




import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
  pass

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


_lowerCamelCase      :						Any							=  logging.get_logger(__name__)

_lowerCamelCase      :						Tuple							=  {
    """kakaobrain/align-base""": """https://huggingface.co/kakaobrain/align-base/resolve/main/config.json""",
}


class 							UpperCamelCase_       (					UpperCAmelCase__	):

    '''simple docstring'''






    UpperCAmelCase__				    = '''align_text_model'''


    def __init__(     self :      Optional[int]   ,					UpperCAmelCase__ :      List[Any]=30_522   ,					UpperCAmelCase__ :      Optional[Any]=768   ,					UpperCAmelCase__ :      List[str]=12   ,					UpperCAmelCase__ :      Optional[int]=12   ,					UpperCAmelCase__ :      Optional[Any]=3_072   ,					UpperCAmelCase__ :      Union[str, Any]="gelu"   ,					UpperCAmelCase__ :      Any=0.1   ,					UpperCAmelCase__ :      Union[str, Any]=0.1   ,					UpperCAmelCase__ :      Any=512   ,					UpperCAmelCase__ :      Tuple=2   ,					UpperCAmelCase__ :      List[Any]=0.02   ,					UpperCAmelCase__ :      Optional[int]=1e-12   ,					UpperCAmelCase__ :      str=0   ,					UpperCAmelCase__ :      Optional[int]="absolute"   ,					UpperCAmelCase__ :      Union[str, Any]=True   ,					**UpperCAmelCase__ :      Optional[Any]   ,					)		->Union[str, Any]:





           '''simple docstring'''

           super().__init__(**UpperCAmelCase__)

           A__ 					=       vocab_size
           A__ 					=       hidden_size
           A__ 					=       num_hidden_layers
           A__ 					=       num_attention_heads
           A__ 					=       hidden_act
           A__ 					=       intermediate_size
           A__ 					=       hidden_dropout_prob
           A__ 					=       attention_probs_dropout_prob
           A__ 					=       max_position_embeddings
           A__ 					=       type_vocab_size
           A__ 					=       initializer_range
           A__ 					=       layer_norm_eps
           A__ 					=       position_embedding_type
           A__ 					=       use_cache
           A__ 					=       pad_token_id





    @classmethod
    def 			SCREAMING_SNAKE_CASE				(     cls :      Any   ,					UpperCAmelCase__ :      Union[str, os.PathLike]   ,					**UpperCAmelCase__ :      Optional[Any])		->"PretrainedConfig":





           '''simple docstring'''

           cls._set_token_in_kwargs(UpperCAmelCase__)

           A__					,				A__ 					=       cls.get_config_dict(UpperCAmelCase__   ,					**UpperCAmelCase__)

           # get the text config dict if we are loading from AlignConfig
           if config_dict.get('''model_type''') == "align":
                  A__ 					=       config_dict['''text_config''']

           if "model_type" in config_dict and hasattr(cls   ,					'''model_type''') and config_dict["model_type"] != cls.model_type:
                  logger.warning(
                      f"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
                      f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""")

           return cls.from_dict(UpperCAmelCase__   ,					**UpperCAmelCase__)


class 							UpperCamelCase_       (					UpperCAmelCase__	):

    '''simple docstring'''






    UpperCAmelCase__				    = '''align_vision_model'''


    def __init__(     self :      int   ,					UpperCAmelCase__ :      int = 3   ,					UpperCAmelCase__ :      int = 600   ,					UpperCAmelCase__ :      float = 2.0   ,					UpperCAmelCase__ :      float = 3.1   ,					UpperCAmelCase__ :      int = 8   ,					UpperCAmelCase__ :      List[int] = [3, 3, 5, 3, 5, 5, 3]   ,					UpperCAmelCase__ :      List[int] = [32, 16, 24, 40, 80, 112, 192]   ,					UpperCAmelCase__ :      List[int] = [16, 24, 40, 80, 112, 192, 320]   ,					UpperCAmelCase__ :      List[int] = []   ,					UpperCAmelCase__ :      List[int] = [1, 2, 2, 2, 1, 2, 1]   ,					UpperCAmelCase__ :      List[int] = [1, 2, 2, 3, 3, 4, 1]   ,					UpperCAmelCase__ :      List[int] = [1, 6, 6, 6, 6, 6, 6]   ,					UpperCAmelCase__ :      float = 0.25   ,					UpperCAmelCase__ :      str = "swish"   ,					UpperCAmelCase__ :      int = 2_560   ,					UpperCAmelCase__ :      str = "mean"   ,					UpperCAmelCase__ :      float = 0.02   ,					UpperCAmelCase__ :      float = 0.001   ,					UpperCAmelCase__ :      float = 0.99   ,					UpperCAmelCase__ :      float = 0.2   ,					**UpperCAmelCase__ :      int   ,					)		->Union[str, Any]:





