






from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any





class __lowerCamelCase			:





							"""simple docstring"""






							UpperCamelCase__								=				("_front", "_back", "_len")





							@dataclass
							class __lowerCamelCase			:





														"""simple docstring"""






														UpperCamelCase__								=				None
														UpperCamelCase__								=				None
														UpperCamelCase__								=				None





							class __lowerCamelCase			:





														"""simple docstring"""






														UpperCamelCase__								=				("_cur",)

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







																				_UpperCAmelCase     =      cur

														def __iter__(							self   ):
																				"""simple docstring"""







																				return self

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







																				if self._cur is None:
																										# finished iterating
																										raise StopIteration
																				_UpperCAmelCase     =      self._cur.val
																				_UpperCAmelCase     =      self._cur.next_node

																				return val



							def __init__(							self	,   UpperCAmelCase = None   ):
													"""simple docstring"""







													_UpperCAmelCase     =      None
													_UpperCAmelCase     =      None
													_UpperCAmelCase     =      0

													if iterable is not None:
																			# append every value to the deque
																			for val in iterable:
																									self.append(UpperCAmelCase   )

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







													_UpperCAmelCase     =      self._Node(UpperCAmelCase	,   UpperCAmelCase	,   UpperCAmelCase   )
													if self.is_empty():
																			# front = back
																			_UpperCAmelCase     =      _UpperCAmelCase     =      node
																			_UpperCAmelCase     =      1
													else:
																			# connect nodes
																			_UpperCAmelCase     =      node
																			_UpperCAmelCase     =      self._back
																			_UpperCAmelCase     =      node  # assign new back to the new node

																			self._len += 1

																			# make sure there were no errors
																			assert not self.is_empty(), "Error on appending value."

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







													_UpperCAmelCase     =      self._Node(UpperCAmelCase	,   UpperCAmelCase	,   UpperCAmelCase   )
													if self.is_empty():
																			# front = back
																			_UpperCAmelCase     =      _UpperCAmelCase     =      node
																			_UpperCAmelCase     =      1
													else:
																			# connect nodes
																			_UpperCAmelCase     =      self._front
																			_UpperCAmelCase     =      node
																			_UpperCAmelCase     =      node  # assign new front to the new node

																			self._len += 1

																			# make sure there were no errors
																			assert not self.is_empty(), "Error on appending value."

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







													for val in iterable:
																			self.append(UpperCAmelCase   )

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







													for val in iterable:
																			self.appendleft(UpperCAmelCase   )

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







													assert not self.is_empty(), "Deque is empty."

													_UpperCAmelCase     =      self._back
													_UpperCAmelCase     =      self._back.prev_node  # set new back
													# drop the last node - python will deallocate memory automatically
													_UpperCAmelCase     =      None

													self._len -= 1

													return topop.val

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







													assert not self.is_empty(), "Deque is empty."

													_UpperCAmelCase     =      self._front
													_UpperCAmelCase     =      self._front.next_node  # set new front and drop the first node
													_UpperCAmelCase     =      None

													self._len -= 1

													return topop.val

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







													return self._front is None

							def __len__(							self   ):
													"""simple docstring"""







													return self._len

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







													if not isinstance(UpperCAmelCase	,   UpperCAmelCase   ):
																			return NotImplemented

													_UpperCAmelCase     =      self._front
													_UpperCAmelCase     =      other._front

													# if the length of the dequeues are not the same, they are not equal
													if len(self   ) != len(UpperCAmelCase   ):
																			return False

													while me is not None and oth is not None:
																			# compare every value
																			if me.val != oth.val:
																									return False
																			_UpperCAmelCase     =      me.next_node
																			_UpperCAmelCase     =      oth.next_node

													return True

							def __iter__(							self   ):
													"""simple docstring"""







													return Deque._Iterator(self._front   )

							def __repr__(							self   ):
													"""simple docstring"""







													_UpperCAmelCase     =      []
													_UpperCAmelCase     =      self._front
													while aux is not None:
																			# append the values in a list to display
																			values_list.append(aux.val   )
																			_UpperCAmelCase     =      aux.next_node

													return F"""[{", ".join(repr(UpperCAmelCase   ) for val in values_list   )}]"""


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'   )
