




# 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__					(      UpperCamelCase__   ):
						_a							:					List[Any]      =					"""facebook/bart-large-mnli"""
						_a							:					Optional[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."""
						)
						_a							:					Union[str, Any]      =					"""text_classifier"""
						_a							:					int      =					AutoTokenizer
						_a							:					Tuple      =					AutoModelForSequenceClassification

						_a							:					str      =					["""text""", ["""text"""]]
						_a							:					List[Any]      =					["""text"""]






						def        __SCREAMING_SNAKE_CASE(     self    ):




											"""simple docstring"""



											super().setup()
											__lowerCAmelCase            = self.model.config
											__lowerCAmelCase            = -1
											for idx, label in config.idalabel.items():
																if label.lower().startswith("entail"    ):
																					__lowerCAmelCase            = 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        __SCREAMING_SNAKE_CASE(     self	,    _A	,    _A    ):




											"""simple docstring"""



											__lowerCAmelCase            = labels
											return self.pre_processor(
											    [text] * len(__A    )	,    [f"""This example is {label}""" for label in labels]	,    return_tensors="pt"	,    padding="max_length"	,    )






						def        __SCREAMING_SNAKE_CASE(     self	,    _A    ):




											"""simple docstring"""



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










from math import ceil, sqrt







def 			_a   (		SCREAMING_SNAKE_CASE_							:       int = 1_00_00_00  ):
					__lowerCAmelCase            = 0

					for outer_width in range(3   ,   (limit // 4) + 2  ):
										if outer_width**2 > limit:
															__lowerCAmelCase            = max(ceil(sqrt(outer_width**2 - limit  )  )   ,   1  )
										else:
															__lowerCAmelCase            = 1
										if (outer_width - hole_width_lower_bound) % 2:
															hole_width_lower_bound += 1

										answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

					return answer


if __name__ == "__main__":
					print(f'''{solution() = }''')




