



# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json






class 				SCREAMING_SNAKE_CASE     (							lowerCamelCase__   ):





							@classmethod
							def   UpperCamelCase_   (				cls						:						List[str]		):

											'''simple docstring'''
											return cls







							@slow
							@require_torch_gpu
							def   UpperCamelCase_   (				self						:						Dict		):

											'''simple docstring'''
											__a					       =						self.get_auto_remove_tmp_dir()
											__a					       =						F"\n            --model_name Helsinki-NLP/opus-mt-en-ro\n            --save_dir {output_dir}\n            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro\n            --num_beams 2\n            --task translation\n        ".split()

											# we want this test to run even if there is only one GPU, but if there are more we use them all
											__a					       =						get_gpu_count()
											__a					       =						F"\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        ".split()
											__a					       =						[sys.executable] + distributed_args + args
											execute_subprocess_async(__lowercase ,			env=self.get_env()		)

											__a					       =						os.path.join(__lowercase ,			"""test_bleu.json"""		)
											__a					       =						load_json(__lowercase		)
											# print(metrics)
											self.assertGreaterEqual(metrics["""bleu"""] ,			25		)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase__     =	{
    """configuration_oneformer""": ["""ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OneFormerConfig"""],
    """processing_oneformer""": ["""OneFormerProcessor"""],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__     =	["""OneFormerImageProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__     =	[
						    """ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """OneFormerForUniversalSegmentation""",
						    """OneFormerModel""",
						    """OneFormerPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
						from .processing_oneformer import OneFormerProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_oneformer import OneFormerImageProcessor
						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_oneformer import (
												    ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    OneFormerForUniversalSegmentation,
												    OneFormerModel,
												    OneFormerPreTrainedModel,
												)


else:
						import sys

						lowerCamelCase__     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)
