






# 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 							a_				(		a_	):


							'''simple docstring'''






							@classmethod
							def   _lowercase (	cls     )      ->      List[str]:
														'''simple docstring'''

														return cls






							@slow
							@require_torch_gpu
							def   _lowercase (	self     )      ->      List[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_auto_remove_tmp_dir()
														lowerCAmelCase_       		=  f'''
            --model_name Helsinki-NLP/opus-mt-en-ro
            --save_dir {output_dir}
            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
            --num_beams 2
            --task translation
        '''.split()

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

														lowerCAmelCase_       		=  os.path.join(lowercase_    ,    'test_bleu.json'     )
														lowerCAmelCase_       		=  load_json(lowercase_     )
														# print(metrics)
														self.assertGreaterEqual(metrics['bleu']    ,    2_5     )











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_		  =						{
    """configuration_prophetnet""": ["""PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ProphetNetConfig"""],
    """tokenization_prophetnet""": ["""ProphetNetTokenizer"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase_		  =						[
		    """PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """ProphetNetDecoder""",
		    """ProphetNetEncoder""",
		    """ProphetNetForCausalLM""",
		    """ProphetNetForConditionalGeneration""",
		    """ProphetNetModel""",
		    """ProphetNetPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
		from .tokenization_prophetnet import ProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_prophetnet import (
				    PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ProphetNetDecoder,
				    ProphetNetEncoder,
				    ProphetNetForCausalLM,
				    ProphetNetForConditionalGeneration,
				    ProphetNetModel,
				    ProphetNetPreTrainedModel,
				)

else:
		import sys

		lowerCamelCase_		  =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



