import unittest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TextaTextGenerationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_available

from .test_pipelines_common import ANY


if is_torch_available():
      import torch






@is_pipeline_test
class 		_lowerCamelCase		(   unittest.TestCase    ):
    __a  =      MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    __a  =      TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   Tuple=      TextaTextGenerationPipeline(model=lowerCAmelCase , tokenizer=lowerCAmelCase   )
     return generator, ["Something to write", "Something else"]
    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase   )       ->					str:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      generator('''Something there'''   )
     self.assertEqual(lowerCAmelCase , [{'''generated_text''': ANY(lowerCAmelCase   )}]   )
     # These are encoder decoder, they don't just append to incoming string
     self.assertFalse(outputs[0]['''generated_text'''].startswith('''Something there'''   )   )

     SCREAMING_SNAKE_CASE__:   List[str]=      generator(['''This is great !''', '''Something else'''] , num_return_sequences=2 , do_sample=lowerCAmelCase   )
     self.assertEqual(
         lowerCAmelCase , [
             [{'''generated_text''': ANY(lowerCAmelCase   )}, {'''generated_text''': ANY(lowerCAmelCase   )}],
             [{'''generated_text''': ANY(lowerCAmelCase   )}, {'''generated_text''': ANY(lowerCAmelCase   )}],
         ] , )

     SCREAMING_SNAKE_CASE__:   int=      generator(
         ['''This is great !''', '''Something else'''] , num_return_sequences=2 , batch_size=2 , do_sample=lowerCAmelCase   )
     self.assertEqual(
         lowerCAmelCase , [
             [{'''generated_text''': ANY(lowerCAmelCase   )}, {'''generated_text''': ANY(lowerCAmelCase   )}],
             [{'''generated_text''': ANY(lowerCAmelCase   )}, {'''generated_text''': ANY(lowerCAmelCase   )}],
         ] , )

     with self.assertRaises(lowerCAmelCase   ):
      generator(4   )
    @require_torch
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      pipeline('''text2text-generation''' , model='''patrickvonplaten/t5-tiny-random''' , framework='''pt'''   )
     # do_sample=False necessary for reproducibility
     SCREAMING_SNAKE_CASE__:   int=      generator('''Something there''' , do_sample=lowerCAmelCase   )
     self.assertEqual(lowerCAmelCase , [{'''generated_text''': ''''''}]   )

     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      3
     SCREAMING_SNAKE_CASE__:   Dict=      generator(
         '''Something there''' , num_return_sequences=lowerCAmelCase , num_beams=lowerCAmelCase , )
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      [
         {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide Beide'''},
         {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide'''},
         {'''generated_text''': ''''''},
     ]
     self.assertEqual(lowerCAmelCase , lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   List[Any]=      generator('''This is a test''' , do_sample=lowerCAmelCase , num_return_sequences=2 , return_tensors=lowerCAmelCase   )
     self.assertEqual(
         lowerCAmelCase , [
             {'''generated_token_ids''': ANY(torch.Tensor   )},
             {'''generated_token_ids''': ANY(torch.Tensor   )},
         ] , )
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      generator.model.config.eos_token_id
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      '''<pad>'''
     SCREAMING_SNAKE_CASE__:   int=      generator(
         ['''This is a test''', '''This is a second test'''] , do_sample=lowerCAmelCase , num_return_sequences=2 , batch_size=2 , return_tensors=lowerCAmelCase , )
     self.assertEqual(
         lowerCAmelCase , [
             [
                 {'''generated_token_ids''': ANY(torch.Tensor   )},
                 {'''generated_token_ids''': ANY(torch.Tensor   )},
             ],
             [
                 {'''generated_token_ids''': ANY(torch.Tensor   )},
                 {'''generated_token_ids''': ANY(torch.Tensor   )},
             ],
         ] , )



    @require_tf
    def 						UpperCamelCase_				(  self   )       ->					List[Any]:
     SCREAMING_SNAKE_CASE__:   int=      pipeline('''text2text-generation''' , model='''patrickvonplaten/t5-tiny-random''' , framework='''tf'''   )
     # do_sample=False necessary for reproducibility
     SCREAMING_SNAKE_CASE__:   str=      generator('''Something there''' , do_sample=lowerCAmelCase   )
     self.assertEqual(lowerCAmelCase , [{'''generated_text''': ''''''}]   )


import re







def 			A__      (	snake_case_ :		str      ):

 if len(re.findall('''[ATCG]'''       ,				snake_case_      )      ) != len(snake_case_      ):
  raise ValueError('''Invalid Strand'''      )

 return dna.translate(dna.maketrans('''ATCG'''       ,				'''TAGC'''      )      )


if __name__ == "__main__":
      import doctest

      doctest.testmod()

