



"""simple docstring"""


import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand

def 			_lowerCAmelCase				(       lowercase_						):
						return EnvironmentCommand()

def 			_lowerCAmelCase				(       lowercase_						):
						return EnvironmentCommand(args.accelerate_config_file						)







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""






						@staticmethod
						def      UpperCAmelCase__					( lowercase_			:ArgumentParser )    ->      Union[str, Any]:
												UpperCAmelCase					=			parser.add_parser('env' )
												download_parser.set_defaults(func=lowercase_ )
												download_parser.add_argument(
												    '--accelerate-config_file'       ,  default=lowercase_       ,  help='The accelerate config file to use for the default values in the launching script.'       ,  )
												download_parser.set_defaults(func=lowercase_ )






						def __init__( self			:Any       ,  lowercase_			:int       ,  *lowercase_			:Optional[int] )    ->      None:
												UpperCAmelCase					=			accelerate_config_file






						def      UpperCAmelCase__					( self			:Dict )    ->      Union[str, Any]:
												UpperCAmelCase					=			'not installed'
												if is_safetensors_available():
																		import safetensors

																		UpperCAmelCase					=			safetensors.__version__
												elif importlib.util.find_spec('safetensors' ) is not None:
																		import safetensors

																		UpperCAmelCase					=			f"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			UpperCAmelCase					=			'not found'
												if is_accelerate_available():
																		import accelerate
																		from accelerate.commands.config import default_config_file, load_config_from_file

																		UpperCAmelCase					=			accelerate.__version__
																		# Get the default from the config file.
																		if self._accelerate_config_file is not None or os.path.isfile(lowercase_ ):
																								UpperCAmelCase					=			load_config_from_file(self._accelerate_config_file ).to_dict()

																		UpperCAmelCase					=			(
																		    '\n'.join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()] )
																		    if isinstance(lowercase_       ,  lowercase_ )
																		    else f"""\t{accelerate_config}"""
																		)

												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			'NA'
												if is_torch_available():
																		import torch

																		UpperCAmelCase					=			torch.__version__
																		UpperCAmelCase					=			torch.cuda.is_available()

												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			'NA'
												if is_tf_available():
																		import tensorflow as tf

																		UpperCAmelCase					=			tf.__version__
																		try:
																								# deprecated in v2.1
																								UpperCAmelCase					=			tf.test.is_gpu_available()
																		except AttributeError:
																								# returns list of devices, convert to bool
																								UpperCAmelCase					=			bool(tf.config.list_physical_devices('GPU' ) )

												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			'not installed'
												UpperCAmelCase					=			'NA'
												if is_flax_available():
																		import flax
																		import jax
																		import jaxlib

																		UpperCAmelCase					=			flax.__version__
																		UpperCAmelCase					=			jax.__version__
																		UpperCAmelCase					=			jaxlib.__version__
																		UpperCAmelCase					=			jax.lib.xla_bridge.get_backend().platform

												UpperCAmelCase					=			{
												    '`transformers` version': version,
												    'Platform': platform.platform(),
												    'Python version': platform.python_version(),
												    'Huggingface_hub version': huggingface_hub.__version__,
												    'Safetensors version': f"""{safetensors_version}""",
												    'Accelerate version': f"""{accelerate_version}""",
												    'Accelerate config': f"""{accelerate_config_str}""",
												    'PyTorch version (GPU?)': f"""{pt_version} ({pt_cuda_available})""",
												    'Tensorflow version (GPU?)': f"""{tf_version} ({tf_cuda_available})""",
												    'Flax version (CPU?/GPU?/TPU?)': f"""{flax_version} ({jax_backend})""",
												    'Jax version': f"""{jax_version}""",
												    'JaxLib version': f"""{jaxlib_version}""",
												    'Using GPU in script?': '<fill in>',
												    'Using distributed or parallel set-up in script?': '<fill in>',
												}

												print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n' )
												print(self.format_dict(lowercase_ ) )

												return info






						@staticmethod
						def      UpperCAmelCase__					( lowercase_			:List[str] )    ->      Dict:
												return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()] ) + "\n"










"""simple docstring"""


# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""
						__UpperCamelCase		    =							"""philschmid/bart-large-cnn-samsum"""
						__UpperCamelCase		    =							(
						    """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
						    """and returns a summary of the text."""
						)
						__UpperCamelCase		    =							"""summarizer"""
						__UpperCamelCase		    =							AutoTokenizer
						__UpperCamelCase		    =							AutoModelForSeqaSeqLM

						__UpperCamelCase		    =							["""text"""]
						__UpperCamelCase		    =							["""text"""]






						def      UpperCAmelCase__					( self			:int       ,  lowercase_			:Tuple )    ->      int:
												return self.pre_processor(lowercase_       ,  return_tensors='pt'       ,  truncation=lowercase_ )






						def      UpperCAmelCase__					( self			:Dict       ,  lowercase_			:Dict )    ->      Optional[int]:
												return self.model.generate(**lowercase_ )[0]






						def      UpperCAmelCase__					( self			:Dict       ,  lowercase_			:Tuple )    ->      List[str]:
												return self.pre_processor.decode(lowercase_       ,  skip_special_tokens=lowercase_       ,  clean_up_tokenization_spaces=lowercase_ )





