






import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


_a    :   Any        =			logging.get_logger(__name__)

_a    :   Dict        =			{
    """Salesforce/instruct-blip-flan-t5""": """https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json""",
}







class 	_UpperCAmelCase  (  _A		):




      """simple docstring"""



      A          =    '''instructblip_vision_model'''
      def __init__(   self    ,	_lowerCAmelCase=1_408    ,	_lowerCAmelCase=6_144    ,	_lowerCAmelCase=39    ,	_lowerCAmelCase=16    ,	_lowerCAmelCase=224    ,	_lowerCAmelCase=14    ,	_lowerCAmelCase="gelu"    ,	_lowerCAmelCase=1e-6    ,	_lowerCAmelCase=0.0    ,	_lowerCAmelCase=1e-10    ,	_lowerCAmelCase=True    ,	**_lowerCAmelCase    ,	):



          '''simple docstring'''
          super().__init__(**_lowerCAmelCase		)

          lowerCAmelCase__   :Tuple      							=				hidden_size
          lowerCAmelCase__   :Any      							=				intermediate_size
          lowerCAmelCase__   :Tuple      							=				num_hidden_layers
          lowerCAmelCase__   :Any      							=				num_attention_heads
          lowerCAmelCase__   :List[str]      							=				patch_size
          lowerCAmelCase__   :str      							=				image_size
          lowerCAmelCase__   :int      							=				initializer_range
          lowerCAmelCase__   :Dict      							=				attention_dropout
          lowerCAmelCase__   :List[Any]      							=				layer_norm_eps
          lowerCAmelCase__   :List[str]      							=				hidden_act
          lowerCAmelCase__   :List[str]      							=				qkv_bias



      @classmethod
      def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	**_lowerCAmelCase		):



          '''simple docstring'''
          cls._set_token_in_kwargs(_lowerCAmelCase		)

          lowerCAmelCase__							,lowerCAmelCase__   :Union[str, Any]      							=				cls.get_config_dict(_lowerCAmelCase    ,	**_lowerCAmelCase		)

          # get the vision config dict if we are loading from InstructBlipConfig
          if config_dict.get("model_type"		) == "instructblip":
              lowerCAmelCase__   :Dict      							=				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(_lowerCAmelCase    ,	**_lowerCAmelCase		)







class 	_UpperCAmelCase  (  _A		):




      """simple docstring"""



      A          =    '''instructblip_qformer'''
      def __init__(   self    ,	_lowerCAmelCase=30_522    ,	_lowerCAmelCase=768    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=3_072    ,	_lowerCAmelCase="gelu"    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=512    ,	_lowerCAmelCase=0.02    ,	_lowerCAmelCase=1e-12    ,	_lowerCAmelCase=0    ,	_lowerCAmelCase="absolute"    ,	_lowerCAmelCase=2    ,	_lowerCAmelCase=1_408    ,	**_lowerCAmelCase    ,	):



          '''simple docstring'''
          super().__init__(pad_token_id=_lowerCAmelCase    ,	**_lowerCAmelCase		)

          lowerCAmelCase__   :str      							=				vocab_size
          lowerCAmelCase__   :int      							=				hidden_size
          lowerCAmelCase__   :Tuple      							=				num_hidden_layers
          lowerCAmelCase__   :Optional[Any]      							=				num_attention_heads
          lowerCAmelCase__   :List[Any]      							=				hidden_act
          lowerCAmelCase__   :int      							=				intermediate_size
          lowerCAmelCase__   :Any      							=				hidden_dropout_prob
          lowerCAmelCase__   :Union[str, Any]      							=				attention_probs_dropout_prob
          lowerCAmelCase__   :Any      							=				max_position_embeddings
          lowerCAmelCase__   :List[Any]      							=				initializer_range
          lowerCAmelCase__   :List[str]      							=				layer_norm_eps
          lowerCAmelCase__   :str      							=				position_embedding_type
          lowerCAmelCase__   :Dict      							=				cross_attention_frequency
          lowerCAmelCase__   :Optional[Any]      							=				encoder_hidden_size



      @classmethod
      def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	**_lowerCAmelCase		):



          '''simple docstring'''
          cls._set_token_in_kwargs(_lowerCAmelCase		)

          lowerCAmelCase__							,lowerCAmelCase__   :Union[str, Any]      							=				cls.get_config_dict(_lowerCAmelCase    ,	**_lowerCAmelCase		)

