


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 	__a   (       unittest.TestCase    ):
		_a			:						List[Any]    			=			MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		_a			:						Optional[Any]    			=			TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		)				-> Tuple:




									"""simple docstring"""





									if isinstance(model.config    ,					_lowerCAmelCase		):
																_UpperCAmelCase					=    list(tokenizer.lang_code_to_id.keys()		)[:2]
																_UpperCAmelCase					=    TranslationPipeline(model=_lowerCAmelCase    ,					tokenizer=_lowerCAmelCase    ,					src_lang=_lowerCAmelCase    ,					tgt_lang=_lowerCAmelCase		)
									else:
																_UpperCAmelCase					=    TranslationPipeline(model=_lowerCAmelCase    ,					tokenizer=_lowerCAmelCase		)
									return translator, ["Some string", "Some other text"]
		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		)				-> Optional[Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    translator('Some string'		)
									self.assertEqual(_lowerCAmelCase    ,					[{'translation_text': ANY(_lowerCAmelCase		)}]		)

									_UpperCAmelCase					=    translator(['Some string']		)
									self.assertEqual(_lowerCAmelCase    ,					[{'translation_text': ANY(_lowerCAmelCase		)}]		)

									_UpperCAmelCase					=    translator(['Some string', 'other string']		)
									self.assertEqual(_lowerCAmelCase    ,					[{'translation_text': ANY(_lowerCAmelCase		)}, {'translation_text': ANY(_lowerCAmelCase		)}]		)
		@require_torch
		def 			UpperCAmelCase__       (    self		)				-> Dict:




									"""simple docstring"""





									_UpperCAmelCase					=    pipeline('translation_en_to_ro'    ,					model='patrickvonplaten/t5-tiny-random'    ,					framework='pt'		)
									_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> List[str]:




									"""simple docstring"""





									_UpperCAmelCase					=    pipeline('translation_en_to_ro'    ,					model='patrickvonplaten/t5-tiny-random'    ,					framework='tf'		)
									_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> Any:




									"""simple docstring"""





									_UpperCAmelCase					=    pipeline('translation_en_to_de'    ,					model='patrickvonplaten/t5-tiny-random'    ,					framework='pt'		)
									_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> List[Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    pipeline('translation_en_to_de'    ,					model='patrickvonplaten/t5-tiny-random'    ,					framework='tf'		)
									_UpperCAmelCase					=    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 	__a   (       unittest.TestCase    ):
		@require_torch
		@slow
		def 			UpperCAmelCase__       (    self		)				-> List[Any]:




									"""simple docstring"""





									with self.assertRaises(_lowerCAmelCase		):
																pipeline(task='translation_cn_to_ar'		)

									# but we do for this one
									_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> Optional[Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-50-many-to-many-mmt'		)
									_UpperCAmelCase					=    MBartaaTokenizerFast.from_pretrained('facebook/mbart-large-50-many-to-many-mmt'		)

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

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

									_UpperCAmelCase					=    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					=    pipeline(task='translation'    ,					model=_lowerCAmelCase    ,					tokenizer=_lowerCAmelCase    ,					src_lang='en_XX'    ,					tgt_lang='ar_AR'		)
									_UpperCAmelCase					=    translator('This is a test'		)
									self.assertEqual(_lowerCAmelCase    ,					[{'translation_text': 'هذا إختبار'}]		)
		@require_torch
		def 			UpperCAmelCase__       (    self		)				-> str:




									"""simple docstring"""





									_UpperCAmelCase					=    """patrickvonplaten/t5-tiny-random"""
									_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> Any:




									"""simple docstring"""





									_UpperCAmelCase					=    """patrickvonplaten/t5-tiny-random"""
									with pytest.warns(_lowerCAmelCase    ,					match=R'.*translation_en_to_de.*'		):
																_UpperCAmelCase					=    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 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									with self.assertRaises(_lowerCAmelCase		):
																pipeline(task='translation'		)




import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types

class 	__a   (       unittest.TestCase					,   UpperCAmelCase    ):
		def 			UpperCAmelCase__       (    self		)				-> str:




									"""simple docstring"""





									_UpperCAmelCase					=    load_tool('translation'		)
									self.tool.setup()
									_UpperCAmelCase					=    load_tool('translation'    ,					remote=_SCREAMING_SNAKE_CASE		)
		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    self.tool('Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Tuple:




									"""simple docstring"""





									_UpperCAmelCase					=    self.remote_tool('Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    self.tool(text='Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> int:




									"""simple docstring"""





									_UpperCAmelCase					=    self.remote_tool(text='Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Tuple:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

									# There is a single output
									if len(self.tool.outputs		) == 1:
																_UpperCAmelCase					=    [outputs]

									self.assertListEqual(output_types(_SCREAMING_SNAKE_CASE		)    ,					self.tool.outputs		)
		def 			UpperCAmelCase__       (    self		)				-> Union[str, Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

									if not isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    [outputs]

									self.assertEqual(len(_SCREAMING_SNAKE_CASE		)    ,					len(self.tool.outputs		)		)

									for output, output_type in zip(_SCREAMING_SNAKE_CASE    ,					self.tool.outputs		):
																_UpperCAmelCase					=    AGENT_TYPE_MAPPING[output_type]
																self.assertTrue(isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		)		)






		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']

									_UpperCAmelCase					=    []

									for _input, input_type in zip(_SCREAMING_SNAKE_CASE    ,					self.tool.inputs		):
																if isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																							_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input		) for _input_type in input_type]		)
																else:
																							_inputs.append(AGENT_TYPE_MAPPING[input_type](_input		)		)

        # Should not raise an error
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

									if not isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    [outputs]

									self.assertEqual(len(_SCREAMING_SNAKE_CASE		)    ,					len(self.tool.outputs		)		)
