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


_UpperCAmelCase            =		logging.get_logger(__name__)

_UpperCAmelCase            =		{
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}





class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				lowerCamelCase_    = '''mgp-str'''
				def __init__(						self		,     lowercase=[3_2, 1_2_8]		,     lowercase=4		,     lowercase=3		,     lowercase=2_7		,     lowercase=3_8		,     lowercase=5_0_2_5_7		,     lowercase=3_0_5_2_2		,     lowercase=7_6_8		,     lowercase=1_2		,     lowercase=1_2		,     lowercase=4.0		,     lowercase=True		,     lowercase=False		,     lowercase=1E-5		,     lowercase=0.0		,     lowercase=0.0		,     lowercase=0.0		,     lowercase=False		,     lowercase=0.02		,     **lowercase		,     ):



						"""simple docstring"""





						super().__init__(**lowercase )

						A_		:    List[str]         =				image_size
						A_		:    str         =				patch_size
						A_		:    Optional[Any]         =				num_channels
						A_		:    List[Any]         =				max_token_length
						A_		:    str         =				num_character_labels
						A_		:    Optional[int]         =				num_bpe_labels
						A_		:    Optional[int]         =				num_wordpiece_labels
						A_		:    Any         =				hidden_size
						A_		:    Optional[int]         =				num_hidden_layers
						A_		:    List[Any]         =				num_attention_heads
						A_		:    Union[str, Any]         =				mlp_ratio
						A_		:    Optional[int]         =				distilled
						A_		:    Tuple         =				layer_norm_eps
						A_		:    int         =				drop_rate
						A_		:    Dict         =				qkv_bias
						A_		:    str         =				attn_drop_rate
						A_		:    int         =				drop_path_rate
						A_		:    Optional[Any]         =				output_aa_attentions
						A_		:    Optional[int]         =				initializer_range







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






