
import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput





@dataclass
class 					snake_case__  ( __A       ):
	UpperCAmelCase   :							float
	UpperCAmelCase   :							Optional[float]         = None
	UpperCAmelCase   :							Optional[float]         = None





class 					snake_case__  ( unittest.TestCase       ):





	def     A				(  self							)		->			Optional[int]:
								"""simple docstring"""






								a_       :   Dict			=	ModelOutputTest(a=30							)
								self.assertEqual(x.a				,    30							)
								self.assertIsNone(x.b							)
								self.assertIsNone(x.c							)
								with self.assertRaises(UpperCamelCase_							):
															a_       :   List[str]			=	x.d





	def     A				(  self							)		->			List[str]:
								"""simple docstring"""






								a_       :   Optional[int]			=	ModelOutputTest(a=30				,    b=10							)
								self.assertEqual(x[0]				,    30							)
								self.assertEqual(x[1]				,    10							)
								self.assertEqual(x[:2]				,    (30, 10)							)
								self.assertEqual(x[:]				,    (30, 10)							)

								a_       :   Union[str, Any]			=	ModelOutputTest(a=30				,    c=10							)
								self.assertEqual(x[0]				,    30							)
								self.assertEqual(x[1]				,    10							)
								self.assertEqual(x[:2]				,    (30, 10)							)
								self.assertEqual(x[:]				,    (30, 10)							)





	def     A				(  self							)		->			int:
								"""simple docstring"""






								a_       :   List[Any]			=	ModelOutputTest(a=30				,    b=10							)
								self.assertEqual(x["""a"""]				,    30							)
								self.assertEqual(x["""b"""]				,    10							)
								with self.assertRaises(UpperCamelCase_							):
															a_       :   Union[str, Any]			=	x["""c"""]

								a_       :   Union[str, Any]			=	ModelOutputTest(a=30				,    c=10							)
								self.assertEqual(x["""a"""]				,    30							)
								self.assertEqual(x["""c"""]				,    10							)
								with self.assertRaises(UpperCamelCase_							):
															a_       :   Optional[int]			=	x["""b"""]





	def     A				(  self							)		->			Any:
								"""simple docstring"""






								a_       :   Any			=	ModelOutputTest(a=30							)
								self.assertEqual(list(x.keys()							)				,    ["""a"""]							)
								self.assertEqual(list(x.values()							)				,    [30]							)
								self.assertEqual(list(x.items()							)				,    [("""a""", 30)]							)
								self.assertEqual(list(UpperCamelCase_							)				,    ["""a"""]							)

								a_       :   str			=	ModelOutputTest(a=30				,    b=10							)
								self.assertEqual(list(x.keys()							)				,    ["""a""", """b"""]							)
								self.assertEqual(list(x.values()							)				,    [30, 10]							)
								self.assertEqual(list(x.items()							)				,    [("""a""", 30), ("""b""", 10)]							)
								self.assertEqual(list(UpperCamelCase_							)				,    ["""a""", """b"""]							)

								a_       :   str			=	ModelOutputTest(a=30				,    c=10							)
								self.assertEqual(list(x.keys()							)				,    ["""a""", """c"""]							)
								self.assertEqual(list(x.values()							)				,    [30, 10]							)
								self.assertEqual(list(x.items()							)				,    [("""a""", 30), ("""c""", 10)]							)
								self.assertEqual(list(UpperCamelCase_							)				,    ["""a""", """c"""]							)

								with self.assertRaises(UpperCamelCase_							):
															a_       :   str			=	x.update({"""d""": 20}							)
								with self.assertRaises(UpperCamelCase_							):
															del x["a"]
								with self.assertRaises(UpperCamelCase_							):
															a_       :   Optional[int]			=	x.pop("""a"""							)
								with self.assertRaises(UpperCamelCase_							):
															a_       :   List[str]			=	x.setdefault("""d"""				,    32							)





	def     A				(  self							)		->			List[str]:
								"""simple docstring"""






								a_       :   List[Any]			=	ModelOutputTest(a=30							)
								a_       :   int			=	10
								self.assertEqual(x.a				,    10							)
								self.assertEqual(x["""a"""]				,    10							)





	def     A				(  self							)		->			Tuple:
								"""simple docstring"""






								a_       :   Tuple			=	ModelOutputTest(a=30							)
								a_       :   Dict			=	10
								self.assertEqual(x.a				,    10							)
								self.assertEqual(x["""a"""]				,    10							)





