# 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.
import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool






class 		_lowerCamelCase		( UpperCamelCase_     ):
    __a						=   "facebook/bart-large-mnli"
    __a						=   (
        "This is a tool that classifies an English text using provided labels. It takes two inputs: `text`, which "
        "should be the text to classify, and `labels`, which should be the list of labels to use for classification. "
        "It returns the most likely label in the list of provided `labels` for the input text."
    )
    __a						=   "text_classifier"
    __a						=   AutoTokenizer
    __a						=   AutoModelForSequenceClassification

    __a						=   ["text", ["text"]]
    __a						=   ["text"]
    def     UpperCamelCase_					(	self )							->       Optional[Any]:
     super().setup()
     SCREAMING_SNAKE_CASE__: str=   self.model.config
     SCREAMING_SNAKE_CASE__: Optional[Any]=   -1
     for idx, label in config.idalabel.items():
      if label.lower().startswith('''entail''' ):
       SCREAMING_SNAKE_CASE__: Optional[Any]=   int(lowerCAmelCase )
     if self.entailment_id == -1:
      raise ValueError('''Could not determine the entailment ID from the model config, please pass it at init.''' )
    def     UpperCamelCase_					(	self			,			lowerCAmelCase			,			lowerCAmelCase )							->       List[Any]:
     SCREAMING_SNAKE_CASE__: Dict=   labels
     return self.pre_processor(
         [text] * len(lowerCAmelCase )			,			[f'This example is {label}' for label in labels]			,			return_tensors='''pt'''			,			padding='''max_length'''			,			)



    def     UpperCamelCase_					(	self			,			lowerCAmelCase )							->       List[Any]:
     SCREAMING_SNAKE_CASE__: str=   outputs.logits
     SCREAMING_SNAKE_CASE__: Optional[int]=   torch.argmax(logits[:, 2] ).item()
     return self._labels[label_id]


# Copyright 2021 The HuggingFace 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 argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def 	__A		(      ):



 """simple docstring"""


 __a							=	ArgumentParser("Accelerate CLI tool"				,					usage="accelerate <command> [<args>]"				,					allow_abbrev=_A       )
 __a							=	parser.add_subparsers(help="accelerate command helpers"       )

 # Register commands
 get_config_parser(subparsers=_A       )
 env_command_parser(subparsers=_A       )
 launch_command_parser(subparsers=_A       )
 tpu_command_parser(subparsers=_A       )
 test_command_parser(subparsers=_A       )

 # Let's go
 __a							=	parser.parse_args()

 if not hasattr(_A				,					"func"       ):
  parser.print_help()
  exit(1       )

 # Run
 args.func(_A       )


if __name__ == "__main__":
  main()


