






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

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


__UpperCAmelCase     							=						[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        'text-classification',
        'language-modeling',
        'summarization',
        'token-classification',
        'question-answering',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
		import run_clm_flax
		import run_flax_glue
		import run_flax_ner
		import run_mlm_flax
		import run_qa
		import run_summarization_flax
		import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

__UpperCAmelCase     							=						logging.getLogger()




def 					lowercase__				(					):


					'''simple docstring'''


					UpperCAmelCase_   :				Dict						=						argparse.ArgumentParser()
					parser.add_argument('-f'  )
					UpperCAmelCase_   :				List[str]						=						parser.parse_args()
					return args.f




def 					lowercase__				(					__snake_case   :							Optional[int]					,	__snake_case   :							List[str]="eval"  ):


					'''simple docstring'''


					UpperCAmelCase_   :				List[str]						=						os.path.join(__snake_case					,	F"{split}_results.json"  )
					if os.path.exists(__snake_case  ):
										with open(__snake_case					,	'r'  ) as f:
															return json.load(__snake_case  )
					raise ValueError(F"can't find {path}"  )


__UpperCAmelCase     							=						logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)






class   lowerCamelCase				(_snake_case      ):







		'''simple docstring'''



		def  __UpperCAmelCase      (							self       )     ->							List[Any]:
							UpperCAmelCase_   :				List[Any]						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Optional[int]						=						f"\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_flax_glue.main()
												UpperCAmelCase_   :				int						=						get_results(_UpperCamelCase       )
												self.assertGreaterEqual(result['eval_accuracy']    ,		0.75       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							List[str]:
							UpperCAmelCase_   :				List[str]						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Union[str, Any]						=						f"\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_clm_flax.main()
												UpperCAmelCase_   :				Optional[Any]						=						get_results(_UpperCamelCase       )
												self.assertLess(result['eval_perplexity']    ,		1_0_0       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							Optional[int]:
							UpperCAmelCase_   :				List[str]						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Union[str, Any]						=						f"\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_summarization_flax.main()
												UpperCAmelCase_   :				int						=						get_results(_UpperCamelCase    ,		split='test'       )
												self.assertGreaterEqual(result['test_rouge1']    ,		1_0       )
												self.assertGreaterEqual(result['test_rouge2']    ,		2       )
												self.assertGreaterEqual(result['test_rougeL']    ,		7       )
												self.assertGreaterEqual(result['test_rougeLsum']    ,		7       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							Tuple:
							UpperCAmelCase_   :				Tuple						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Optional[Any]						=						f"\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_mlm_flax.main()
												UpperCAmelCase_   :				int						=						get_results(_UpperCamelCase       )
												self.assertLess(result['eval_perplexity']    ,		4_2       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							Union[str, Any]:
							UpperCAmelCase_   :				Dict						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Union[str, Any]						=						f"\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_ta_mlm_flax.main()
												UpperCAmelCase_   :				Any						=						get_results(_UpperCamelCase       )
												self.assertGreaterEqual(result['eval_accuracy']    ,		0.42       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							List[str]:
							# with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
							UpperCAmelCase_   :				Any						=						7 if get_gpu_count() > 1 else 2

							UpperCAmelCase_   :				Any						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Any						=						f"\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_flax_ner.main()
												UpperCAmelCase_   :				Union[str, Any]						=						get_results(_UpperCamelCase       )
												self.assertGreaterEqual(result['eval_accuracy']    ,		0.75       )
												self.assertGreaterEqual(result['eval_f1']    ,		0.3       )



		@slow
		def  __UpperCAmelCase      (							self       )     ->							Dict:
							UpperCAmelCase_   :				str						=						self.get_auto_remove_tmp_dir()
							UpperCAmelCase_   :				Optional[int]						=						f"\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        ".split()

							with patch.object(_UpperCamelCase    ,		'argv'    ,		_UpperCamelCase       ):
												run_qa.main()
												UpperCAmelCase_   :				str						=						get_results(_UpperCamelCase       )
												self.assertGreaterEqual(result['eval_f1']    ,		3_0       )
												self.assertGreaterEqual(result['eval_exact']    ,		3_0       )














def 					lowercase__				(					__snake_case   :							List[str]					,	__snake_case   :							List[str]					,	__snake_case   :							Union[str, Any]					,	__snake_case   :							Optional[int]					,	__snake_case   :							str					,	__snake_case   :							Optional[Any]  ):


					'''simple docstring'''


					if index == r:
										for j in range(__snake_case  ):
															print(data[j]					,	end=' '  )
										print(' '  )
										return
					#  When no more elements are there to put in data[]
					if i >= n:
										return
					# current is included, put next at next location
					UpperCAmelCase_   :				int						=						arr[i]
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	index + 1					,	__snake_case					,	i + 1  )
					# current is excluded, replace it with
					# next (Note that i+1 is passed, but
					# index is not changed)
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	__snake_case					,	__snake_case					,	i + 1  )
					# The main function that prints all combinations
					# of size r in arr[] of size n. This function
					# mainly uses combinationUtil()




def 					lowercase__				(					__snake_case   :							List[Any]					,	__snake_case   :							List[Any]					,	__snake_case   :							str  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Union[str, Any]						=						[0] * r
					# Print all combination using temporary array 'data[]'
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	0					,	__snake_case					,	0  )


if __name__ == "__main__":
		# Driver code to check the function above
		__UpperCAmelCase     							=						[10, 20, 30, 40, 50]
		print_combination(arr, len(arr), 3)
		# This code is contributed by Ambuj sahu






