"""simple docstring"""






import math

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


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

lowerCAmelCase__  :  Optional[int]						     =	{
    'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json',
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					snake_case__				    = "data2vec-audio"







					def __init__(				self   :	int    ,lowerCamelCase__   :	List[str]=32    ,lowerCamelCase__   :	int=768    ,lowerCamelCase__   :	Optional[Any]=12    ,lowerCamelCase__   :	int=12    ,lowerCamelCase__   :	int=3_072    ,lowerCamelCase__   :	int="gelu"    ,lowerCamelCase__   :	Dict=0.1    ,lowerCamelCase__   :	Any=0.1    ,lowerCamelCase__   :	Dict=0.1    ,lowerCamelCase__   :	List[str]=0.0    ,lowerCamelCase__   :	List[str]=0.1    ,lowerCamelCase__   :	List[str]=0.1    ,lowerCamelCase__   :	Union[str, Any]=0.0_2    ,lowerCamelCase__   :	int=1e-5    ,lowerCamelCase__   :	Tuple="gelu"    ,lowerCamelCase__   :	Optional[int]=(512, 512, 512, 512, 512, 512, 512)    ,lowerCamelCase__   :	List[str]=(5, 2, 2, 2, 2, 2, 2)    ,lowerCamelCase__   :	str=(10, 3, 3, 3, 3, 2, 2)    ,lowerCamelCase__   :	int=False    ,lowerCamelCase__   :	Any=16    ,lowerCamelCase__   :	List[Any]=19    ,lowerCamelCase__   :	Any=5    ,lowerCamelCase__   :	Union[str, Any]=0.0_5    ,lowerCamelCase__   :	str=10    ,lowerCamelCase__   :	int=2    ,lowerCamelCase__   :	List[Any]=0.0    ,lowerCamelCase__   :	List[Any]=10    ,lowerCamelCase__   :	Dict=0    ,lowerCamelCase__   :	Optional[Any]="sum"    ,lowerCamelCase__   :	List[str]=False    ,lowerCamelCase__   :	Any=False    ,lowerCamelCase__   :	int=256    ,lowerCamelCase__   :	Any=(512, 512, 512, 512, 1_500)    ,lowerCamelCase__   :	Union[str, Any]=(5, 3, 3, 1, 1)    ,lowerCamelCase__   :	int=(1, 2, 3, 1, 1)    ,lowerCamelCase__   :	List[str]=512    ,lowerCamelCase__   :	Dict=0    ,lowerCamelCase__   :	Dict=1    ,lowerCamelCase__   :	Tuple=2    ,lowerCamelCase__   :	Optional[Any]=False    ,lowerCamelCase__   :	Optional[int]=3    ,lowerCamelCase__   :	Tuple=2    ,lowerCamelCase__   :	List[str]=3    ,lowerCamelCase__   :	int=None    ,**lowerCamelCase__   :	int    ,):
									super().__init__(**lowerCamelCase__    ,pad_token_id=lowerCamelCase__    ,bos_token_id=lowerCamelCase__    ,eos_token_id=lowerCamelCase__			)
									UpperCAmelCase__             =							hidden_size
									UpperCAmelCase__             =							feat_extract_activation
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							conv_bias
									UpperCAmelCase__             =							num_conv_pos_embeddings
									UpperCAmelCase__             =							num_conv_pos_embedding_groups
									UpperCAmelCase__             =							conv_pos_kernel_size
									UpperCAmelCase__             =							len(self.conv_dim			)
									UpperCAmelCase__             =							num_hidden_layers
									UpperCAmelCase__             =							intermediate_size
									UpperCAmelCase__             =							hidden_act
									UpperCAmelCase__             =							num_attention_heads
									UpperCAmelCase__             =							hidden_dropout
									UpperCAmelCase__             =							attention_dropout
									UpperCAmelCase__             =							activation_dropout
									UpperCAmelCase__             =							feat_proj_dropout
									UpperCAmelCase__             =							final_dropout
									UpperCAmelCase__             =							layerdrop
									UpperCAmelCase__             =							layer_norm_eps
									UpperCAmelCase__             =							initializer_range
									UpperCAmelCase__             =							vocab_size
									UpperCAmelCase__             =							use_weighted_layer_sum

									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)`, but is `len(config.conv_dim) ='
													    f''' {len(self.conv_dim			)}`, `len(config.conv_stride) = {len(self.conv_stride			)}`,'''
													    f''' `len(config.conv_kernel) = {len(self.conv_kernel			)}`.'''			)

									# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
									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

									# ctc loss
									UpperCAmelCase__             =							ctc_loss_reduction
									UpperCAmelCase__             =							ctc_zero_infinity

									# adapter
									UpperCAmelCase__             =							add_adapter
									UpperCAmelCase__             =							adapter_kernel_size
									UpperCAmelCase__             =							adapter_stride
									UpperCAmelCase__             =							num_adapter_layers
									UpperCAmelCase__             =							output_hidden_size or hidden_size

									# SequenceClassification-specific parameter. Feel free to ignore for other classes.
									UpperCAmelCase__             =							classifier_proj_size

									# XVector-specific parameters. Feel free to ignore for other classes.
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							list(lowerCamelCase__			)
									UpperCAmelCase__             =							xvector_output_dim







					@property
					def 		__lowerCAmelCase						(				self   :	Optional[Any]			):
									return math.prod(self.conv_stride			)




"""simple docstring"""






import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

lowerCAmelCase__  :  Optional[Any]						     =	logging.getLogger()



def   a_						(					):
				UpperCAmelCase__             =							argparse.ArgumentParser()
				parser.add_argument('-f'       )
				UpperCAmelCase__             =							parser.parse_args()
				return args.f







class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	int			):
									UpperCAmelCase__             =							logging.StreamHandler(sys.stdout			)
									logger.addHandler(lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	Optional[Any]    ,lowerCamelCase__   :	Union[str, Any]			):
									UpperCAmelCase__             =							get_gpu_count()

									if n_gpu > 1:
													pass
													# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
													# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
													# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
													# cmd = [sys.executable] + distributed_args + args
													# execute_subprocess_async(cmd, env=self.get_env())
													# XXX: test the results - need to save them first into .json file
									else:
													args.insert(0    ,'run_glue_deebert.py'			)
													with patch.object(lowerCamelCase__    ,'argv'    ,lowerCamelCase__			):
																	UpperCAmelCase__             =							run_glue_deebert.main()
																	for value in result.values():
																					self.assertGreaterEqual(lowerCamelCase__    ,0.6_6_6			)







					@slow
					@require_torch_non_multi_gpu
					def 		__lowerCAmelCase						(				self   :	List[str]			):
									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            '.split()
									self.run_and_check(lowerCamelCase__			)

									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
									self.run_and_check(lowerCamelCase__			)

									UpperCAmelCase__             =							'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
									self.run_and_check(lowerCamelCase__			)