	def     A				(  self							)		->			List[str]:
								"""simple docstring"""






								a_       :   str			=	ModelOutputTest({"""a""": 30, """b""": 10}							)
								self.assertEqual(list(x.keys()							)				,    ["""a""", """b"""]							)
								self.assertEqual(x.a				,    30							)
								self.assertEqual(x.b				,    10							)





	def     A				(  self							)		->			Union[str, Any]:
								"""simple docstring"""






								a_       :   Tuple			=	ModelOutputTest([("""a""", 30), ("""b""", 10)]							)
								self.assertEqual(list(x.keys()							)				,    ["""a""", """b"""]							)
								self.assertEqual(x.a				,    30							)
								self.assertEqual(x.b				,    10							)

								with self.assertRaises(UpperCamelCase_							):
															a_       :   int			=	ModelOutputTest([("""a""", 30), (10, 10)]							)

								a_       :   Optional[int]			=	ModelOutputTest(a=(30, 30)							)
								self.assertEqual(list(x.keys()							)				,    ["""a"""]							)
								self.assertEqual(x.a				,    (30, 30)							)






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


SCREAMING_SNAKE_CASE : Dict          =    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE : str          =    {
    "apple/mobilevit-small": "https://huggingface.co/apple/mobilevit-small/resolve/main/config.json",
    "apple/mobilevit-x-small": "https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json",
    "apple/mobilevit-xx-small": "https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json",
    "apple/deeplabv3-mobilevit-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-x-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-xx-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}





class 					snake_case__  ( __A       ):
	UpperCAmelCase   :							List[str]         = """mobilevit"""





	def __init__(  self				,    UpperCamelCase_=3				,    UpperCamelCase_=256				,    UpperCamelCase_=2				,    UpperCamelCase_=[144, 192, 240]				,    UpperCamelCase_=[16, 32, 64, 96, 128, 160, 640]				,    UpperCamelCase_=4				,    UpperCamelCase_=2.0				,    UpperCamelCase_=4.0				,    UpperCamelCase_="silu"				,    UpperCamelCase_=3				,    UpperCamelCase_=32				,    UpperCamelCase_=0.1				,    UpperCamelCase_=0.0				,    UpperCamelCase_=0.1				,    UpperCamelCase_=0.02				,    UpperCamelCase_=1e-5				,    UpperCamelCase_=True				,    UpperCamelCase_=256				,    UpperCamelCase_=[6, 12, 18]				,    UpperCamelCase_=0.1				,    UpperCamelCase_=255				,    **UpperCamelCase_				,    )		->			str:
								"""simple docstring"""






								super().__init__(**UpperCamelCase_							)

								a_       :   Optional[int]			=	num_channels
								a_       :   Optional[Any]			=	image_size
								a_       :   int			=	patch_size
								a_       :   List[str]			=	hidden_sizes
								a_       :   Optional[int]			=	neck_hidden_sizes
								a_       :   List[Any]			=	num_attention_heads
								a_       :   Union[str, Any]			=	mlp_ratio
								a_       :   List[str]			=	expand_ratio
								a_       :   str			=	hidden_act
								a_       :   Union[str, Any]			=	conv_kernel_size
								a_       :   Optional[Any]			=	output_stride
								a_       :   Union[str, Any]			=	hidden_dropout_prob
								a_       :   List[Any]			=	attention_probs_dropout_prob
								a_       :   List[Any]			=	classifier_dropout_prob
								a_       :   Union[str, Any]			=	initializer_range
								a_       :   List[Any]			=	layer_norm_eps
								a_       :   str			=	qkv_bias

								# decode head attributes for semantic segmentation
								a_       :   Optional[Any]			=	aspp_out_channels
								a_       :   Any			=	atrous_rates
								a_       :   Union[str, Any]			=	aspp_dropout_prob
								a_       :   Any			=	semantic_loss_ignore_index





class 					snake_case__  ( __A       ):
	UpperCAmelCase   :							Optional[int]         = version.parse("""1.11"""       )





	@property
	def     A				(  self							)		->			Mapping[str, Mapping[int, str]]:
								"""simple docstring"""






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





	@property
	def     A				(  self							)		->			Mapping[str, Mapping[int, str]]:
								"""simple docstring"""






								if self.task == "image-classification":
															return OrderedDict([("""logits""", {0: """batch"""})]							)
								else:
															return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]							)





	@property
	def     A				(  self							)		->			float:
								"""simple docstring"""






								return 1e-4


