



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 				lowerCAmelCase__	(						unittest.TestCase    ):
					__A  :     Union[str, Any]     =    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
					__A  :     str     =    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING







					def 			_lowercase      (							self   :  int      ,		_A   :  Dict      ,		_A   :  Optional[Any]      ,		_A   :  List[str]):
											if isinstance(model.config      ,		_A):
																	A__     ,							A__						:				str         =			list(tokenizer.lang_code_to_id.keys())[:2]
																	A__						:				Any         =			TranslationPipeline(model=_A      ,		tokenizer=_A      ,		src_lang=_A      ,		tgt_lang=_A)
											else:
																	A__						:				Union[str, Any]         =			TranslationPipeline(model=_A      ,		tokenizer=_A)
											return translator, ["Some string", "Some other text"]







					def 			_lowercase      (							self   :  Tuple      ,		_A   :  Any      ,		_A   :  Tuple):
											A__						:				Optional[Any]         =			translator("Some string")
											self.assertEqual(_A      ,		[{"translation_text": ANY(_A)}])

											A__						:				int         =			translator(["Some string"])
											self.assertEqual(_A      ,		[{"translation_text": ANY(_A)}])

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







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







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







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




class 				lowerCAmelCase__	(						unittest.TestCase    ):







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

											# but we do for this one
											A__						:				Optional[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   :  Dict):
											A__						:				Union[str, Any]         =			MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
											A__						:				int         =			MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")

											A__						:				List[Any]         =			pipeline(task="translation"      ,		model=_A      ,		tokenizer=_A)
											# Missing src_lang, tgt_lang
											with self.assertRaises(_A):
																	translator("This is a test")

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

											A__						:				List[str]         =			translator("This is a test"      ,		src_lang="en_XX"      ,		tgt_lang="hi_IN")
											self.assertEqual(_A      ,		[{"translation_text": "यह एक परीक्षण है"}])

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







					@require_torch
					def 			_lowercase      (							self   :  Any):
											A__						:				Optional[Any]         =			"patrickvonplaten/t5-tiny-random"
											A__						:				List[Any]         =			pipeline(task="translation_cn_to_ar"      ,		model=_A)
											self.assertEqual(translator._preprocess_params["src_lang"]      ,		"cn")
											self.assertEqual(translator._preprocess_params["tgt_lang"]      ,		"ar")







					@require_torch
					def 			_lowercase      (							self   :  int):
											A__						:				int         =			"patrickvonplaten/t5-tiny-random"
											with pytest.warns(_A      ,		match=r".*translation_en_to_de.*"):
																	A__						:				Optional[Any]         =			pipeline(task="translation"      ,		model=_A)
											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   :  Dict):
											with self.assertRaises(_A):
																	pipeline(task="translation")




from __future__ import annotations
def 						snake_case__							(       __lowercase				,  __lowercase				,  __lowercase				,  )		->		list[float | int]:







						"""simple docstring"""

						if not all((nth_term, start_term_a, common_ratio_r)							):
												return []
						A__						:				list[float | int]         =			[]
						A__						:				Optional[Any]         =			1
						A__						:				List[Any]         =			common_ratio_r
						for _ in range(int(__lowercase							)							):
												if not series:
																		series.append(__lowercase							)
												else:
																		power += 1
																		series.append(float(start_term_a * multiple							)							)
																		A__						:				Optional[Any]         =			pow(float(__lowercase							)				,  __lowercase							)
						return series


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		snake_case     :    Optional[int]						=    float(input('Enter the last number (n term) of the Geometric Series'))
		snake_case     :    str						=    float(input('Enter the starting term (a) of the Geometric Series'))
		snake_case     :    int						=    float(
		    input('Enter the common ratio between two terms (r) of the Geometric Series')
		)
		print('Formula of Geometric Series => a + ar + ar^2 ... +ar^n')
		print(geometric_series(nth_term, start_term_a, common_ratio_r))