



'''simple docstring'''





import copy
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


SCREAMING_SNAKE_CASE__      					=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      					=     {
    "microsoft/conditional-detr-resnet-50": (
        "https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"
    ),
}


class 				snake_case (UpperCamelCase   ):
       lowerCAmelCase__  :str						   =					"conditional_detr"
       lowerCAmelCase__  :Tuple						   =					["past_key_values"]
       lowerCAmelCase__  :Any						   =					{
           "hidden_size": "d_model",
           "num_attention_heads": "encoder_attention_heads",
       }



       def __init__(				self     ,UpperCAmelCase_=True     ,UpperCAmelCase_=None     ,UpperCAmelCase_=3     ,UpperCAmelCase_=300     ,UpperCAmelCase_=6     ,UpperCAmelCase_=2_048     ,UpperCAmelCase_=8     ,UpperCAmelCase_=6     ,UpperCAmelCase_=2_048     ,UpperCAmelCase_=8     ,UpperCAmelCase_=0.0     ,UpperCAmelCase_=0.0     ,UpperCAmelCase_=True     ,UpperCAmelCase_="relu"     ,UpperCAmelCase_=256     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=0.0     ,UpperCAmelCase_=0.0     ,UpperCAmelCase_=0.02     ,UpperCAmelCase_=1.0     ,UpperCAmelCase_=False     ,UpperCAmelCase_="sine"     ,UpperCAmelCase_="resnet50"     ,UpperCAmelCase_=True     ,UpperCAmelCase_=False     ,UpperCAmelCase_=2     ,UpperCAmelCase_=5     ,UpperCAmelCase_=2     ,UpperCAmelCase_=1     ,UpperCAmelCase_=1     ,UpperCAmelCase_=2     ,UpperCAmelCase_=5     ,UpperCAmelCase_=2     ,UpperCAmelCase_=0.25     ,**UpperCAmelCase_     ,)  ->							Optional[Any]:
           if backbone_config is not None and use_timm_backbone:
               raise ValueError("You can't specify both `backbone_config` and `use_timm_backbone`."      )

           if not use_timm_backbone:
               if backbone_config is None:
                   logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."      )
                   lowercase__		       =						CONFIG_MAPPING["resnet"](out_features=["stage4"]      )
               elif isinstance(UpperCAmelCase_     ,UpperCAmelCase_      ):
                   lowercase__		       =						backbone_config.get("model_type"      )
                   lowercase__		       =						CONFIG_MAPPING[backbone_model_type]
                   lowercase__		       =						config_class.from_dict(UpperCAmelCase_      )

           lowercase__		       =						use_timm_backbone
           lowercase__		       =						backbone_config
           lowercase__		       =						num_channels
           lowercase__		       =						num_queries
           lowercase__		       =						d_model
           lowercase__		       =						encoder_ffn_dim
           lowercase__		       =						encoder_layers
           lowercase__		       =						encoder_attention_heads
           lowercase__		       =						decoder_ffn_dim
           lowercase__		       =						decoder_layers
           lowercase__		       =						decoder_attention_heads
           lowercase__		       =						dropout
           lowercase__		       =						attention_dropout
           lowercase__		       =						activation_dropout
           lowercase__		       =						activation_function
           lowercase__		       =						init_std
           lowercase__		       =						init_xavier_std
           lowercase__		       =						encoder_layerdrop
           lowercase__		       =						decoder_layerdrop
           lowercase__		       =						encoder_layers
           lowercase__		       =						auxiliary_loss
           lowercase__		       =						position_embedding_type
           lowercase__		       =						backbone
           lowercase__		       =						use_pretrained_backbone
           lowercase__		       =						dilation
           # Hungarian matcher
           lowercase__		       =						class_cost
           lowercase__		       =						bbox_cost
           lowercase__		       =						giou_cost
           # Loss coefficients
           lowercase__		       =						mask_loss_coefficient
           lowercase__		       =						dice_loss_coefficient
           lowercase__		       =						cls_loss_coefficient
           lowercase__		       =						bbox_loss_coefficient
           lowercase__		       =						giou_loss_coefficient
           lowercase__		       =						focal_alpha
           super().__init__(is_encoder_decoder=UpperCAmelCase_     ,**UpperCAmelCase_      )



       @property
       def 							_a      (				self      )  ->							int:
           return self.encoder_attention_heads



       @property
       def 							_a      (				self      )  ->							int:
           return self.d_model







       def 							_a      (				self      )  ->							Dict:
           lowercase__		       =						copy.deepcopy(self.__dict__      )
           if self.backbone_config is not None:
               lowercase__		       =						self.backbone_config.to_dict()
           lowercase__		       =						self.__class__.model_type
           return output





class 				snake_case (UpperCamelCase   ):
       lowerCAmelCase__  :str						   =					version.parse("1.11"   )



       @property
       def 							_a      (				self      )  ->							Mapping[str, Mapping[int, str]]:
           return OrderedDict(
               [
                   ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
                   ("pixel_mask", {0: "batch"}),
               ]      )



       @property
       def 							_a      (				self      )  ->							float:
           return 1E-5







       @property
       def 							_a      (				self      )  ->							int:
           return 12









'''simple docstring'''





import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


class 				snake_case (unittest.TestCase		,      UpperCamelCase   ):



       def 							_a      (				self      )  ->							List[str]:
           lowercase__		       =						load_tool("text-classification"      )
           self.tool.setup()
           lowercase__		       =						load_tool("text-classification"     ,remote=UpperCAmelCase_      )



       def 							_a      (				self      )  ->							Any:
           lowercase__		       =						self.tool("That's quite cool"     ,["positive", "negative"]      )
           self.assertEqual(UpperCAmelCase_     ,"positive"      )



       def 							_a      (				self      )  ->							Optional[int]:
           lowercase__		       =						self.remote_tool("That's quite cool"     ,["positive", "negative"]      )
           self.assertEqual(UpperCAmelCase_     ,"positive"      )



       def 							_a      (				self      )  ->							List[Any]:
           lowercase__		       =						self.tool(text="That's quite cool"     ,labels=["positive", "negative"]      )
           self.assertEqual(UpperCAmelCase_     ,"positive"      )







       def 							_a      (				self      )  ->							List[Any]:
           lowercase__		       =						self.remote_tool(text="That's quite cool"     ,labels=["positive", "negative"]      )
           self.assertEqual(UpperCAmelCase_     ,"positive"      )




