
import unittest

import pytest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    MBartaaTokenizerFast,
    MBartConfig,
    MBartForConditionalGeneration,
    TranslationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch, slow

from .test_pipelines_common import ANY
@is_pipeline_test
class    _UpperCamelCase(   unittest.TestCase				):
						__A:						int				   =      MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
						__A:						Optional[int]				   =      TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

						def 						a__ (					self		:			List[Any]	,						_lowerCamelCase		:			str	,						_lowerCamelCase		:			List[str]	,						_lowerCamelCase		:			Union[str, Any]			):
													if isinstance(model.config	,						_lowerCamelCase			):
																				_UpperCAmelCase       ,_UpperCAmelCase  :			Union[str, Any]	       =		list(tokenizer.lang_code_to_id.keys()			)[:2]
																				_UpperCAmelCase  :			Union[str, Any]	       =		TranslationPipeline(model=_lowerCamelCase	,						tokenizer=_lowerCamelCase	,						src_lang=_lowerCamelCase	,						tgt_lang=_lowerCamelCase			)
													else:
																				_UpperCAmelCase  :			List[str]	       =		TranslationPipeline(model=_lowerCamelCase	,						tokenizer=_lowerCamelCase			)
													return translator, ["Some string", "Some other text"]

						def 						a__ (					self		:			str	,						_lowerCamelCase		:			List[str]	,						_lowerCamelCase		:			str			):
													_UpperCAmelCase  :			List[str]	       =		translator("Some string"			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": ANY(_lowerCamelCase			)}]			)

													_UpperCAmelCase  :			Union[str, Any]	       =		translator(["Some string"]			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": ANY(_lowerCamelCase			)}]			)

													_UpperCAmelCase  :			List[Any]	       =		translator(["Some string", "other string"]			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": ANY(_lowerCamelCase			)}, {"translation_text": ANY(_lowerCamelCase			)}]			)

						@require_torch
						def 						a__ (					self		:			List[Any]			):
													_UpperCAmelCase  :			Optional[int]	       =		pipeline("translation_en_to_ro"	,						model="patrickvonplaten/t5-tiny-random"	,						framework="pt"			)
													_UpperCAmelCase  :			Tuple	       =		translator("This is a test string"	,						max_length=20			)
													self.assertEqual(
													    _lowerCamelCase	,						[
													        {
													            "translation_text": (
													                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
													                " Beide Beide"
													            )
													        }
													    ]	,						)

						@require_tf
						def 						a__ (					self		:			List[Any]			):
													_UpperCAmelCase  :			Dict	       =		pipeline("translation_en_to_ro"	,						model="patrickvonplaten/t5-tiny-random"	,						framework="tf"			)
													_UpperCAmelCase  :			List[Any]	       =		translator("This is a test string"	,						max_length=20			)
													self.assertEqual(
													    _lowerCamelCase	,						[
													        {
													            "translation_text": (
													                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
													                " Beide Beide"
													            )
													        }
													    ]	,						)

						@require_torch
						def 						a__ (					self		:			Any			):
													_UpperCAmelCase  :			Optional[int]	       =		pipeline("translation_en_to_de"	,						model="patrickvonplaten/t5-tiny-random"	,						framework="pt"			)
													_UpperCAmelCase  :			List[Any]	       =		translator("This is a test string"	,						max_length=20			)
													self.assertEqual(
													    _lowerCamelCase	,						[
													        {
													            "translation_text": (
													                "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
													                " urine urine urine urine urine urine urine"
													            )
													        }
													    ]	,						)






						@require_tf
						def 						a__ (					self		:			Dict			):
													_UpperCAmelCase  :			Union[str, Any]	       =		pipeline("translation_en_to_de"	,						model="patrickvonplaten/t5-tiny-random"	,						framework="tf"			)
													_UpperCAmelCase  :			str	       =		translator("This is a test string"	,						max_length=20			)
													self.assertEqual(
													    _lowerCamelCase	,						[
													        {
													            "translation_text": (
													                "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
													                " urine urine urine urine urine urine urine"
													            )
													        }
													    ]	,						)







class    _UpperCamelCase(   unittest.TestCase				):

						@require_torch
						@slow
						def 						a__ (					self		:			Dict			):
													# We don't provide a default for this pair
													with self.assertRaises(_lowerCamelCase			):
																				pipeline(task="translation_cn_to_ar"			)

													# but we do for this one
													_UpperCAmelCase  :			Dict	       =		pipeline(task="translation_en_to_de"			)
													self.assertEqual(translator._preprocess_params["src_lang"]	,						"en"			)
													self.assertEqual(translator._preprocess_params["tgt_lang"]	,						"de"			)

