
# 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 			__A( a			):
				snake_case_						   =    '''facebook/bart-large-mnli'''
				snake_case_						   =    (
				    '''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.'''
				)
				snake_case_						   =    '''text_classifier'''
				snake_case_						   =    AutoTokenizer
				snake_case_						   =    AutoModelForSequenceClassification

				snake_case_						   =    ['''text''', ['''text''']]
				snake_case_						   =    ['''text''']




				def 				SCREAMING_SNAKE_CASE_		(     self				)    ->      Optional[int]:


								'''simple docstring'''




								super().setup()
								__a										=    self.model.config
								__a										=    -1
								for idx, label in config.idalabel.items():
												if label.lower().startswith('''entail'''				):
																__a										=    int(_snake_case				)
								if self.entailment_id == -1:
												raise ValueError('''Could not determine the entailment ID from the model config, please pass it at init.'''				)




				def 				SCREAMING_SNAKE_CASE_		(     self		,     _snake_case		,     _snake_case				)    ->      Tuple:


								'''simple docstring'''




								__a										=    labels
								return self.pre_processor(
								    [text] * len(_snake_case				)		,     [F"""This example is {label}""" for label in labels]		,     return_tensors='''pt'''		,     padding='''max_length'''		,     )




				def 				SCREAMING_SNAKE_CASE_		(     self		,     _snake_case				)    ->      str:


								'''simple docstring'''




								__a										=    outputs.logits
								__a										=    torch.argmax(logits[:, 2]				).item()
								return self._labels[label_id]

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel  # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    'stable diffusion controlnet',
    '0.22.0',
    'Importing `StableDiffusionControlNetPipeline` or `MultiControlNetModel` from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import StableDiffusionControlNetPipeline` instead.',
    standard_warn=False,
    stacklevel=3,
)