Zjc`SSKJr SSKJr SSKJr \"SS9\"SS\555rS/rg ) )strict)PreTrainedConfig)auto_docstringz&tue-mps/videomt-dinov2-small-ytvis2019) checkpointc\rSrSr%SrSrSr\\S'Sr \\S'Sr \\S 'S r \ \S 'S r \\-\S 'Sr\\S'Sr\\S'Sr\\\-\\\4-\S'Sr\\\-\\\4-\S'Sr\\S'Sr\\S'Sr\\S'S r\\-\S'Sr\\S'S r\\-\S'Sr\\S 'Sr\\S!'S"r\\S#'S$r\\S%'S&r \\S''S&r!\\S('S)r"\\S*'S+r#\\S,'S-r$\\S.'S/r%\\S0'Sr&\\S1'S2r'g3)4 VideomtConfiga layerscale_value (`float`, *optional*, defaults to 1.0): Initial value for the LayerScale parameter. num_upscale_blocks (`int`, *optional*, defaults to 2): Number of upsampling blocks used in the decoder or segmentation head. use_swiglu_ffn (`bool`, *optional*, defaults to `False`): Whether to use the SwiGLU feedforward neural network. num_blocks (`int`, *optional*, defaults to 4): Number of feature blocks or stages in the architecture. no_object_weight (`float`, *optional*, defaults to 0.1): Loss weight for the 'no object' class in panoptic/instance segmentation. class_weight (`float`, *optional*, defaults to 2.0): Loss weight for classification targets. mask_weight (`float`, *optional*, defaults to 5.0): Loss weight for mask prediction. train_num_points (`int`, *optional*, defaults to 12544): Number of points to sample for mask loss computation during training. oversample_ratio (`float`, *optional*, defaults to 3.0): Oversampling ratio used in point sampling for mask training. importance_sample_ratio (`float`, *optional*, defaults to 0.75): Ratio of points to sample based on importance during training. num_queries (`int`, *optional*, defaults to 200): Number of object queries in the Transformer. num_register_tokens (`int`, *optional*, defaults to 4): Number of learnable register tokens added to the transformer input. Example: ```python >>> from transformers import VideomtConfig, VideomtForUniversalSegmentation >>> # Initialize configuration >>> config = VideomtConfig() >>> # Initialize model >>> model = VideomtForUniversalSegmentation(config) >>> # Access config >>> config = model.config ```videomti hidden_sizenum_hidden_layersnum_attention_headsgelu hidden_actghidden_dropout_probg{Gz?initializer_rangegư>layer_norm_epsi image_size patch_sizer num_channels mlp_ratiog?layerscale_valuedrop_path_ratenum_upscale_blocksattention_dropoutFuse_swiglu_ffn num_blocksg?no_object_weightg@ class_weightg@ mask_weight dice_weighti1train_num_pointsg@oversample_ratiog?importance_sample_ratio num_queriesnum_register_tokensN)(__name__ __module__ __qualname____firstlineno____doc__ model_typer int__annotations__rrrstrrfloatrrrlisttuplerrrrrrrr boolr!r"r#r$r%r&r'r(r*r+__static_attributes__r,ڂ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/videomt/configuration_videomt.pyr r sU' RJKs!!J'**#u# NE 47Jd3i%S/1746Jd3i%S/16L#Is!e!"%NECK%%(us{( ND J!e!L%KK!c!!e!%)U)K  r;r N)huggingface_hub.dataclassesrconfiguration_utilsrutilsrr __all__r,r;r<rAsI*/3#CDE!$E!EE!P  r;