Update config.py

config.py

@@ -0,0 +1,54 @@
+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"]