
"""simple docstring"""





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

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

UpperCamelCase_       :    str						      =			logging.getLogger()
def 				A_  (__a					):

					'''simple docstring'''





					A_								=    {}
					A_								=    os.path.join(__a					, "all_results.json"					)
					if os.path.exists(__a					):
										with open(__a					, "r"					) as f:
															A_								=    json.load(__a					)
					else:
										raise ValueError(f'can\'t find {path}'					)
					return results


UpperCamelCase_       :    str						      =			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)




@require_torch_tpu
class __lowerCAmelCase					(       _lowercase   ):




			"""simple docstring"""







			def   lowerCamelCase__  (					self    :       str						)   ->			int:







								"""simple docstring"""
								import xla_spawn

								A_								=    self.get_auto_remove_tmp_dir()
								A_								=    F'\n            ./examples/pytorch/text-classification/run_glue.py\n            --num_cores=8\n            ./examples/pytorch/text-classification/run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --do_train\n            --do_eval\n            --debug tpu_metrics_debug\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --max_steps=10\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

								with patch.object(_snake_case							, "argv"							, _snake_case						):
													A_								=    time()
													xla_spawn.main()
													A_								=    time()

													A_								=    get_results(_snake_case						)
													self.assertGreaterEqual(result["eval_accuracy"]							, 0.7_5						)

													# Assert that the script takes less than 500 seconds to make sure it doesn't hang.
													self.assertLess(end - start							, 500						)






			def   lowerCamelCase__  (					self    :       Tuple						)   ->			List[Any]:







								"""simple docstring"""
								import xla_spawn

								A_								=    "\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            ".split()
								with patch.object(_snake_case							, "argv"							, _snake_case						):
													xla_spawn.main()






"""simple docstring"""





import argparse
import os
import re


UpperCamelCase_       :    Any						      =			'''src/transformers/models/auto'''


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCamelCase_       :    Optional[int]						      =			re.compile(R'''[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict''')
# re pattern that matches identifiers in mappings
UpperCamelCase_       :    Tuple						      =			re.compile(R'''\s*\(\s*"(\S[^"]+)"''')
def 				A_  (__a					, __a = False					):

					'''simple docstring'''





					with open(__a					, "r"					, encoding="utf-8"					) as f:
										A_								=    f.read()

					A_								=    content.split("\n"					)
					A_								=    []
					A_								=    0
					while line_idx < len(__a					):
										if _re_intro_mapping.search(lines[line_idx]					) is not None:
															A_								=    len(re.search(R"^(\s*)\S"					, lines[line_idx]					).groups()[0]					) + 8
															# Start of a new mapping!
															while not lines[line_idx].startswith(" " * indent + "("					):
																				new_lines.append(lines[line_idx]					)
																				line_idx += 1

															A_								=    []
															while lines[line_idx].strip() != "]":
																				# Blocks either fit in one line or not
																				if lines[line_idx].strip() == "(":
																									A_								=    line_idx
																									while not lines[line_idx].startswith(" " * indent + ")"					):
																														line_idx += 1
																									blocks.append("\n".join(lines[start_idx : line_idx + 1]					)					)
																				else:
																									blocks.append(lines[line_idx]					)
																				line_idx += 1

															# Sort blocks by their identifiers
															A_								=    sorted(__a					, key=lambda __a					: _re_identifier.search(__a					).groups()[0]					)
															new_lines += blocks
										else:
															new_lines.append(lines[line_idx]					)
															line_idx += 1

					if overwrite:
										with open(__a					, "w"					, encoding="utf-8"					) as f:
															f.write("\n".join(__a					)					)
					elif "\n".join(__a					) != content:
										return True
def 				A_  (__a = False					):

					'''simple docstring'''





					A_								=    [os.path.join(__a					, __a					) for f in os.listdir(__a					) if f.endswith(".py"					)]
					A_								=    [sort_auto_mapping(__a					, overwrite=__a					) for fname in fnames]

					if not overwrite and any(__a					):
										A_								=    [f for f, d in zip(__a					, __a					) if d]
										raise ValueError(
										    f'The following files have auto mappings that need sorting: {", ".join(__a					)}. Run `make style` to fix'
										    " this."					)


if __name__ == "__main__":
		UpperCamelCase_       :    str						      =			argparse.ArgumentParser()
		parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
		UpperCamelCase_       :    List[Any]						      =			parser.parse_args()

		sort_all_auto_mappings(not args.check_only)




