
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						:							Dict							=  logging.getLogger()
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					{}
			SCREAMING_SNAKE_CASE           =					os.path.join(SCREAMING_SNAKE_CASE					,	"""all_results.json"""   )
			if os.path.exists(SCREAMING_SNAKE_CASE   ):
						with open(SCREAMING_SNAKE_CASE					,	"""r"""   ) as f:
									SCREAMING_SNAKE_CASE           =					json.load(SCREAMING_SNAKE_CASE   )
			else:
						raise ValueError(f"""can't find {path}"""   )
			return results


__A						:							List[Any]							=  logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)




@require_torch_tpu
class 			UpperCAmelCase_      (   A       ):




							'''simple docstring'''



							def    _UpperCAmelCase     (					self       :	str			)			->					Union[str, Any]:
										import xla_spawn

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

										with patch.object(a       ,     """argv"""       ,     a			):
													SCREAMING_SNAKE_CASE           =					time()
													xla_spawn.main()
													SCREAMING_SNAKE_CASE           =					time()

													SCREAMING_SNAKE_CASE           =					get_results(a			)
													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       :	List[str]			)			->					List[str]:
										import xla_spawn

										SCREAMING_SNAKE_CASE           =					"""
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
										with patch.object(a       ,     """argv"""       ,     a			):
													xla_spawn.main()












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A						:							Dict							=  {
    """configuration_nllb_moe""": [
        """NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """NllbMoeConfig""",
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A						:							List[Any]							=  [
		    """NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """NllbMoeForConditionalGeneration""",
		    """NllbMoeModel""",
		    """NllbMoePreTrainedModel""",
		    """NllbMoeTop2Router""",
		    """NllbMoeSparseMLP""",
		]


if TYPE_CHECKING:
		from .configuration_nllb_moe import (
		    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    NllbMoeConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_nllb_moe import (
				    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    NllbMoeForConditionalGeneration,
				    NllbMoeModel,
				    NllbMoePreTrainedModel,
				    NllbMoeSparseMLP,
				    NllbMoeTopaRouter,
				)


else:
		import sys

		__A						:							Optional[Any]							=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






