





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     ):
		lowerCamelCase__  :Tuple 					=		MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		lowerCamelCase__  :Union[str, Any] 					=		TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING







		def 							lowercase							(     self			,    __snake_case			,    __snake_case			,    __snake_case					)   ->   Dict:


							'''simple docstring'''

							if isinstance(model.config			,    __snake_case					):
												_snake_case							,			_snake_case							:       List[Any]												= list(tokenizer.lang_code_to_id.keys()					)[:2]
												_snake_case							:       List[Any]												= TranslationPipeline(model=__snake_case			,    tokenizer=__snake_case			,    src_lang=__snake_case			,    tgt_lang=__snake_case					)
							else:
												_snake_case							:       Any												= TranslationPipeline(model=__snake_case			,    tokenizer=__snake_case					)
							return translator, ["Some string", "Some other text"]







		def 							lowercase							(     self			,    __snake_case			,    __snake_case					)   ->   Union[str, Any]:


							'''simple docstring'''

							_snake_case							:       Any												= translator("Some string"					)
							self.assertEqual(__snake_case			,    [{"translation_text": ANY(__snake_case					)}]					)

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

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







		@require_torch
		def 							lowercase							(     self					)   ->   Any:


							'''simple docstring'''

							_snake_case							:       List[str]												= pipeline("translation_en_to_ro"			,    model="patrickvonplaten/t5-tiny-random"			,    framework="pt"					)
							_snake_case							:       Dict												= translator("This is a test string"			,    max_length=2_0					)
							self.assertEqual(
							    __snake_case			,    [
							        {
							            "translation_text": (
							                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
							                " Beide Beide"
							            )
							        }
							    ]			,    )







		@require_tf
		def 							lowercase							(     self					)   ->   Optional[int]:


							'''simple docstring'''

							_snake_case							:       Optional[int]												= pipeline("translation_en_to_ro"			,    model="patrickvonplaten/t5-tiny-random"			,    framework="tf"					)
							_snake_case							:       Optional[int]												= translator("This is a test string"			,    max_length=2_0					)
							self.assertEqual(
							    __snake_case			,    [
							        {
							            "translation_text": (
							                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
							                " Beide Beide"
							            )
							        }
							    ]			,    )







		@require_torch
		def 							lowercase							(     self					)   ->   Union[str, Any]:


							'''simple docstring'''

							_snake_case							:       Tuple												= pipeline("translation_en_to_de"			,    model="patrickvonplaten/t5-tiny-random"			,    framework="pt"					)
							_snake_case							:       Dict												= translator("This is a test string"			,    max_length=2_0					)
							self.assertEqual(
							    __snake_case			,    [
							        {
							            "translation_text": (
							                "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
							                " urine urine urine urine urine urine urine"
							            )
							        }
							    ]			,    )







		@require_tf
		def 							lowercase							(     self					)   ->   Tuple:


							'''simple docstring'''

							_snake_case							:       Dict												= pipeline("translation_en_to_de"			,    model="patrickvonplaten/t5-tiny-random"			,    framework="tf"					)
							_snake_case							:       List[str]												= translator("This is a test string"			,    max_length=2_0					)
							self.assertEqual(
							    __snake_case			,    [
							        {
							            "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 							lowercase							(     self					)   ->   str:


							'''simple docstring'''

							with self.assertRaises(__snake_case					):
												pipeline(task="translation_cn_to_ar"					)

							# but we do for this one
							_snake_case							:       List[Any]												= 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 							lowercase							(     self					)   ->   Optional[Any]:


							'''simple docstring'''

							_snake_case							:       Tuple												= MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"					)
							_snake_case							:       Dict												= MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"					)

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

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

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

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







		@require_torch
		def 							lowercase							(     self					)   ->   List[str]:


							'''simple docstring'''

							_snake_case							:       Any												= "patrickvonplaten/t5-tiny-random"
							_snake_case							:       str												= pipeline(task="translation_cn_to_ar"			,    model=__snake_case					)
							self.assertEqual(translator._preprocess_params["src_lang"]			,    "cn"					)
							self.assertEqual(translator._preprocess_params["tgt_lang"]			,    "ar"					)







		@require_torch
		def 							lowercase							(     self					)   ->   Optional[int]:


							'''simple docstring'''

							_snake_case							:       Union[str, Any]												= "patrickvonplaten/t5-tiny-random"
							with pytest.warns(__snake_case			,    match=r".*translation_en_to_de.*"					):
												_snake_case							:       Optional[Any]												= pipeline(task="translation"			,    model=__snake_case					)
							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 							lowercase							(     self					)   ->   int:


							'''simple docstring'''

							with self.assertRaises(__snake_case					):
												pipeline(task="translation"					)






def  A					(				UpperCAmelCase					):
					if not isinstance(UpperCAmelCase	,	UpperCAmelCase					):
										_snake_case							:       Optional[Any]												= F"""Input value of [number={number}] must be an integer"""
										raise TypeError(UpperCAmelCase					)
					if number < 1:
										raise ValueError("Input must be a positive integer"					)
					return number * (2 * number - 1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()