






from collections import namedtuple

a_							=    namedtuple('''from_to''', '''from_ to''')

a_							=    {
    '''cubicmeter''': from_to(1, 1),
    '''litre''': from_to(0.001, 1000),
    '''kilolitre''': from_to(1, 1),
    '''gallon''': from_to(0.00454, 264.172),
    '''cubicyard''': from_to(0.76455, 1.30795),
    '''cubicfoot''': from_to(0.028, 35.3147),
    '''cup''': from_to(0.000236588, 4226.75),
}


def        _a  (     UpperCamelCase_					:				float    ,   UpperCamelCase_					:				str    ,   UpperCamelCase_					:				str   ) ->   float:
						"""simple docstring"""







						if from_type not in METRIC_CONVERSION:
												raise ValueError(
												    F"Invalid 'from_type' value: {from_type!r}  Supported values are:\n"
												    + ", ".join(UpperCamelCase_   )   )
						if to_type not in METRIC_CONVERSION:
												raise ValueError(
												    F"Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"
												    + ", ".join(UpperCamelCase_   )   )
						return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
	import doctest

	doctest.testmod()














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)

a_							=    logging.getLogger()


def        _a  (     UpperCamelCase_					:				Union[str, Any]   ) ->   Dict:
						"""simple docstring"""







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


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





@require_torch_tpu
class      lowercase__     (			_UpperCAmelCase	):

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						self.get_auto_remove_tmp_dir()
							lowerCAmelCase__       =						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(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													lowerCAmelCase__       =						time()
													xla_spawn.main()
													lowerCAmelCase__       =						time()

													lowerCAmelCase__       =						get_results(__UpperCAmelCase       )
													self.assertGreaterEqual(result["eval_accuracy"]		,    0.75       )

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


	def 		UpperCAmelCase  (							self       )->					Dict:







							'''simple docstring'''





							import xla_spawn

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






