


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):
     SCREAMING_SNAKE_CASE__      =     MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
     SCREAMING_SNAKE_CASE__      =     TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING





     def 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase			)	->  Tuple:
      if isinstance(model.config						,	UpperCAmelCase			):
       _lowercase ,       _lowercase				 =list(tokenizer.lang_code_to_id.keys()			)[:2]
       _lowercase				 =TranslationPipeline(model=UpperCAmelCase						,	tokenizer=UpperCAmelCase						,	src_lang=UpperCAmelCase						,	tgt_lang=UpperCAmelCase			)
      else:
       _lowercase				 =TranslationPipeline(model=UpperCAmelCase						,	tokenizer=UpperCAmelCase			)
      return translator, ["Some string", "Some other text"]





     def 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase			)	->  List[Any]:
      _lowercase				 =translator('''Some string'''			)
      self.assertEqual(UpperCAmelCase						,	[{'''translation_text''': ANY(UpperCAmelCase			)}]			)

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

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





     @require_torch
     def 	__A   (self			)	->  Optional[Any]:
      _lowercase				 =pipeline('''translation_en_to_ro'''						,	model='''patrickvonplaten/t5-tiny-random'''						,	framework='''pt'''			)
      _lowercase				 =translator('''This is a test string'''						,	max_length=2_0			)
      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 	__A   (self			)	->  Optional[Any]:
      _lowercase				 =pipeline('''translation_en_to_ro'''						,	model='''patrickvonplaten/t5-tiny-random'''						,	framework='''tf'''			)
      _lowercase				 =translator('''This is a test string'''						,	max_length=2_0			)
      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 	__A   (self			)	->  str:
      _lowercase				 =pipeline('''translation_en_to_de'''						,	model='''patrickvonplaten/t5-tiny-random'''						,	framework='''pt'''			)
      _lowercase				 =translator('''This is a test string'''						,	max_length=2_0			)
      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 	__A   (self			)	->  Optional[int]:
      _lowercase				 =pipeline('''translation_en_to_de'''						,	model='''patrickvonplaten/t5-tiny-random'''						,	framework='''tf'''			)
      _lowercase				 =translator('''This is a test string'''						,	max_length=2_0			)
      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):





     @require_torch
     @slow
     def 	__A   (self			)	->  Optional[Any]:
      # We don't provide a default for this pair
      with self.assertRaises(UpperCAmelCase			):
       pipeline(task='''translation_cn_to_ar'''			)

      # but we do for this one
      _lowercase				 =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 	__A   (self			)	->  Optional[Any]:
      _lowercase				 =MBartForConditionalGeneration.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''			)
      _lowercase				 =MBartaaTokenizerFast.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''			)

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

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

      _lowercase				 =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
      _lowercase				 =pipeline(task='''translation'''						,	model=UpperCAmelCase						,	tokenizer=UpperCAmelCase						,	src_lang='''en_XX'''						,	tgt_lang='''ar_AR'''			)
      _lowercase				 =translator('''This is a test'''			)
      self.assertEqual(UpperCAmelCase						,	[{'''translation_text''': '''هذا إختبار'''}]			)





     @require_torch
     def 	__A   (self			)	->  Tuple:
      _lowercase				 ='''patrickvonplaten/t5-tiny-random'''
      _lowercase				 =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 	__A   (self			)	->  str:
      _lowercase				 ='''patrickvonplaten/t5-tiny-random'''
      with pytest.warns(UpperCAmelCase						,	match=R'''.*translation_en_to_de.*'''			):
       _lowercase				 =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 	__A   (self			)	->  List[str]:
      with self.assertRaises(UpperCAmelCase			):
       pipeline(task='''translation'''			)





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__        =				logging.get_logger(__name__)

UpperCAmelCase__        =				{
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}







class  lowerCamelCase__  (			lowerCAmelCase):
     SCREAMING_SNAKE_CASE__      =     '''rembert'''





     def __init__(self						,	UpperCAmelCase=2_5_0_3_0_0						,	UpperCAmelCase=1_1_5_2						,	UpperCAmelCase=3_2						,	UpperCAmelCase=1_8						,	UpperCAmelCase=2_5_6						,	UpperCAmelCase=1_6_6_4						,	UpperCAmelCase=4_6_0_8						,	UpperCAmelCase="gelu"						,	UpperCAmelCase=0.0						,	UpperCAmelCase=0.0						,	UpperCAmelCase=0.1						,	UpperCAmelCase=5_1_2						,	UpperCAmelCase=2						,	UpperCAmelCase=0.02						,	UpperCAmelCase=1e-12						,	UpperCAmelCase=True						,	UpperCAmelCase=0						,	UpperCAmelCase=3_1_2						,	UpperCAmelCase=3_1_3						,	**UpperCAmelCase						,	)	->  Tuple:
      super().__init__(pad_token_id=UpperCAmelCase						,	bos_token_id=UpperCAmelCase						,	eos_token_id=UpperCAmelCase						,	**UpperCAmelCase			)

      _lowercase				 =vocab_size
      _lowercase				 =input_embedding_size
      _lowercase				 =output_embedding_size
      _lowercase				 =max_position_embeddings
      _lowercase				 =hidden_size
      _lowercase				 =num_hidden_layers
      _lowercase				 =num_attention_heads
      _lowercase				 =intermediate_size
      _lowercase				 =hidden_act
      _lowercase				 =hidden_dropout_prob
      _lowercase				 =attention_probs_dropout_prob
      _lowercase				 =classifier_dropout_prob
      _lowercase				 =initializer_range
      _lowercase				 =type_vocab_size
      _lowercase				 =layer_norm_eps
      _lowercase				 =use_cache
      _lowercase				 =False







class  lowerCamelCase__  (			lowerCAmelCase):





     @property
     def 	__A   (self			)	->  Mapping[str, Mapping[int, str]]:
      if self.task == "multiple-choice":
       _lowercase				 ={0: '''batch''', 1: '''choice''', 2: '''sequence'''}
      else:
       _lowercase				 ={0: '''batch''', 1: '''sequence'''}
      return OrderedDict(
          [
              ('''input_ids''', dynamic_axis),
              ('''attention_mask''', dynamic_axis),
              ('''token_type_ids''', dynamic_axis),
          ]			)





     @property
     def 	__A   (self			)	->  float:
      return 1e-4

