






"""simple docstring"""





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase					=     logging.get_logger(__name__)

UpperCamelCase					=     {
    """facebook/sam-vit-huge""": """https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json""",
    """facebook/sam-vit-large""": """https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json""",
    """facebook/sam-vit-base""": """https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json""",
}







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_=256					, UpperCAmelCase_=1_024					, UpperCAmelCase_=16					, UpperCAmelCase_=16					, UpperCAmelCase_=4					, UpperCAmelCase_="gelu"					, UpperCAmelCase_=1E-6					, **UpperCAmelCase_					, )			->   Any:




          '''simple docstring'''




          super().__init__(**UpperCAmelCase_)
          lowercase__:							Dict         =     hidden_size
          lowercase__:							List[Any]         =     image_size
          lowercase__:							int         =     patch_size
          lowercase__:							Optional[Any]         =     image_size // patch_size
          lowercase__:							str         =     mask_input_channels
          lowercase__:							Any         =     num_point_embeddings
          lowercase__:							Optional[Any]         =     hidden_act
          lowercase__:							List[str]         =     layer_norm_eps







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_=256					, UpperCAmelCase_="relu"					, UpperCAmelCase_=2_048					, UpperCAmelCase_=2					, UpperCAmelCase_=8					, UpperCAmelCase_=2					, UpperCAmelCase_=3					, UpperCAmelCase_=3					, UpperCAmelCase_=256					, UpperCAmelCase_=1E-6					, **UpperCAmelCase_					, )			->   Optional[Any]:




          '''simple docstring'''




          super().__init__(**UpperCAmelCase_)
          lowercase__:							Dict         =     hidden_size
          lowercase__:							Dict         =     hidden_act
          lowercase__:							List[str]         =     mlp_dim
          lowercase__:							List[str]         =     num_hidden_layers
          lowercase__:							List[str]         =     num_attention_heads
          lowercase__:							int         =     attention_downsample_rate
          lowercase__:							Optional[int]         =     num_multimask_outputs
          lowercase__:							str         =     iou_head_depth
          lowercase__:							List[Any]         =     iou_head_hidden_dim
          lowercase__:							List[str]         =     layer_norm_eps







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_=768					, UpperCAmelCase_=256					, UpperCAmelCase_=12					, UpperCAmelCase_=12					, UpperCAmelCase_=3					, UpperCAmelCase_=1_024					, UpperCAmelCase_=16					, UpperCAmelCase_="gelu"					, UpperCAmelCase_=1E-0_6					, UpperCAmelCase_=0.0					, UpperCAmelCase_=1E-1_0					, UpperCAmelCase_=True					, UpperCAmelCase_=4.0					, UpperCAmelCase_=True					, UpperCAmelCase_=True					, UpperCAmelCase_=14					, UpperCAmelCase_=[2, 5, 8, 11]					, UpperCAmelCase_=128					, UpperCAmelCase_=None					, **UpperCAmelCase_					, )			->   Any:




          '''simple docstring'''




          super().__init__(**UpperCAmelCase_)

          lowercase__:							Tuple         =     hidden_size
          lowercase__:							Union[str, Any]         =     output_channels
          lowercase__:							List[str]         =     num_hidden_layers
          lowercase__:							Any         =     num_attention_heads
          lowercase__:							Optional[int]         =     num_channels
          lowercase__:							List[Any]         =     image_size
          lowercase__:							Dict         =     patch_size
          lowercase__:							Tuple         =     hidden_act
          lowercase__:							Union[str, Any]         =     layer_norm_eps
          lowercase__:							Dict         =     attention_dropout
          lowercase__:							List[str]         =     initializer_range
          lowercase__:							List[str]         =     qkv_bias
          lowercase__:							Tuple         =     mlp_ratio
          lowercase__:							Optional[int]         =     use_abs_pos
          lowercase__:							Dict         =     use_rel_pos
          lowercase__:							List[str]         =     window_size
          lowercase__:							Optional[int]         =     global_attn_indexes
          lowercase__:							List[Any]         =     num_pos_feats
          lowercase__:							List[Any]         =     int(hidden_size * mlp_ratio) if mlp_dim is None else mlp_dim







