code: def eva02_tiny_patch14_336(pretrained=False, **kwargs) -> Eva:
      model_args = dict(
          img_size=336,
          patch_size=14,
          embed_dim=192,
          depth=12,
          num_heads=3,
          mlp_ratio=4 * 2 / 3,
          swiglu_mlp=True,
          use_rot_pos_emb=True,
          ref_feat_shape=(16, 16),  # 224/14
      )
      model = _create_eva(
          "eva02_tiny_patch14_336",
          pretrained=pretrained,
          **dict(model_args, **kwargs),
      )
      return model
  
imports: import math
  from typing import Callable, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, OPENAI_CLIP_MEAN, OPENAI_CLIP_STD
  from timm.layers import PatchEmbed, Mlp, GluMlp, SwiGLU, LayerNorm, DropPath, PatchDropout, RotaryEmbeddingCat, apply_rot_embed_cat, apply_keep_indices_nlc, trunc_normal_, resample_patch_embed, resample_abs_pos_embed, to_2tuple, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._registry import generate_default_cfgs, register_model
label_desc: Use image node_id 11 for calling a global function with example usage: eva02_tiny_patch14_336(pretrained) and returns: model