

"""simple docstring"""






import copy
import os
from typing import Union

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


__lowerCamelCase										=		logging.get_logger(__name__)

__lowerCamelCase										=		{
    "Salesforce/blip-vqa-base": "https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/config.json",
    "Salesforce/blip-vqa-capfit-large": (
        "https://huggingface.co/Salesforce/blip-vqa-base-capfit/resolve/main/config.json"
    ),
    "Salesforce/blip-image-captioning-base": (
        "https://huggingface.co/Salesforce/blip-image-captioning-base/resolve/main/config.json"
    ),
    "Salesforce/blip-image-captioning-large": (
        "https://huggingface.co/Salesforce/blip-image-captioning-large/resolve/main/config.json"
    ),
    "Salesforce/blip-itm-base-coco": "https://huggingface.co/Salesforce/blip-itm-base-coco/resolve/main/config.json",
    "Salesforce/blip-itm-large-coco": "https://huggingface.co/Salesforce/blip-itm-large-coco/resolve/main/config.json",
    "Salesforce/blip-itm-base-flikr": "https://huggingface.co/Salesforce/blip-itm-base-flikr/resolve/main/config.json",
    "Salesforce/blip-itm-large-flikr": (
        "https://huggingface.co/Salesforce/blip-itm-large-flikr/resolve/main/config.json"
    ),
}
class        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       '''blip_text_model'''







     def __init__(      self ,						UpperCamelCase_=3_0524 ,						UpperCamelCase_=768 ,						UpperCamelCase_=768 ,						UpperCamelCase_=3072 ,						UpperCamelCase_=768 ,						UpperCamelCase_=12 ,						UpperCamelCase_=8 ,						UpperCamelCase_=512 ,						UpperCamelCase_="gelu" ,						UpperCamelCase_=1E-1_2 ,						UpperCamelCase_=0.0 ,						UpperCamelCase_=0.0 ,						UpperCamelCase_=0.0_2 ,						UpperCamelCase_=3_0522 ,						UpperCamelCase_=2 ,						UpperCamelCase_=0 ,						UpperCamelCase_=102 ,						UpperCamelCase_=True ,						UpperCamelCase_=True ,						**UpperCamelCase_ ,						):
      super().__init__(
          pad_token_id=UpperCamelCase_ ,						bos_token_id=UpperCamelCase_ ,						eos_token_id=UpperCamelCase_ ,						sep_token_id=UpperCamelCase_ ,						**UpperCamelCase_ ,						)

      __magic_name__     =      vocab_size
      __magic_name__     =      hidden_size
      __magic_name__     =      encoder_hidden_size
      __magic_name__     =      intermediate_size
      __magic_name__     =      projection_dim
      __magic_name__     =      hidden_dropout_prob
      __magic_name__     =      num_hidden_layers
      __magic_name__     =      num_attention_heads
      __magic_name__     =      max_position_embeddings
      __magic_name__     =      layer_norm_eps
      __magic_name__     =      hidden_act
      __magic_name__     =      initializer_range
      __magic_name__     =      attention_probs_dropout_prob
      __magic_name__     =      is_decoder
      __magic_name__     =      use_cache







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_ ,						**UpperCamelCase_       ):
      cls._set_token_in_kwargs(UpperCamelCase_       )

      __magic_name__   ,						__magic_name__     =      cls.get_config_dict(UpperCamelCase_ ,						**UpperCamelCase_       )

      # get the text config dict if we are loading from BlipConfig
      if config_dict.get('''model_type'''       ) == "blip":
       __magic_name__     =      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        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       '''blip_vision_model'''







     def __init__(      self ,						UpperCamelCase_=768 ,						UpperCamelCase_=3072 ,						UpperCamelCase_=512 ,						UpperCamelCase_=12 ,						UpperCamelCase_=12 ,						UpperCamelCase_=384 ,						UpperCamelCase_=16 ,						UpperCamelCase_="gelu" ,						UpperCamelCase_=1E-5 ,						UpperCamelCase_=0.0 ,						UpperCamelCase_=1E-1_0 ,						**UpperCamelCase_ ,						):
      super().__init__(**UpperCamelCase_       )

