


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     __lowercase    (				unittest.TestCase   ):



		"""simple docstring"""

		UpperCamelCase			: Optional[Any]           =						MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		UpperCamelCase			: List[Any]           =						TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING







		def  __A					(      self						,	A						,	A						,	A     )   ->      List[str]:







					'''simple docstring'''







					lowerCamelCase  						=   TextaTextGenerationPipeline(model=lowerCamelCase__						,	tokenizer=lowerCamelCase__     )
					return generator, ["Something to write", "Something else"]







		def  __A					(      self						,	A						,	A     )   ->      int:







					'''simple docstring'''







					lowerCamelCase  						=   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"""     )     )

					lowerCamelCase  						=   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__     )}],
					    ]						,	)

					lowerCamelCase  						=   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  __A					(      self     )   ->      Dict:







					'''simple docstring'''







					lowerCamelCase  						=   pipeline("""text2text-generation"""						,	model="""patrickvonplaten/t5-tiny-random"""						,	framework="""pt"""     )
					# do_sample=False necessary for reproducibility
					lowerCamelCase  						=   generator("""Something there"""						,	do_sample=lowerCamelCase__     )
					self.assertEqual(lowerCamelCase__						,	[{"""generated_text""": """"""}]     )

					lowerCamelCase  						=   3
					lowerCamelCase  						=   generator(
					    """Something there"""						,	num_return_sequences=lowerCamelCase__						,	num_beams=lowerCamelCase__						,	)
					lowerCamelCase  						=   [
					    {"""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__     )

					lowerCamelCase  						=   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     )},
					    ]						,	)
					lowerCamelCase  						=   generator.model.config.eos_token_id
					lowerCamelCase  						=   """<pad>"""
					lowerCamelCase  						=   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  __A					(      self     )   ->      int:







					'''simple docstring'''







					lowerCamelCase  						=   pipeline("""text2text-generation"""						,	model="""patrickvonplaten/t5-tiny-random"""						,	framework="""tf"""     )
					# do_sample=False necessary for reproducibility
					lowerCamelCase  						=   generator("""Something there"""						,	do_sample=lowerCamelCase__     )
					self.assertEqual(lowerCamelCase__						,	[{"""generated_text""": """"""}]     )


"""simple docstring"""






import argparse


lowerCAmelCase__  :  List[str]						     =	'docs/source/_static/js/custom.js'



def   a_						(					lowerCamelCase       ):
				with open(lowerCamelCase					,			encoding='utf-8'					,			newline='\n'       ) as f:
								UpperCAmelCase__             =							f.readlines()
				UpperCAmelCase__             =							0

				# First let's put the right version
				while not lines[index].startswith('const stableVersion ='       ):
								index += 1
				UpperCAmelCase__             =							f'''const stableVersion = "v{version}"\n'''

				# Then update the dictionary
				while not lines[index].startswith('const versionMapping = {'       ):
								index += 1

				# We go until the end
				while not lines[index].startswith('}'       ):
								index += 1
				# We add the new version at the end
				lines[index - 1] += f'''    "v{version}": "v{version}",\n'''

				with open(lowerCamelCase					,			'w'					,			encoding='utf-8'					,			newline='\n'       ) as f:
								f.writelines(lowerCamelCase       )


if __name__ == "__main__":
						lowerCAmelCase__  :  List[Any]						     =	argparse.ArgumentParser()
						parser.add_argument('--version', help='Release version.')
						lowerCAmelCase__  :  Optional[int]						     =	parser.parse_args()
						update_custom_js(args.version)



