



'''simple docstring'''



import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard






class        UpperCAmelCase__						(		unittest.TestCase			):



					def 							UpperCAmelCase_			(     self  )  ->      Any:
						__lowerCAmelCase       				=	{
						    "model_details": {
						        "Organization": "testing",
						        "Model date": "today",
						        "Model version": "v2.1, Developed by Test Corp in 2019.",
						        "Architecture": "Convolutional Neural Network.",
						    },
						    "metrics": "BLEU and ROUGE-1",
						    "evaluation_data": {
						        "Datasets": {"BLEU": "My-great-dataset-v1", "ROUGE-1": "My-short-dataset-v2.1"},
						        "Preprocessing": "See details on https://arxiv.org/pdf/1810.03993.pdf",
						    },
						    "training_data": {
						        "Dataset": "English Wikipedia dump dated 2018-12-01",
						        "Preprocessing": (
						            "Using SentencePiece vocabulary of size 52k tokens. See details on"
						            " https://arxiv.org/pdf/1810.03993.pdf"
						        ),
						    },
						    "quantitative_analyses": {"BLEU": 55.1, "ROUGE-1": 76},
						}



					def 							UpperCAmelCase_			(     self  )  ->      str:
						__lowerCAmelCase       				=	ModelCard.from_dict(self.inputs_dict  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"model_details"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"intended_use"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"factors"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"metrics"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"evaluation_data"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"training_data"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"quantitative_analyses"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"ethical_considerations"  )  )
						self.assertTrue(hasattr(UpperCamelCase      ,					"caveats_and_recommendations"  )  )



					def 							UpperCAmelCase_			(     self  )  ->      List[str]:
						__lowerCAmelCase       				=	ModelCard.from_dict(self.inputs_dict  )
						__lowerCAmelCase       				=	json.loads(modelcard.to_json_string()  )
						for key, value in self.inputs_dict.items():
							self.assertEqual(obj[key]      ,					UpperCamelCase  )



					def 							UpperCAmelCase_			(     self  )  ->      Optional[Any]:
						__lowerCAmelCase       				=	ModelCard.from_dict(self.inputs_dict  )

						with tempfile.TemporaryDirectory() as tmpdirname:
							__lowerCAmelCase       				=	os.path.join(UpperCamelCase      ,					"modelcard.json"  )
							model_card_first.to_json_file(UpperCamelCase  )
							__lowerCAmelCase       				=	ModelCard.from_json_file(UpperCamelCase  )

						self.assertEqual(model_card_second.to_dict()      ,					model_card_first.to_dict()  )



					def 							UpperCAmelCase_			(     self  )  ->      Tuple:
						__lowerCAmelCase       				=	ModelCard.from_dict(self.inputs_dict  )

						with tempfile.TemporaryDirectory() as tmpdirname:
							model_card_first.save_pretrained(UpperCamelCase  )
							__lowerCAmelCase       				=	ModelCard.from_pretrained(UpperCamelCase  )

						self.assertEqual(model_card_second.to_dict()      ,					model_card_first.to_dict()  )


"""simple docstring"""



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_       :						Union[str, Any]					=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    {
    'MBZUAI/swiftformer-xs': 'https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json',
}



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    UpperCAmelCase    			=       "swiftformer"

    def __init__(  self:			Tuple     ,    UpperCamelCase:			int=3     ,    UpperCamelCase:			Union[str, Any]=[3, 3, 6, 4]     ,    UpperCamelCase:			List[str]=[48, 56, 1_12, 2_20]     ,    UpperCamelCase:			List[Any]=4     ,    UpperCamelCase:			List[Any]=[True, True, True, True]     ,    UpperCamelCase:			str="gelu"     ,    UpperCamelCase:			Tuple=3     ,    UpperCamelCase:			Dict=2     ,    UpperCamelCase:			int=1     ,    UpperCamelCase:			List[Any]=0.0     ,    UpperCamelCase:			Any=True     ,    UpperCamelCase:			List[Any]=1e-5     ,    UpperCamelCase:			List[Any]=1e-5     ,    **UpperCamelCase:			Any     ,    ):






         """simple docstring"""


         super().__init__(**UpperCamelCase							)
         A__				      =	num_channels
         A__				      =	depths
         A__				      =	embed_dims
         A__				      =	mlp_ratio
         A__				      =	downsamples
         A__				      =	hidden_act
         A__				      =	down_patch_size
         A__				      =	down_stride
         A__				      =	down_pad
         A__				      =	drop_path_rate
         A__				      =	use_layer_scale
         A__				      =	layer_scale_init_value
         A__				      =	batch_norm_eps



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    UpperCAmelCase    			=       version.parse("1.11"					)

    @property
    def 					UpperCamelCase						(  self:			int							):






         """simple docstring"""


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





    @property
    def 					UpperCamelCase						(  self:			Any							):






         """simple docstring"""


         return 1e-4






