


import unittest

from transformers import DonutProcessor


SCREAMING_SNAKE_CASE							    =							'naver-clova-ix/donut-base'


class     __UpperCAmelCase							(       unittest.TestCase							):


     """simple docstring"""


     def 	snake_case_  (	self    ):
        __a					=  DonutProcessor.from_pretrained(__A    )


     def 	snake_case_  (	self    ):
        __a					=  {
            """name""": """John Doe""",
            """age""": """99""",
            """city""": """Atlanta""",
            """state""": """GA""",
            """zip""": """30301""",
            """phone""": """123-4567""",
            """nicknames""": [{"""nickname""": """Johnny"""}, {"""nickname""": """JD"""}],
        }

        __a					=  (
            """<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"""
            """<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"""
            """<s_nicknames><s_nickname>Johnny</s_nickname>"""
            """<sep/><s_nickname>JD</s_nickname></s_nicknames>"""
        )
        __a					=  self.processor.tokenajson(__A    )

        self.assertDictEqual(__A  ,       __A    )











"""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_							      = logging.getLogger()

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







class      UpperCamelCase_			(__A	):





	def 	_SCREAMING_SNAKE_CASE ( self   :					str		)		->     None:
				UpperCAmelCase_	:					List[str]     	=   logging.StreamHandler(sys.stdout		)
				logger.addHandler(lowerCAmelCase_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					int      ,      lowerCAmelCase_   :					List[str]		)		->     Tuple:
				UpperCAmelCase_	:					Optional[int]     	=   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_	:					Dict     	=   run_glue_deebert.main()
										for value in result.values():
													self.assertGreaterEqual(lowerCAmelCase_      ,      0.6_6_6		)





	@slow
	@require_torch_non_multi_gpu
	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     int:
				UpperCAmelCase_	:					Tuple     	=   "\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_	:					Union[str, Any]     	=   "\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_	:					str     	=   "\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_		)



