"""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.
import torch

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


class      UpperCAmelCase_	(    _a):
      lowerCamelCase__		:    List[str]   =  "facebook/bart-large-mnli"
      lowerCamelCase__		:    Union[str, Any]   =  (
          "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."
      )
      lowerCamelCase__		:    Any   =  "text_classifier"
      lowerCamelCase__		:    List[Any]   =  AutoTokenizer
      lowerCamelCase__		:    List[str]   =  AutoModelForSequenceClassification

      lowerCamelCase__		:    Optional[Any]   =  ["text", ["text"]]
      lowerCamelCase__		:    Dict   =  ["text"]


      def 		_UpperCAmelCase       (   self							)       ->					Optional[int]:
             super().setup()
             lowercase__			:		Optional[Any]       =	self.model.config
             lowercase__			:		List[Any]       =	-1
             for idx, label in config.idalabel.items():
                    if label.lower().startswith('entail'							):
                           lowercase__			:		Optional[Any]       =	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 		_UpperCAmelCase       (   self		,			a		,			a							)       ->					Tuple:
             lowercase__			:		Optional[int]       =	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 		_UpperCAmelCase       (   self		,			a							)       ->					str:
             lowercase__			:		int       =	outputs.logits
             lowercase__			:		List[str]       =	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,
)