          # get the qformer config dict if we are loading from InstructBlipConfig
          if config_dict.get("model_type"		) == "instructblip":
              lowerCAmelCase__   :int      							=				config_dict["qformer_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(_lowerCAmelCase    ,	**_lowerCAmelCase		)







class 	_UpperCAmelCase  (  _A		):




      """simple docstring"""



      A          =    '''instructblip'''
      A          =    True
      def __init__(   self    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=32    ,	**_lowerCAmelCase		):



          '''simple docstring'''
          super().__init__(**_lowerCAmelCase		)

          if vision_config is None:
              lowerCAmelCase__   :Any      							=				{}
              logger.info("vision_config is None. initializing the InstructBlipVisionConfig with default values."		)

          if qformer_config is None:
              lowerCAmelCase__   :Tuple      							=				{}
              logger.info("qformer_config is None. Initializing the InstructBlipQFormerConfig with default values."		)

          if text_config is None:
              lowerCAmelCase__   :Any      							=				{}
              logger.info("text_config is None. Initializing the text config with default values (`OPTConfig`)."		)

          lowerCAmelCase__   :Optional[int]      							=				InstructBlipVisionConfig(**_lowerCAmelCase		)
          lowerCAmelCase__   :str      							=				InstructBlipQFormerConfig(**_lowerCAmelCase		)
          lowerCAmelCase__   :int      							=				text_config["model_type"] if "model_type" in text_config else "opt"
          lowerCAmelCase__   :Optional[Any]      							=				CONFIG_MAPPING[text_model_type](**_lowerCAmelCase		)

          lowerCAmelCase__   :Optional[int]      							=				self.text_config.tie_word_embeddings
          lowerCAmelCase__   :Union[str, Any]      							=				self.text_config.is_encoder_decoder

          lowerCAmelCase__   :int      							=				num_query_tokens
          lowerCAmelCase__   :Optional[int]      							=				self.vision_config.hidden_size
          lowerCAmelCase__   :List[Any]      							=				self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
          lowerCAmelCase__   :str      							=				1.0
          lowerCAmelCase__   :Union[str, Any]      							=				0.02
      @classmethod
      def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	_lowerCAmelCase    ,	_lowerCAmelCase    ,	**_lowerCAmelCase    ,	):



          '''simple docstring'''
          return cls(
              vision_config=vision_config.to_dict()    ,	qformer_config=qformer_config.to_dict()    ,	text_config=text_config.to_dict()    ,	**_lowerCAmelCase    ,	)



      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[Any]      							=				copy.deepcopy(self.__dict__		)
          lowerCAmelCase__   :Optional[int]      							=				self.vision_config.to_dict()
          lowerCAmelCase__   :Optional[Any]      							=				self.qformer_config.to_dict()
          lowerCAmelCase__   :str      							=				self.text_config.to_dict()
          lowerCAmelCase__   :Union[str, Any]      							=				self.__class__.model_type
          return output











from argparse import ArgumentParser

from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.utils.logging import set_verbosity_info


def 				snake_case__							(							UpperCAmelCase							:  Dict       ):
    return {key.lstrip("-"       ): value for key, value in zip(unknown_args[::2]    ,			unknown_args[1::2]       )}


def 				snake_case__							(							):
    lowerCAmelCase__   :str      							=				ArgumentParser(
        "HuggingFace Datasets CLI tool"    ,			usage="datasets-cli <command> [<args>]"    ,			allow_abbrev=UpperCAmelCase       )
    lowerCAmelCase__   :Any      							=				parser.add_subparsers(help="datasets-cli command helpers"       )
    set_verbosity_info()

    # Register commands
    ConvertCommand.register_subcommand(UpperCAmelCase       )
    EnvironmentCommand.register_subcommand(UpperCAmelCase       )
    TestCommand.register_subcommand(UpperCAmelCase       )
    RunBeamCommand.register_subcommand(UpperCAmelCase       )
    DummyDataCommand.register_subcommand(UpperCAmelCase       )

    # Parse args
    lowerCAmelCase__							,lowerCAmelCase__   :int      							=				parser.parse_known_args()
    if not hasattr(UpperCAmelCase    ,			"func"       ):
        parser.print_help()
        exit(1       )
    lowerCAmelCase__   :Optional[int]      							=				parse_unknown_args(UpperCAmelCase       )

    # Run
    lowerCAmelCase__   :str      							=				args.func(UpperCAmelCase    ,			**UpperCAmelCase       )
    service.run()


if __name__ == "__main__":
 main()



