
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_  :	Dict 				=					logging.getLogger()







def     A__   (  )					->		Union[str, Any]:
				UpperCamelCase_:							List[Any]		=  argparse.ArgumentParser()
				parser.add_argument("""-f"""  )
				UpperCamelCase_:							Any		=  parser.parse_args()
				return args.f





class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			def  lowerCAmelCase__		(    self	:    Dict ):
							UpperCamelCase_:							Tuple		=  logging.StreamHandler(sys.stdout )
							logger.addHandler(snake_case_ )

			def  lowerCAmelCase__		(    self	:    str  ,		snake_case_	:    Dict ):
							UpperCamelCase_:							Any		=  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(snake_case_  ,		"""argv"""  ,		snake_case_ ):
															UpperCamelCase_:							int		=  run_glue_deebert.main()
															for value in result.values():
																			self.assertGreaterEqual(snake_case_  ,		0.666 )




			@slow
			@require_torch_non_multi_gpu
			def  lowerCAmelCase__		(    self	:    Optional[int] ):
							UpperCamelCase_:							Any		=  """
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            """.split()
							self.run_and_check(snake_case_ )

							UpperCamelCase_:							Dict		=  """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
							self.run_and_check(snake_case_ )

							UpperCamelCase_:							List[str]		=  """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
							self.run_and_check(snake_case_ )








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


lowerCamelCase_  :	Optional[int] 				=					logging.get_logger(__name__)

lowerCamelCase_  :	Dict 				=					{
    """studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""",
    """studio-ousia/luke-large""": """https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json""",
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  Optional[int]    =	"""luke"""

			def __init__(    self	:    Tuple  ,		snake_case_	:    List[Any]=5_0267  ,		snake_case_	:    Any=50_0000  ,		snake_case_	:    str=768  ,		snake_case_	:    int=256  ,		snake_case_	:    str=12  ,		snake_case_	:    int=12  ,		snake_case_	:    Dict=3072  ,		snake_case_	:    Optional[Any]="gelu"  ,		snake_case_	:    Dict=0.1  ,		snake_case_	:    List[str]=0.1  ,		snake_case_	:    int=512  ,		snake_case_	:    Dict=2  ,		snake_case_	:    List[Any]=0.02  ,		snake_case_	:    int=1e-12  ,		snake_case_	:    Union[str, Any]=True  ,		snake_case_	:    Union[str, Any]=None  ,		snake_case_	:    Dict=1  ,		snake_case_	:    Optional[int]=0  ,		snake_case_	:    List[str]=2  ,		**snake_case_	:    Union[str, Any]  ,		):
							super().__init__(pad_token_id=snake_case_  ,		bos_token_id=snake_case_  ,		eos_token_id=snake_case_  ,		**snake_case_ )

							UpperCamelCase_:							Dict		=  vocab_size
							UpperCamelCase_:							Tuple		=  entity_vocab_size
							UpperCamelCase_:							Optional[int]		=  hidden_size
							UpperCamelCase_:							Any		=  entity_emb_size
							UpperCamelCase_:							str		=  num_hidden_layers
							UpperCamelCase_:							Union[str, Any]		=  num_attention_heads
							UpperCamelCase_:							Dict		=  hidden_act
							UpperCamelCase_:							Dict		=  intermediate_size
							UpperCamelCase_:							str		=  hidden_dropout_prob
							UpperCamelCase_:							List[str]		=  attention_probs_dropout_prob
							UpperCamelCase_:							int		=  max_position_embeddings
							UpperCamelCase_:							int		=  type_vocab_size
							UpperCamelCase_:							List[Any]		=  initializer_range
							UpperCamelCase_:							Union[str, Any]		=  layer_norm_eps
							UpperCamelCase_:							Tuple		=  use_entity_aware_attention
							UpperCamelCase_:							int		=  classifier_dropout






