





import io
import json
import unittest

from parameterized import parameterized

from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu


SCREAMING_SNAKE_CASE_		     = get_tests_dir() + """/test_data/fsmt/fsmt_val_data.json"""
with io.open(filename, """r""", encoding="""utf-8""") as f:
						SCREAMING_SNAKE_CASE_		     = json.load(f)

@require_torch
class 	UpperCamelCase__				(   unittest.TestCase     ):



					'''simple docstring'''

					def        SCREAMING_SNAKE_CASE__						(							self		:					Union[str, Any]		,lowerCamelCase__		:					int )  ->	Union[str, Any]:




											'''simple docstring'''


											return FSMTTokenizer.from_pretrained(_lowercase )






					def        SCREAMING_SNAKE_CASE__						(							self		:					List[str]		,lowerCamelCase__		:					Tuple )  ->	str:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		FSMTForConditionalGeneration.from_pretrained(_lowercase ).to(_lowercase )
											if torch_device == "cuda":
																	model.half()
											return model






					@parameterized.expand(
					    [
					        ["""en-ru""", 26.0],
					        ["""ru-en""", 22.0],
					        ["""en-de""", 22.0],
					        ["""de-en""", 29.0],
					    ] )
					@slow
					def        SCREAMING_SNAKE_CASE__						(							self		:					Tuple		,lowerCamelCase__		:					Union[str, Any]		,lowerCamelCase__		:					Tuple )  ->	int:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		F"""facebook/wmt19-{pair}"""
											SCREAMING_SNAKE_CASE	=		self.get_tokenizer(_lowercase )
											SCREAMING_SNAKE_CASE	=		self.get_model(_lowercase )

											SCREAMING_SNAKE_CASE	=		bleu_data[pair]["""src"""]
											SCREAMING_SNAKE_CASE	=		bleu_data[pair]["""tgt"""]

											SCREAMING_SNAKE_CASE	=		tokenizer(_lowercase		,return_tensors="""pt"""		,truncation=_lowercase		,padding="""longest""" ).to(_lowercase )
											SCREAMING_SNAKE_CASE	=		model.generate(
											    input_ids=batch.input_ids		,num_beams=8		,)
											SCREAMING_SNAKE_CASE	=		tokenizer.batch_decode(
											    _lowercase		,skip_special_tokens=_lowercase		,clean_up_tokenization_spaces=_lowercase )
											SCREAMING_SNAKE_CASE	=		calculate_bleu(_lowercase		,_lowercase )
											print(_lowercase )
											self.assertGreaterEqual(scores["""bleu"""]		,_lowercase )









import pytest

from datasets import inspect_metric, list_metrics, load_metric



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     List[Any]:


      '''simple docstring'''


      monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings"""				,		set()			)



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     Dict:


      '''simple docstring'''


      class 	UpperCamelCase__				:



           '''simple docstring'''

           def __init__(							self		:					int		,lowerCamelCase__		:					Dict )  ->	List[Any]:




                 '''simple docstring'''


                 SCREAMING_SNAKE_CASE	=		metric_id

      class 	UpperCamelCase__				:



           '''simple docstring'''

           __snake_case					:			List[str]				=    [MetricMock(lowerCAmelCase_     ) for metric_id in ["accuracy", "mse", "precision", "codeparrot/apps_metric"]]






           def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	str:




                 '''simple docstring'''


                 return self._metrics
      monkeypatch.setattr("""datasets.inspect.huggingface_hub"""				,		HfhMock()			)



@pytest.mark.parametrize(
    """func, args"""				,		[(load_metric, ("""metrics/mse""",)), (list_metrics, ()), (inspect_metric, ("""metrics/mse""", """tmp_path"""))]			)
def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     Union[str, Any]:


      '''simple docstring'''


      if "tmp_path" in args:
            SCREAMING_SNAKE_CASE	=		tuple(arg if arg != """tmp_path""" else tmp_path for arg in args			)
      with pytest.warns(_SCREAMING_SNAKE_CASE				,		match="""https://huggingface.co/docs/evaluate"""			):
            func(*_SCREAMING_SNAKE_CASE			)