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   UpperCamelCase__     	=							"""sam"""
   UpperCamelCase__     	=							True





   def __init__(       self					, UpperCAmelCase_=None					, UpperCAmelCase_=None					, UpperCAmelCase_=None					, UpperCAmelCase_=0.02					, **UpperCAmelCase_					, )			->   Optional[int]:




          '''simple docstring'''




          super().__init__(**UpperCAmelCase_)
          lowercase__:							Tuple         =     vision_config if vision_config is not None else {}
          lowercase__:							Optional[int]         =     prompt_encoder_config if prompt_encoder_config is not None else {}
          lowercase__:							Dict         =     mask_decoder_config if mask_decoder_config is not None else {}

          if isinstance(UpperCAmelCase_					, UpperCAmelCase_):
                 lowercase__:							str         =     vision_config.to_dict()
          if isinstance(UpperCAmelCase_					, UpperCAmelCase_):
                 lowercase__:							List[str]         =     prompt_encoder_config.to_dict()
          if isinstance(UpperCAmelCase_					, UpperCAmelCase_):
                 lowercase__:							List[str]         =     mask_decoder_config.to_dict()

          lowercase__:							int         =     SamVisionConfig(**UpperCAmelCase_)
          lowercase__:							Optional[int]         =     SamPromptEncoderConfig(**UpperCAmelCase_)
          lowercase__:							Optional[Any]         =     SamMaskDecoderConfig(**UpperCAmelCase_)
          lowercase__:							Optional[int]         =     initializer_range





   def __lowercase							(       self)			->   Optional[Any]:




          '''simple docstring'''




          lowercase__:							List[Any]         =     copy.deepcopy(self.__dict__)
          lowercase__:							Any         =     self.vision_config.to_dict()
          lowercase__:							int         =     self.prompt_encoder_config.to_dict()
          lowercase__:							List[Any]         =     self.mask_decoder_config.to_dict()
          lowercase__:							Any         =     self.__class__.model_type
          return output










import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata

def  lowercase_						(						_A     :       str		):

      """simple docstring"""




      lowerCamelCase__						:							Optional[Any]       =    min(re.search("^ +"       ,   _A		).end() if t.startswith(" "		) else 0 for t in string.splitlines()		)
      return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(_A		)]		)


A :       Optional[int]						=   "\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n"

A :       str						=   "\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n"


A :       Optional[Any]						=   "\\n# Begin of markdown\n\nSome cool dataset card\n"







class      _lowercase					(				unittest.TestCase):


       """simple docstring"""




       def 		lowerCAmelCase	(  self				:     List[Any]			):


             '''simple docstring'''



             with tempfile.TemporaryDirectory() as tmp_dir:
                   lowerCamelCase__						:							List[str]       =    Path(__lowerCamelCase			) / "README.md"
                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							Dict       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertDictEqual(__lowerCamelCase   , {"language": ["zh", "en"], "task_ids": ["sentiment-classification"]}			)

                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							Optional[Any]       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertDictEqual(__lowerCamelCase   , {}			)

                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							int       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertEqual(__lowerCamelCase   , {}			)





       def 		lowerCAmelCase	(  self				:     Any			):


             '''simple docstring'''



             lowerCamelCase__						:							List[str]       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            "			)
             assert DatasetMetadata.from_yaml_string(__lowerCamelCase			)

             lowerCamelCase__						:							Dict       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            "			)
             with self.assertRaises(__lowerCamelCase			):
                   DatasetMetadata.from_yaml_string(__lowerCamelCase			)

             lowerCamelCase__						:							Optional[Any]       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            "			)
             assert DatasetMetadata.from_yaml_string(__lowerCamelCase			)


