



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


_snake_case	=						[
    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)

_snake_case	=						logging.getLogger()






def        A       (      ):





							'''simple docstring'''




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






def        A       (      _lowerCamelCase       ,				_lowerCamelCase="eval"						):





							'''simple docstring'''




							_lowerCAmelCase  :							Dict				     =					os.path.join(_lowerCamelCase       ,				F"{split}_results.json"						)
							if os.path.exists(_lowerCamelCase						):
														with open(_lowerCamelCase       ,				"r"						) as f:
																					return json.load(_lowerCamelCase						)
							raise ValueError(F"can't find {path}"						)


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



class 						UpperCAmelCase_					( a):







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							List[Any]				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							List[Any]				     =					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(__a,    "argv",    __a):
																					run_flax_glue.main()
																					_lowerCAmelCase  :							List[str]				     =					get_results(__a)
																					self.assertGreaterEqual(result["eval_accuracy"],    0.75)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Any				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							Optional[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(__a,    "argv",    __a):
																					run_clm_flax.main()
																					_lowerCAmelCase  :							int				     =					get_results(__a)
																					self.assertLess(result["eval_perplexity"],    100)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[int]				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							Tuple				     =					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(__a,    "argv",    __a):
																					run_summarization_flax.main()
																					_lowerCAmelCase  :							Optional[int]				     =					get_results(__a,    split="test")
																					self.assertGreaterEqual(result["test_rouge1"],    10)
																					self.assertGreaterEqual(result["test_rouge2"],    2)
																					self.assertGreaterEqual(result["test_rougeL"],    7)
																					self.assertGreaterEqual(result["test_rougeLsum"],    7)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Dict				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							Optional[int]				     =					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(__a,    "argv",    __a):
																					run_mlm_flax.main()
																					_lowerCAmelCase  :							Dict				     =					get_results(__a)
																					self.assertLess(result["eval_perplexity"],    42)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							int				     =					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(__a,    "argv",    __a):
																					run_ta_mlm_flax.main()
																					_lowerCAmelCase  :							Optional[int]				     =					get_results(__a)
																					self.assertGreaterEqual(result["eval_accuracy"],    0.42)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							int				     =					7 if get_gpu_count() > 1 else 2

														_lowerCAmelCase  :							Optional[int]				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							int				     =					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(__a,    "argv",    __a):
																					run_flax_ner.main()
																					_lowerCAmelCase  :							Optional[int]				     =					get_results(__a)
																					self.assertGreaterEqual(result["eval_accuracy"],    0.75)
																					self.assertGreaterEqual(result["eval_f1"],    0.3)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							int				     =					self.get_auto_remove_tmp_dir()
														_lowerCAmelCase  :							Dict				     =					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(__a,    "argv",    __a):
																					run_qa.main()
																					_lowerCAmelCase  :							int				     =					get_results(__a)
																					self.assertGreaterEqual(result["eval_f1"],    30)
																					self.assertGreaterEqual(result["eval_exact"],    30)





import baseaa






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							return baseaa.aaaencode(string.encode("utf-8"						)						)






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							return baseaa.aaadecode(_lowerCamelCase						).decode("utf-8"						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
