"""simple docstring"""




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     UpperCamelCase__(			unittest.TestCase ):
						lowerCAmelCase__  :						int													=		MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
						lowerCAmelCase__  :						Any													=		TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase     )					->				List[str]:
													A__	     =							TextaTextGenerationPipeline(model=__UpperCAmelCase		,tokenizer=__UpperCAmelCase     )
													return generator, ["Something to write", "Something else"]





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase     )					->				Union[str, Any]:
													A__	     =							generator('Something there'     )
													self.assertEqual(__UpperCAmelCase		,[{'generated_text': ANY(__UpperCAmelCase     )}]     )
													# These are encoder decoder, they don't just append to incoming string
													self.assertFalse(outputs[0]['generated_text'].startswith('Something there'     )     )

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

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

													with self.assertRaises(__UpperCAmelCase     ):
																				generator(4     )





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

													A__	     =							3
													A__	     =							generator(
													    'Something there'		,num_return_sequences=__UpperCAmelCase		,num_beams=__UpperCAmelCase		,)
													A__	     =							[
													    {'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(__UpperCAmelCase		,__UpperCAmelCase     )

													A__	     =							generator('This is a test'		,do_sample=__UpperCAmelCase		,num_return_sequences=2		,return_tensors=__UpperCAmelCase     )
													self.assertEqual(
													    __UpperCAmelCase		,[
													        {'generated_token_ids': ANY(torch.Tensor     )},
													        {'generated_token_ids': ANY(torch.Tensor     )},
													    ]		,)
													A__	     =							generator.model.config.eos_token_id
													A__	     =							'<pad>'
													A__	     =							generator(
													    ['This is a test', 'This is a second test']		,do_sample=__UpperCAmelCase		,num_return_sequences=2		,batch_size=2		,return_tensors=__UpperCAmelCase		,)
													self.assertEqual(
													    __UpperCAmelCase		,[
													        [
													            {'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 				snake_case__	(       self     )					->				int:
													A__	     =							pipeline('text2text-generation'		,model='patrickvonplaten/t5-tiny-random'		,framework='tf'     )
													# do_sample=False necessary for reproducibility
													A__	     =							generator('Something there'		,do_sample=__UpperCAmelCase     )
													self.assertEqual(__UpperCAmelCase		,[{'generated_text': ''}]     )






"""simple docstring"""




import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


__lowerCamelCase											=  importlib.util.find_spec("s3fs") is not None

if _has_safs:
				from .safilesystem import SaFileSystem  # noqa: F401

__lowerCamelCase											=  [
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
				if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
								warnings.warn(F'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
				fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)






def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							if "://" in dataset_path:
														A__	     =							dataset_path.split('://'				)[1]
							return dataset_path






def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							if fs is not None and fs.protocol != "file":
														return True
							else:
														return False






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							not is_remote_filesystem(UpperCamelCase__				)
							if is_local:
														# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
														shutil.move(fs._strip_protocol(UpperCamelCase__				)       ,    fs._strip_protocol(UpperCamelCase__				)				)
							else:
														fs.mv(UpperCamelCase__       ,    UpperCamelCase__       ,    recursive=UpperCamelCase__				)






def   UpperCAmelCase					(	):






							"""simple docstring"""





							if hasattr(fsspec.asyn       ,    'reset_lock'				):
														# for future fsspec>2022.05.0
														fsspec.asyn.reset_lock()
							else:
														A__	     =							None
														A__	     =							None
														A__	     =							threading.Lock()





