






_a				     =  {
    "kilogram": 1,
    "gram": pow(10, 3),
    "milligram": pow(10, 6),
    "metric-ton": pow(10, -3),
    "long-ton": 0.00_09_84_20_73,
    "short-ton": 0.00_11_02_31_22,
    "pound": 2.20_46_24_42_02,
    "stone": 0.15_74_73_17_28,
    "ounce": 35.2_73_99_07_23,
    "carrat": 5000,
    "atomic-mass-unit": 6.0_2213_6652e26,
}

_a				     =  {
    "kilogram": 1,
    "gram": pow(10, -3),
    "milligram": pow(10, -6),
    "metric-ton": pow(10, 3),
    "long-ton": 10_16.0_46_08,
    "short-ton": 9_07.1_84,
    "pound": 0.45_35_92,
    "stone": 6.3_50_29,
    "ounce": 0.0_28_34_95,
    "carrat": 0.00_02,
    "atomic-mass-unit": 1.6_6054_0199e-27,
}


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  float:





						"""simple docstring"""



						if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
												_UpperCAmelCase     =      (
												    F"""Invalid 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
												    F"""Supported values are: {", ".join(__lowerCAmelCase     )}"""
												)
												raise ValueError(__lowerCAmelCase     )
						return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]


if __name__ == "__main__":
		import doctest

		doctest.testmod()








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):





	"""simple docstring"""






	UpperCamelCase__								=				MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
	UpperCamelCase__								=				TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

	def 	UpperCamelCase   (							self	,   UpperCAmelCase	,   UpperCAmelCase	,   UpperCAmelCase   ):
							"""simple docstring"""







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

	def 	UpperCamelCase   (							self	,   UpperCAmelCase	,   UpperCAmelCase   ):
							"""simple docstring"""







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

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

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

	@require_torch
	def 	UpperCamelCase   (							self   ):
							"""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(
							    UpperCAmelCase	,   [
							        {
							            'translation_text': (
							                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
							                ' Beide Beide'
							            )
							        }
							    ]	,   )

	@require_tf
	def 	UpperCamelCase   (							self   ):
							"""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(
							    UpperCAmelCase	,   [
							        {
							            'translation_text': (
							                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
							                ' Beide Beide'
							            )
							        }
							    ]	,   )

	@require_torch
	def 	UpperCamelCase   (							self   ):
							"""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(
							    UpperCAmelCase	,   [
							        {
							            '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   ):
							"""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(
							    UpperCAmelCase	,   [
							        {
							            '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):





	"""simple docstring"""






	@require_torch
	@slow
	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							with self.assertRaises(UpperCAmelCase   ):
													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   ):
							"""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=UpperCAmelCase	,   tokenizer=UpperCAmelCase   )
							# Missing src_lang, tgt_lang
							with self.assertRaises(UpperCAmelCase   ):
													translator('This is a test'   )

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

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

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

	@require_torch
	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      'patrickvonplaten/t5-tiny-random'
							_UpperCAmelCase     =      pipeline(task='translation_cn_to_ar'	,   model=UpperCAmelCase   )
							self.assertEqual(translator._preprocess_params['src_lang']	,   'cn'   )
							self.assertEqual(translator._preprocess_params['tgt_lang']	,   'ar'   )

	@require_torch
	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      'patrickvonplaten/t5-tiny-random'
							with pytest.warns(UpperCAmelCase	,   match=R'.*translation_en_to_de.*'   ):
													_UpperCAmelCase     =      pipeline(task='translation'	,   model=UpperCAmelCase   )
							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   ):
							"""simple docstring"""







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