
import copy
import os
from typing import Union

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


_UpperCAmelCase :			List[str]              =	logging.get_logger(__name__)

_UpperCAmelCase :			str              =	{
    "microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",
}


class     lowercase (		_SCREAMING_SNAKE_CASE       ):
		__lowercase	:	Any     					=    "git_vision_model"



		def __init__(			self    ,  A_=768    ,  A_=3_072    ,  A_=12    ,  A_=12    ,  A_=3    ,  A_=224    ,  A_=16    ,  A_="quick_gelu"    ,  A_=1e-5    ,  A_=0.0    ,  A_=0.02    ,  **A_    ,  )  -> Union[str, Any]:
				"""simple docstring"""
				super().__init__(**A_	)

				UpperCamelCase          =					hidden_size
				UpperCamelCase          =					intermediate_size
				UpperCamelCase          =					num_hidden_layers
				UpperCamelCase          =					num_attention_heads
				UpperCamelCase          =					num_channels
				UpperCamelCase          =					patch_size
				UpperCamelCase          =					image_size
				UpperCamelCase          =					initializer_range
				UpperCamelCase          =					attention_dropout
				UpperCamelCase          =					layer_norm_eps
				UpperCamelCase          =					hidden_act



		@classmethod
		def __UpperCamelCase			(			cls    ,  A_    ,  **A_	)  -> "PretrainedConfig":
				"""simple docstring"""
				cls._set_token_in_kwargs(A_	)

				UpperCamelCase     ,  UpperCamelCase          =					cls.get_config_dict(A_    ,  **A_	)

				# get the vision config dict if we are loading from GITConfig
				if config_dict.get('model_type'	) == "git":
						UpperCamelCase          =					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(A_    ,  **A_	)






class     lowercase (		_SCREAMING_SNAKE_CASE       ):
		__lowercase	:	Optional[Any]     					=    "git"



		def __init__(			self    ,  A_=None    ,  A_=30_522    ,  A_=768    ,  A_=6    ,  A_=12    ,  A_=3_072    ,  A_="gelu"    ,  A_=0.1    ,  A_=0.1    ,  A_=1_024    ,  A_=0.02    ,  A_=1e-12    ,  A_=0    ,  A_="absolute"    ,  A_=True    ,  A_=False    ,  A_=101    ,  A_=102    ,  A_=None    ,  **A_    ,  )  -> Optional[int]:
				"""simple docstring"""
				super().__init__(bos_token_id=A_    ,  eos_token_id=A_    ,  pad_token_id=A_    ,  **A_	)

				if vision_config is None:
						UpperCamelCase          =					{}
						logger.info('vision_config is None. initializing the GitVisionConfig with default values.'	)

				UpperCamelCase          =					GitVisionConfig(**A_	)
				UpperCamelCase          =					vocab_size
				UpperCamelCase          =					hidden_size
				UpperCamelCase          =					num_hidden_layers
				UpperCamelCase          =					num_attention_heads
				UpperCamelCase          =					hidden_act
				UpperCamelCase          =					intermediate_size
				UpperCamelCase          =					hidden_dropout_prob
				UpperCamelCase          =					attention_probs_dropout_prob
				UpperCamelCase          =					max_position_embeddings
				UpperCamelCase          =					initializer_range
				UpperCamelCase          =					layer_norm_eps
				UpperCamelCase          =					position_embedding_type
				UpperCamelCase          =					use_cache
				UpperCamelCase          =					tie_word_embeddings
				UpperCamelCase          =					num_image_with_embedding

				UpperCamelCase          =					bos_token_id
				UpperCamelCase          =					eos_token_id



		def __UpperCamelCase			(			self	)  -> List[str]:
				"""simple docstring"""
				UpperCamelCase          =					copy.deepcopy(self.__dict__	)
				UpperCamelCase          =					self.vision_config.to_dict()
				UpperCamelCase          =					self.__class__.model_type
				return output


from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
					if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
					from .pipeline_unclip import UnCLIPPipeline
					from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
					from .text_proj import UnCLIPTextProjModel
