





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)

UpperCAmelCase__   : List[str]         =       logging.getLogger()


def  A							(			)					->				int:
 '''simple docstring'''
 __snake_case         =			argparse.ArgumentParser()
 parser.add_argument('-f'				)
 __snake_case         =			parser.parse_args()
 return args.f







class 							__lowercase			(     snake_case_       ):






      def 			_a						(		self)     ->       List[Any]:
       __snake_case         =			logging.StreamHandler(sys.stdout)
       logger.addHandler(lowercase__)






      def 			_a						(		self			,							lowercase_)     ->       List[Any]:
       __snake_case         =			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__):
         __snake_case         =			run_glue_deebert.main()
         for value in result.values():
          self.assertGreaterEqual(lowercase__			,							0.666)







      @slow
      @require_torch_non_multi_gpu
      def 			_a						(		self)     ->       Tuple:
       __snake_case         =			"""
            --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(lowercase__)

       __snake_case         =			"""
            --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(lowercase__)

       __snake_case         =			"""
            --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(lowercase__)







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowerCAmelCase_      :  Optional[Any]				     =  {}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  Any				     =  ['GPTSw3Tokenizer']


if TYPE_CHECKING:
 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_gpt_swa import GPTSwaTokenizer

else:
 import sys

 lowerCAmelCase_      :  int				     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
