			=     layer_norm_eps
											UpperCamelCase   			=     layerdrop
											UpperCamelCase   			=     hidden_act
											UpperCamelCase   			=     initializer_range
											UpperCamelCase   			=     hidden_dropout_prob
											UpperCamelCase   			=     attention_probs_dropout_prob
											UpperCamelCase   			=     pad_token_id
											UpperCamelCase   			=     bos_token_id
											UpperCamelCase   			=     eos_token_id
											UpperCamelCase   			=     conv_glu_dim
											UpperCamelCase   			=     conv_dropout
											UpperCamelCase   			=     num_conv_layers
											UpperCamelCase   			=     input_feat_per_channel
											UpperCamelCase   			=     input_channels
											UpperCamelCase   			=     conv_channels
											UpperCamelCase   			=     ctc_loss_reduction
											UpperCamelCase   			=     ctc_zero_infinity

											# prevents config testing fail with exporting to json
											UpperCamelCase   			=     list(A_     )
											UpperCamelCase   			=     list(A_     )

											if len(self.conv_kernel     ) != self.num_conv_layers:
																		raise ValueError(
																		    'Configuration for convolutional module is incorrect. '
																		    'It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '
																		    F'''but is `len(config.conv_kernel) = {len(self.conv_kernel     )}`, '''
																		    F'''`config.num_conv_layers = {self.num_conv_layers}`.'''     )




