



'''simple docstring'''




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__       :	List[str]    = [
    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__       :	Union[str, Any]    = logging.getLogger()


def 				lowerCAmelCase_   (	):
		__SCREAMING_SNAKE_CASE       :		Any           =		argparse.ArgumentParser()
		parser.add_argument("""-f"""					)
		__SCREAMING_SNAKE_CASE       :		List[str]           =		parser.parse_args()
		return args.f


def 				lowerCAmelCase_   (	_lowerCamelCase:   List[Any]       ,      _lowerCamelCase:   Optional[Any]="eval"					):
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		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}"					)


UpperCamelCase__       :	List[str]    = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			def UpperCamelCase__					(							self     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Dict           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_flax_glue.main()
							__SCREAMING_SNAKE_CASE       :		Tuple           =		get_results(lowerCAmelCase__						)
							self.assertGreaterEqual(result["""eval_accuracy"""]							,     0.75						)

			@slow
			def UpperCamelCase__					(							self     : Any						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		Dict           =		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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_clm_flax.main()
							__SCREAMING_SNAKE_CASE       :		List[Any]           =		get_results(lowerCAmelCase__						)
							self.assertLess(result["""eval_perplexity"""]							,     1_0_0						)

			@slow
			def UpperCamelCase__					(							self     : Optional[int]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Dict           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_summarization_flax.main()
							__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		get_results(lowerCAmelCase__							,     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     : List[str]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		int           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_mlm_flax.main()
							__SCREAMING_SNAKE_CASE       :		Optional[int]           =		get_results(lowerCAmelCase__						)
							self.assertLess(result["""eval_perplexity"""]							,     4_2						)

			@slow
			def UpperCamelCase__					(							self     : Dict						):





					"""simple docstring"""






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

			@slow
			def UpperCamelCase__					(							self     : int						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		7 if get_gpu_count() > 1 else 2

					__SCREAMING_SNAKE_CASE       :		int           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		Optional[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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_flax_ner.main()
							__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		get_results(lowerCAmelCase__						)
							self.assertGreaterEqual(result["""eval_accuracy"""]							,     0.75						)
							self.assertGreaterEqual(result["""eval_f1"""]							,     0.3						)



			@slow
			def UpperCamelCase__					(							self     : Tuple						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		self.get_auto_remove_tmp_dir()
					__SCREAMING_SNAKE_CASE       :		Tuple           =		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(lowerCAmelCase__							,     """argv"""							,     lowerCAmelCase__						):
							run_qa.main()
							__SCREAMING_SNAKE_CASE       :		Optional[int]           =		get_results(lowerCAmelCase__						)
							self.assertGreaterEqual(result["""eval_f1"""]							,     3_0						)
							self.assertGreaterEqual(result["""eval_exact"""]							,     3_0						)




'''simple docstring'''




import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCamelCase__       :	List[Any]    = {
    '''E''': 1_2.7_0,
    '''T''': 9.0_6,
    '''A''': 8.1_7,
    '''O''': 7.5_1,
    '''I''': 6.9_7,
    '''N''': 6.7_5,
    '''S''': 6.3_3,
    '''H''': 6.0_9,
    '''R''': 5.9_9,
    '''D''': 4.2_5,
    '''L''': 4.0_3,
    '''C''': 2.7_8,
    '''U''': 2.7_6,
    '''M''': 2.4_1,
    '''W''': 2.3_6,
    '''F''': 2.2_3,
    '''G''': 2.0_2,
    '''Y''': 1.9_7,
    '''P''': 1.9_3,
    '''B''': 1.2_9,
    '''V''': 0.9_8,
    '''K''': 0.7_7,
    '''J''': 0.1_5,
    '''X''': 0.1_5,
    '''Q''': 0.1_0,
    '''Z''': 0.0_7,
}
UpperCamelCase__       :	Optional[Any]    = '''ETAOINSHRDLCUMWFGYPBVKJXQZ'''
UpperCamelCase__       :	Dict    = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''


def 				lowerCAmelCase_   (	_lowerCamelCase:   str					):
		__SCREAMING_SNAKE_CASE       :		int           =		{letter: 0 for letter in string.ascii_uppercase}
		for letter in message.upper():
				if letter in LETTERS:
						letter_count[letter] += 1

		return letter_count


def 				lowerCAmelCase_   (	_lowerCamelCase:   tuple					):
		return x[0]


def 				lowerCAmelCase_   (	_lowerCamelCase:   str					):
		__SCREAMING_SNAKE_CASE       :		Dict           =		get_letter_count(_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       :		dict[int, list[str]]           =		{
		    freq: [] for letter, freq in letter_to_freq.items()
		}
		for letter in LETTERS:
				freq_to_letter[letter_to_freq[letter]].append(_lowerCamelCase					)

		__SCREAMING_SNAKE_CASE       :		dict[int, str]           =		{}

		for freq in freq_to_letter:
				freq_to_letter[freq].sort(key=ETAOIN.find       ,      reverse=_lowerCamelCase					)
				__SCREAMING_SNAKE_CASE       :		Tuple           =		"""""".join(freq_to_letter[freq]					)

		__SCREAMING_SNAKE_CASE       :		str           =		list(freq_to_letter_str.items()					)
		freq_pairs.sort(key=_lowerCamelCase       ,      reverse=_lowerCamelCase					)

		__SCREAMING_SNAKE_CASE       :		list[str]           =		[freq_pair[1] for freq_pair in freq_pairs]

		return "".join(_lowerCamelCase					)


def 				lowerCAmelCase_   (	_lowerCamelCase:   str					):
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		get_frequency_order(_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		0
		for common_letter in ETAOIN[:6]:
				if common_letter in freq_order[:6]:
						match_score += 1

		for uncommon_letter in ETAOIN[-6:]:
				if uncommon_letter in freq_order[-6:]:
						match_score += 1

		return match_score


if __name__ == "__main__":
						import doctest

						doctest.testmod()