config.py

git clone https://github.com/opendilab/InterFuser.git
pip install timm
import sys
sys.path.append('/content/InterFuser')
import math
import copy
import sys
from collections import OrderedDict
from functools import partial
from typing import Optional, List
from huggingface_hub import HfApi

import numpy as np
import torch
from torch import nn, Tensor
import torch.nn.functional as F
from InterFuser.modeling_interfuser import InterfuserConfig, InterfuserForHuggingFace
from huggingface_hub import notebook_login
# --- هذه هي الأسطر المهمة التي يجب التأكد من وجودها ---
from InterFuser.interfuser.timm.models.layers import StdConv2dSame, StdConv2d, to_2tuple
from InterFuser.interfuser.timm.models.registry import register_model
from InterFuser.interfuser.timm.models.resnet import resnet26d, resnet50d, resnet18d, resnet26, resnet50, resnet101d
# --------------------------------------------------------
from transformers import AutoConfig, AutoModel
import os

class InterfuserConfig(PretrainedConfig):

    model_type = "interfuser"
    def __init__(
        self,
        embed_dim=256,
        enc_depth=6,
        dec_depth=6,
        num_heads=8,
        dim_feedforward=2048,
        rgb_backbone_name="r50",
        lidar_backbone_name="r18",
        waypoints_pred_head="gru",
        use_different_backbone=True,
        **kwargs
    ):
        super().__init__(**kwargs)
        self.embed_dim = embed_dim
        self.enc_depth = enc_depth
        self.dec_depth = dec_depth
        self.num_heads = num_heads
        self.dim_feedforward = dim_feedforward
        self.rgb_backbone_name = rgb_backbone_name
        self.lidar_backbone_name = lidar_backbone_name
        self.waypoints_pred_head = waypoints_pred_head
        self.use_different_backbone = use_different_backbone
        # Add the architectures key for auto-mapping
        self.architectures = ["InterfuserForHuggingFace"]