
import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowercase        =  logging.get_logger(__name__)

lowercase        =  {
    """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}





class       __A(				__UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    '''deta'''
					SCREAMING_SNAKE_CASE			    =    {
					    '''hidden_size''': '''d_model''',
					    '''num_attention_heads''': '''encoder_attention_heads''',
					}

					def __init__(	self					:     List[str]   ,					__UpperCamelCase					:     Optional[int]=None   ,					__UpperCamelCase					:     Optional[int]=9_0_0   ,					__UpperCamelCase					:     Optional[int]=2_0_4_8   ,					__UpperCamelCase					:     List[Any]=6   ,					__UpperCamelCase					:     Optional[Any]=2_0_4_8   ,					__UpperCamelCase					:     Optional[int]=8   ,					__UpperCamelCase					:     Optional[Any]=6   ,					__UpperCamelCase					:     str=1_0_2_4   ,					__UpperCamelCase					:     Union[str, Any]=8   ,					__UpperCamelCase					:     Union[str, Any]=0.0   ,					__UpperCamelCase					:     Any=True   ,					__UpperCamelCase					:     Optional[Any]="relu"   ,					__UpperCamelCase					:     List[Any]=2_5_6   ,					__UpperCamelCase					:     Any=0.1   ,					__UpperCamelCase					:     List[Any]=0.0   ,					__UpperCamelCase					:     List[str]=0.0   ,					__UpperCamelCase					:     List[Any]=0.02   ,					__UpperCamelCase					:     str=1.0   ,					__UpperCamelCase					:     str=True   ,					__UpperCamelCase					:     List[str]=False   ,					__UpperCamelCase					:     Union[str, Any]="sine"   ,					__UpperCamelCase					:     Tuple=5   ,					__UpperCamelCase					:     int=4   ,					__UpperCamelCase					:     Optional[int]=4   ,					__UpperCamelCase					:     Dict=True   ,					__UpperCamelCase					:     Any=3_0_0   ,					__UpperCamelCase					:     Optional[Any]=True   ,					__UpperCamelCase					:     List[Any]=True   ,					__UpperCamelCase					:     List[str]=1   ,					__UpperCamelCase					:     Dict=5   ,					__UpperCamelCase					:     Tuple=2   ,					__UpperCamelCase					:     List[Any]=1   ,					__UpperCamelCase					:     str=1   ,					__UpperCamelCase					:     List[str]=5   ,					__UpperCamelCase					:     Optional[Any]=2   ,					__UpperCamelCase					:     int=0.1   ,					__UpperCamelCase					:     str=0.25   ,					**__UpperCamelCase					:     Optional[Any]   ,					):

												if backbone_config is None:
																			logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""   )
																			lowerCamelCase_							  =					CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]   )
												else:
																			if isinstance(__UpperCamelCase   ,					__UpperCamelCase   ):
																										lowerCamelCase_							  =					backbone_config.pop("""model_type"""   )
																										lowerCamelCase_							  =					CONFIG_MAPPING[backbone_model_type]
																										lowerCamelCase_							  =					config_class.from_dict(__UpperCamelCase   )

												lowerCamelCase_							  =					backbone_config
												lowerCamelCase_							  =					num_queries
												lowerCamelCase_							  =					max_position_embeddings
												lowerCamelCase_							  =					d_model
												lowerCamelCase_							  =					encoder_ffn_dim
												lowerCamelCase_							  =					encoder_layers
												lowerCamelCase_							  =					encoder_attention_heads
												lowerCamelCase_							  =					decoder_ffn_dim
												lowerCamelCase_							  =					decoder_layers
												lowerCamelCase_							  =					decoder_attention_heads
												lowerCamelCase_							  =					dropout
												lowerCamelCase_							  =					attention_dropout
												lowerCamelCase_							  =					activation_dropout
												lowerCamelCase_							  =					activation_function
												lowerCamelCase_							  =					init_std
												lowerCamelCase_							  =					init_xavier_std
												lowerCamelCase_							  =					encoder_layerdrop
												lowerCamelCase_							  =					auxiliary_loss
												lowerCamelCase_							  =					position_embedding_type
												# deformable attributes
												lowerCamelCase_							  =					num_feature_levels
												lowerCamelCase_							  =					encoder_n_points
												lowerCamelCase_							  =					decoder_n_points
												lowerCamelCase_							  =					two_stage
												lowerCamelCase_							  =					two_stage_num_proposals
												lowerCamelCase_							  =					with_box_refine
												lowerCamelCase_							  =					assign_first_stage
												if two_stage is True and with_box_refine is False:
																			raise ValueError("""If two_stage is True, with_box_refine must be True."""   )
												# Hungarian matcher
												lowerCamelCase_							  =					class_cost
												lowerCamelCase_							  =					bbox_cost
												lowerCamelCase_							  =					giou_cost
												# Loss coefficients
												lowerCamelCase_							  =					mask_loss_coefficient
												lowerCamelCase_							  =					dice_loss_coefficient
												lowerCamelCase_							  =					bbox_loss_coefficient
												lowerCamelCase_							  =					giou_loss_coefficient
												lowerCamelCase_							  =					eos_coefficient
												lowerCamelCase_							  =					focal_alpha
												super().__init__(is_encoder_decoder=__UpperCamelCase   ,					**__UpperCamelCase   )

					@property
					def    lowercase__      (	self					:     int   ):
												return self.encoder_attention_heads

					@property
					def    lowercase__      (	self					:     Optional[Any]   ):
												return self.d_model



					def    lowercase__      (	self					:     List[str]   ):
												lowerCamelCase_							  =					copy.deepcopy(self.__dict__   )
												lowerCamelCase_							  =					self.backbone_config.to_dict()
												lowerCamelCase_							  =					self.__class__.model_type
												return output







# 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       ):
					SCREAMING_SNAKE_CASE			    =    '''facebook/bart-large-mnli'''
					SCREAMING_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.'''
					)
					SCREAMING_SNAKE_CASE			    =    '''text_classifier'''
					SCREAMING_SNAKE_CASE			    =    AutoTokenizer
					SCREAMING_SNAKE_CASE			    =    AutoModelForSequenceClassification

					SCREAMING_SNAKE_CASE			    =    ['''text''', ['''text''']]
					SCREAMING_SNAKE_CASE			    =    ['''text''']

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

					def    lowercase__      (	self					:     Any   ,					__UpperCamelCase					:     List[Any]   ,					__UpperCamelCase					:     Optional[Any]   ):
												lowerCamelCase_							  =					labels
												return self.pre_processor(
												    [text] * len(__UpperCamelCase   )   ,					[F'''This example is {label}''' for label in labels]   ,					return_tensors="""pt"""   ,					padding="""max_length"""   ,					)



					def    lowercase__      (	self					:     List[Any]   ,					__UpperCamelCase					:     List[str]   ):
												lowerCamelCase_							  =					outputs.logits
												lowerCamelCase_							  =					torch.argmax(logits[:, 2]   ).item()
												return self._labels[label_id]





