




"""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)

_A													=      logging.getLogger()



def 	lowercase_				(			):
      lowerCAmelCase__      :			Optional[Any]   =	argparse.ArgumentParser()
      parser.add_argument("""-f"""				)
      lowerCAmelCase__      :			Any   =	parser.parse_args()
      return args.f


class _lowerCamelCase    (					a_						):






   def 	_lowerCAmelCase   (		self       :		List[str]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	logging.StreamHandler(sys.stdout   )
         logger.addHandler(lowercase_   )






   def 	_lowerCAmelCase   (		self       :		Optional[int]   ,     UpperCamelCase       :		List[str]   )			->						Union[str, Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	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(lowercase_   ,     """argv"""   ,     lowercase_   ):
                     lowerCAmelCase__      :			Optional[Any]   =	run_glue_deebert.main()
                     for value in result.values():
                           self.assertGreaterEqual(lowercase_   ,     0.666   )






   @slow
   @require_torch_non_multi_gpu
   def 	_lowerCAmelCase   (		self       :		Tuple   )			->						Optional[int]:

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	"""\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(lowercase_   )

         lowerCAmelCase__      :			Optional[int]   =	"""\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(lowercase_   )

         lowerCAmelCase__      :			Tuple   =	"""\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(lowercase_   )











"""simple docstring"""


from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *





