
class 				lowerCamelCase__							:




	'''simple docstring'''




	def __init__(      self	:Optional[Any]  ,     a	:int		)	->				List[Any]:
				__UpperCamelCase			:     int         =      n
				__UpperCamelCase			:     List[str]         =      [None] * self.n
				__UpperCamelCase			:     str         =      0  # index of the first element
				__UpperCamelCase			:     Any         =      0
				__UpperCamelCase			:     Dict         =      0







	def __len__(      self	:int		)	->				int:
				return self.size







	def      _lowerCamelCase       (      self	:Tuple		)	->				bool:
				return self.size == 0







	def      _lowerCamelCase       (      self	:str		)	->				Optional[Any]:
				return False if self.is_empty() else self.array[self.front]







	def      _lowerCamelCase       (      self	:List[str]  ,     a	:List[Any]		)	->				str:







				if self.size >= self.n:
							raise Exception("QUEUE IS FULL"		)

				__UpperCamelCase			:     List[str]         =      data
				__UpperCamelCase			:     Optional[int]         =      (self.rear + 1) % self.n
				self.size += 1
				return self







	def      _lowerCamelCase       (      self	:Any		)	->				Optional[Any]:







				if self.size == 0:
							raise Exception("UNDERFLOW"		)

				__UpperCamelCase			:     int         =      self.array[self.front]
				__UpperCamelCase			:     List[str]         =      None
				__UpperCamelCase			:     Optional[Any]         =      (self.front + 1) % self.n
				self.size -= 1
				return temp

# 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__							(       __lowercase):




	'''simple docstring'''




	_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      _lowerCamelCase       (      self	:str		)	->				Tuple:
								super().setup()
								__UpperCamelCase			:     Any         =      self.model.config
								__UpperCamelCase			:     List[Any]         =      -1
								for idx, label in config.idalabel.items():
															if label.lower().startswith("entail"		):
																						__UpperCamelCase			:     Optional[Any]         =      int(a		)
								if self.entailment_id == -1:
															raise ValueError("Could not determine the entailment ID from the model config, please pass it at init."		)







	def      _lowerCamelCase       (      self	:Optional[int]  ,     a	:Dict  ,     a	:Optional[Any]		)	->				Optional[int]:
								__UpperCamelCase			:     str         =      labels
								return self.pre_processor(
								    [text] * len(a		)  ,     [f'This example is {label}' for label in labels]  ,     return_tensors="pt"  ,     padding="max_length"  ,     )







	def      _lowerCamelCase       (      self	:Any  ,     a	:Any		)	->				Optional[int]:
								__UpperCamelCase			:     Optional[int]         =      outputs.logits
								__UpperCamelCase			:     Dict         =      torch.argmax(logits[:, 2]		).item()
								return self._labels[label_id]