           '''simple docstring'''

           super().__init__(**UpperCAmelCase__)

           A__ 					=       num_channels
           A__ 					=       image_size
           A__ 					=       width_coefficient
           A__ 					=       depth_coefficient
           A__ 					=       depth_divisor
           A__ 					=       kernel_sizes
           A__ 					=       in_channels
           A__ 					=       out_channels
           A__ 					=       depthwise_padding
           A__ 					=       strides
           A__ 					=       num_block_repeats
           A__ 					=       expand_ratios
           A__ 					=       squeeze_expansion_ratio
           A__ 					=       hidden_act
           A__ 					=       hidden_dim
           A__ 					=       pooling_type
           A__ 					=       initializer_range
           A__ 					=       batch_norm_eps
           A__ 					=       batch_norm_momentum
           A__ 					=       drop_connect_rate
           A__ 					=       sum(UpperCAmelCase__) * 4





    @classmethod
    def 			SCREAMING_SNAKE_CASE				(     cls :      Optional[Any]   ,					UpperCAmelCase__ :      Union[str, os.PathLike]   ,					**UpperCAmelCase__ :      Dict)		->"PretrainedConfig":





           '''simple docstring'''

           cls._set_token_in_kwargs(UpperCAmelCase__)

           A__					,				A__ 					=       cls.get_config_dict(UpperCAmelCase__   ,					**UpperCAmelCase__)

           # get the vision config dict if we are loading from AlignConfig
           if config_dict.get('''model_type''') == "align":
                  A__ 					=       config_dict['''vision_config''']

           if "model_type" in config_dict and hasattr(cls   ,					'''model_type''') and config_dict["model_type"] != cls.model_type:
                  logger.warning(
                      f"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
                      f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""")

           return cls.from_dict(UpperCAmelCase__   ,					**UpperCAmelCase__)


class 							UpperCamelCase_       (					UpperCAmelCase__	):

    '''simple docstring'''






    UpperCAmelCase__				    = '''align'''
    UpperCAmelCase__				    = True


    def __init__(     self :      Union[str, Any]   ,					UpperCAmelCase__ :      Optional[Any]=None   ,					UpperCAmelCase__ :      Optional[Any]=None   ,					UpperCAmelCase__ :      List[Any]=640   ,					UpperCAmelCase__ :      List[Any]=1.0   ,					UpperCAmelCase__ :      Dict=0.02   ,					**UpperCAmelCase__ :      Any   ,					)		->Dict:





           '''simple docstring'''

           super().__init__(**UpperCAmelCase__)

           if text_config is None:
                  A__ 					=       {}
                  logger.info('''text_config is None. Initializing the AlignTextConfig with default values.''')

           if vision_config is None:
                  A__ 					=       {}
                  logger.info('''vision_config is None. Initializing the AlignVisionConfig with default values.''')

           A__ 					=       AlignTextConfig(**UpperCAmelCase__)
           A__ 					=       AlignVisionConfig(**UpperCAmelCase__)

           A__ 					=       projection_dim
           A__ 					=       temperature_init_value
           A__ 					=       initializer_range


    @classmethod
    def 			SCREAMING_SNAKE_CASE				(     cls :      Dict   ,					UpperCAmelCase__ :      AlignTextConfig   ,					UpperCAmelCase__ :      AlignVisionConfig   ,					**UpperCAmelCase__ :      Tuple)		->Tuple:





           '''simple docstring'''

           return cls(text_config=text_config.to_dict()   ,					vision_config=vision_config.to_dict()   ,					**UpperCAmelCase__)





    def 			SCREAMING_SNAKE_CASE				(     self :      Any)		->Optional[int]:





           '''simple docstring'''

           A__ 					=       copy.deepcopy(self.__dict__)
           A__ 					=       self.text_config.to_dict()
           A__ 					=       self.vision_config.to_dict()
           A__ 					=       self.__class__.model_type
           return output










import os

import pytest

from transformers.dynamic_module_utils import get_imports


UpperCamelCase    							=      '\nimport os\n'

UpperCamelCase    							=      '\ndef foo():\n    import os\n    return False\n'

UpperCamelCase    							=      '\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n'

UpperCamelCase    							=      '\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n'

UpperCamelCase    							=      [
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]


@pytest.mark.parametrize("""case"""					,							__lowerCAmelCase							)
def 				__lowerCamelCase     (							__lowerCAmelCase							:					List[Any]					,							__lowerCAmelCase							:					Optional[Any]							)     ->  str:
   __UpperCamelCase	:			str					=					os.path.join(__lowerCAmelCase					,							"""test_file.py"""							)
   with open(__lowerCAmelCase					,							"""w"""							) as _tmp_file:
      _tmp_file.write(__lowerCAmelCase							)

   __UpperCamelCase	:			Optional[int]					=					get_imports(__lowerCAmelCase							)
   assert parsed_imports == ["os"]