      __magic_name__     =      hidden_size
      __magic_name__     =      intermediate_size
      __magic_name__     =      projection_dim
      __magic_name__     =      num_hidden_layers
      __magic_name__     =      num_attention_heads
      __magic_name__     =      patch_size
      __magic_name__     =      image_size
      __magic_name__     =      initializer_range
      __magic_name__     =      attention_dropout
      __magic_name__     =      layer_norm_eps
      __magic_name__     =      hidden_act







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_ ,						**UpperCamelCase_       ):
      cls._set_token_in_kwargs(UpperCamelCase_       )

      __magic_name__   ,						__magic_name__     =      cls.get_config_dict(UpperCamelCase_ ,						**UpperCamelCase_       )

      # get the vision config dict if we are loading from BlipConfig
      if config_dict.get('''model_type'''       ) == "blip":
       __magic_name__     =      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        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       '''blip'''
     _lowerCamelCase     =       True







     def __init__(      self ,						UpperCamelCase_=None ,						UpperCamelCase_=None ,						UpperCamelCase_=512 ,						UpperCamelCase_=2.6_5_9_2 ,						UpperCamelCase_=256 ,						**UpperCamelCase_ ,						):
      super().__init__(**UpperCamelCase_       )

      if text_config is None:
       __magic_name__     =      {}
       logger.info('''`text_config` is `None`. Initializing the `BlipTextConfig` with default values.'''       )

      if vision_config is None:
       __magic_name__     =      {}
       logger.info('''`vision_config` is `None`. Initializing the `BlipVisionConfig` with default values.'''       )

      __magic_name__     =      BlipTextConfig(**UpperCamelCase_       )
      __magic_name__     =      BlipVisionConfig(**UpperCamelCase_       )

      __magic_name__     =      self.vision_config.hidden_size

      __magic_name__     =      projection_dim
      __magic_name__     =      logit_scale_init_value
      __magic_name__     =      1.0
      __magic_name__     =      0.0_2
      __magic_name__     =      image_text_hidden_size







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_ ,						UpperCamelCase_ ,						**UpperCamelCase_       ):
      return cls(text_config=text_config.to_dict() ,						vision_config=vision_config.to_dict() ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      copy.deepcopy(self.__dict__       )
      __magic_name__     =      self.text_config.to_dict()
      __magic_name__     =      self.vision_config.to_dict()
      __magic_name__     =      self.__class__.model_type
      return output




"""simple docstring"""






import pytest

import datasets


# Import fixture modules as plugins
__lowerCamelCase										=		["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      str:
 # Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
 for item in items:
  if any(marker in item.keywords for marker in ['''integration''', '''unit''']						):
   continue
  item.add_marker(pytest.mark.unit						)





def 	lowercase      (   __UpperCamelCase						) ->      Union[str, Any]:
 config.addinivalue_line('''markers'''      ,   '''torchaudio_latest: mark test to run with torchaudio>=0.12'''						)





@pytest.fixture(autouse=__UpperCamelCase						)
def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      Dict:
 # test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
 __magic_name__     =      tmp_path_factory.getbasetemp() / '''cache'''
 __magic_name__     =      test_hf_cache_home / '''datasets'''
 __magic_name__     =      test_hf_cache_home / '''metrics'''
 __magic_name__     =      test_hf_cache_home / '''modules'''
 monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''      ,   str(__UpperCamelCase						)						)
 monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''      ,   str(__UpperCamelCase						)						)
 monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''      ,   str(__UpperCamelCase						)						)
 __magic_name__     =      test_hf_datasets_cache / '''downloads'''
 monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''      ,   str(__UpperCamelCase						)						)
 __magic_name__     =      test_hf_datasets_cache / '''downloads''' / '''extracted'''
 monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''      ,   str(__UpperCamelCase						)						)





@pytest.fixture(autouse=__UpperCamelCase      ,   scope='''session'''						)
def 	lowercase      (   ) ->      Any:
 datasets.disable_progress_bar()





@pytest.fixture(autouse=__UpperCamelCase						)
def 	lowercase      (   __UpperCamelCase						) ->      str:
 # don't take tests into account when counting downloads
 monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''      ,   __UpperCamelCase						)





@pytest.fixture
def 	lowercase      (   __UpperCamelCase						) ->      int:
 # Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
 # To be removed once SQLAlchemy 2.0 supported
 monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''      ,   __UpperCamelCase						)

