



import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
	import torch

if is_soundfile_availble():
	import soundfile as sf

if is_vision_available():
	from PIL import Image



def    snake_case_				(    _SCREAMING_SNAKE_CASE=""   ):
	__lowercase		       =			tempfile.mkdtemp()
	return os.path.join(_SCREAMING_SNAKE_CASE  ,	str(uuid.uuida()   ) + suffix   )

@require_soundfile
@require_torch
class   _A   ( unittest.TestCase	):


						'''simple docstring'''





						def     _snake_case	(	self	:							str	):






							'''simple docstring'''



							__lowercase		       =			torch.rand(12							,      dtype=torch.floataa	) - 0.5
							__lowercase		       =			AgentAudio(lowerCamelCase	)
							__lowercase		       =			str(agent_type.to_string()	)

							# Ensure that the tensor and the agent_type's tensor are the same
							self.assertTrue(torch.allclose(lowerCamelCase							,      agent_type.to_raw()							,      atol=1e-4	)	)

							del agent_type

							# Ensure the path remains even after the object deletion
							self.assertTrue(os.path.exists(lowerCamelCase	)	)

							# Ensure that the file contains the same value as the original tensor
							__lowercase       ,    __lowercase		       =			sf.read(lowerCamelCase	)
							self.assertTrue(torch.allclose(lowerCamelCase							,      torch.tensor(lowerCamelCase	)							,      atol=1e-4	)	)



						def     _snake_case	(	self	:							Optional[Any]	):






							'''simple docstring'''



							__lowercase		       =			torch.rand(12							,      dtype=torch.floataa	) - 0.5
							__lowercase		       =			get_new_path(suffix=".wav"	)
							sf.write(lowerCamelCase							,      lowerCamelCase							,      16_000	)

							__lowercase		       =			AgentAudio(lowerCamelCase	)

							self.assertTrue(torch.allclose(lowerCamelCase							,      agent_type.to_raw()							,      atol=1e-4	)	)
							self.assertEqual(agent_type.to_string()							,      lowerCamelCase	)

@require_vision
@require_torch
class   _A   ( unittest.TestCase	):


						'''simple docstring'''





						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							__lowercase		       =			torch.randint(0							,      256							,      (64, 64, 3)	)
							__lowercase		       =			AgentImage(lowerCamelCase	)
							__lowercase		       =			str(agent_type.to_string()	)

							# Ensure that the tensor and the agent_type's tensor are the same
							self.assertTrue(torch.allclose(lowerCamelCase							,      agent_type._tensor							,      atol=1e-4	)	)

							self.assertIsInstance(agent_type.to_raw()							,      Image.Image	)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(lowerCamelCase	)	)



						def     _snake_case	(	self	:							List[str]	):






							'''simple docstring'''



							__lowercase		       =			Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"
							__lowercase		       =			Image.open(lowerCamelCase	)
							__lowercase		       =			AgentImage(lowerCamelCase	)

							self.assertTrue(path.samefile(agent_type.to_string()	)	)
							self.assertTrue(image == agent_type.to_raw()	)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(lowerCamelCase	)	)



						def     _snake_case	(	self	:							int	):






							'''simple docstring'''



							__lowercase		       =			Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"
							__lowercase		       =			Image.open(lowerCamelCase	)
							__lowercase		       =			AgentImage(lowerCamelCase	)

							self.assertFalse(path.samefile(agent_type.to_string()	)	)
							self.assertTrue(image == agent_type.to_raw()	)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(lowerCamelCase	)	)

class   _A   ( unittest.TestCase	):


						'''simple docstring'''





						def     _snake_case	(	self	:							Optional[Any]	):






							'''simple docstring'''



							__lowercase		       =			"Hey!"
							__lowercase		       =			AgentText(lowerCamelCase	)

							self.assertEqual(lowerCamelCase							,      agent_type.to_string()	)
							self.assertEqual(lowerCamelCase							,      agent_type.to_raw()	)
							self.assertEqual(lowerCamelCase							,      lowerCamelCase	)








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


snake_case__					:     int    		=   logging.get_logger(__name__)

snake_case__					:     Optional[int]    		=   {
    """microsoft/conditional-detr-resnet-50""": (
        """https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"""
    ),
}

class   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     Dict      							=      """conditional_detr"""
						_snake_case			:     Union[str, Any]      							=      ["""past_key_values"""]
						_snake_case			:     Optional[int]      							=      {
						    """hidden_size""": """d_model""",
						    """num_attention_heads""": """encoder_attention_heads""",
						}



						def __init__(	self	:							Optional[Any]							,      lowerCamelCase	:							int=True							,      lowerCamelCase	:							Tuple=None							,      lowerCamelCase	:							Optional[int]=3							,      lowerCamelCase	:							Optional[int]=300							,      lowerCamelCase	:							List[Any]=6							,      lowerCamelCase	:							str=2_048							,      lowerCamelCase	:							Any=8							,      lowerCamelCase	:							List[str]=6							,      lowerCamelCase	:							Any=2_048							,      lowerCamelCase	:							List[Any]=8							,      lowerCamelCase	:							Optional[Any]=0.0							,      lowerCamelCase	:							List[str]=0.0							,      lowerCamelCase	:							List[Any]=True							,      lowerCamelCase	:							str="relu"							,      lowerCamelCase	:							int=256							,      lowerCamelCase	:							Dict=0.1							,      lowerCamelCase	:							Optional[Any]=0.0							,      lowerCamelCase	:							Dict=0.0							,      lowerCamelCase	:							Tuple=0.02							,      lowerCamelCase	:							int=1.0							,      lowerCamelCase	:							Tuple=False							,      lowerCamelCase	:							List[str]="sine"							,      lowerCamelCase	:							List[Any]="resnet50"							,      lowerCamelCase	:							Any=True							,      lowerCamelCase	:							Any=False							,      lowerCamelCase	:							List[Any]=2							,      lowerCamelCase	:							List[Any]=5							,      lowerCamelCase	:							str=2							,      lowerCamelCase	:							Dict=1							,      lowerCamelCase	:							List[str]=1							,      lowerCamelCase	:							Union[str, Any]=2							,      lowerCamelCase	:							Dict=5							,      lowerCamelCase	:							List[Any]=2							,      lowerCamelCase	:							Tuple=0.25							,      **lowerCamelCase	:							List[str]							,      ):






							'''simple docstring'''



							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(lowerCamelCase							,      lowerCamelCase	):
									__lowercase		       =			backbone_config.get("model_type"	)
									__lowercase		       =			CONFIG_MAPPING[backbone_model_type]
									__lowercase		       =			config_class.from_dict(lowerCamelCase	)

							__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=lowerCamelCase							,      **lowerCamelCase	)



						@property
						def     _snake_case	(	self	:							Tuple	):






							'''simple docstring'''



							return self.encoder_attention_heads



						@property
						def     _snake_case	(	self	:							str	):






							'''simple docstring'''



							return self.d_model



						def     _snake_case	(	self	:							int	):






							'''simple docstring'''



							__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   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     Any      							=      version.parse("""1.11"""	)



						@property
						def     _snake_case	(	self	:							Tuple	):






							'''simple docstring'''



							return OrderedDict(
							    [
							        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
							        ("pixel_mask", {0: "batch"}),
							    ]	)



						@property
						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							return 1e-5



						@property
						def     _snake_case	(	self	:							Optional[Any]	):






							'''simple docstring'''



							return 12