						@require_torch
						@slow
						def 						a__ (					self		:			Optional[int]			):
													_UpperCAmelCase  :			Optional[int]	       =		MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"			)
													_UpperCAmelCase  :			Union[str, Any]	       =		MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"			)

													_UpperCAmelCase  :			Dict	       =		pipeline(task="translation"	,						model=_lowerCamelCase	,						tokenizer=_lowerCamelCase			)
													# Missing src_lang, tgt_lang
													with self.assertRaises(_lowerCamelCase			):
																				translator("This is a test"			)

													_UpperCAmelCase  :			Dict	       =		translator("This is a test"	,						src_lang="en_XX"	,						tgt_lang="ar_AR"			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": "هذا إختبار"}]			)

													_UpperCAmelCase  :			Tuple	       =		translator("This is a test"	,						src_lang="en_XX"	,						tgt_lang="hi_IN"			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": "यह एक परीक्षण है"}]			)

													# src_lang, tgt_lang can be defined at pipeline call time
													_UpperCAmelCase  :			int	       =		pipeline(task="translation"	,						model=_lowerCamelCase	,						tokenizer=_lowerCamelCase	,						src_lang="en_XX"	,						tgt_lang="ar_AR"			)
													_UpperCAmelCase  :			Dict	       =		translator("This is a test"			)
													self.assertEqual(_lowerCamelCase	,						[{"translation_text": "هذا إختبار"}]			)

						@require_torch
						def 						a__ (					self		:			Optional[Any]			):
													_UpperCAmelCase  :			Union[str, Any]	       =		"patrickvonplaten/t5-tiny-random"
													_UpperCAmelCase  :			Dict	       =		pipeline(task="translation_cn_to_ar"	,						model=_lowerCamelCase			)
													self.assertEqual(translator._preprocess_params["src_lang"]	,						"cn"			)
													self.assertEqual(translator._preprocess_params["tgt_lang"]	,						"ar"			)

						@require_torch
						def 						a__ (					self		:			Dict			):
													_UpperCAmelCase  :			List[Any]	       =		"patrickvonplaten/t5-tiny-random"
													with pytest.warns(_lowerCamelCase	,						match=R".*translation_en_to_de.*"			):
																				_UpperCAmelCase  :			str	       =		pipeline(task="translation"	,						model=_lowerCamelCase			)
													self.assertEqual(translator.task	,						"translation_en_to_de"			)
													self.assertEqual(translator._preprocess_params["src_lang"]	,						"en"			)
													self.assertEqual(translator._preprocess_params["tgt_lang"]	,						"de"			)






						@require_torch
						def 						a__ (					self		:			int			):
													with self.assertRaises(_lowerCamelCase			):
																				pipeline(task="translation"			)






import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
				from PIL import Image
class    _UpperCamelCase(   unittest.TestCase		,						SCREAMING_SNAKE_CASE				):

						def 						a__ (					self		:			Optional[int]			):
													_UpperCAmelCase  :			Any	       =		load_tool("image-captioning"			)
													self.tool.setup()
													_UpperCAmelCase  :			Optional[Any]	       =		load_tool("image-captioning"	,						remote=_lowerCamelCase			)

						def 						a__ (					self		:			int			):
													_UpperCAmelCase  :			Optional[int]	       =		Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
													_UpperCAmelCase  :			Optional[int]	       =		self.tool(_lowerCamelCase			)
													self.assertEqual(_lowerCamelCase	,						"two cats sleeping on a couch"			)

						def 						a__ (					self		:			str			):
													_UpperCAmelCase  :			List[str]	       =		Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
													_UpperCAmelCase  :			Optional[Any]	       =		self.remote_tool(_lowerCamelCase			)
													self.assertEqual(_lowerCamelCase	,						"two cats sleeping on a couch"			)

						def 						a__ (					self		:			Union[str, Any]			):
													_UpperCAmelCase  :			Any	       =		Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
													_UpperCAmelCase  :			Union[str, Any]	       =		self.tool(image=_lowerCamelCase			)
													self.assertEqual(_lowerCamelCase	,						"two cats sleeping on a couch"			)






						def 						a__ (					self		:			Optional[int]			):
													_UpperCAmelCase  :			str	       =		Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
													_UpperCAmelCase  :			str	       =		self.remote_tool(image=_lowerCamelCase			)
													self.assertEqual(_lowerCamelCase	,						"two cats sleeping on a couch"			)




