code: def gat_v2_model(c: Configs):
      """
      Create GATv2 model
      """
      return GATv2(
          c.in_features,
          c.n_hidden,
          c.n_classes,
          c.n_heads,
          c.dropout,
          c.share_weights,
      ).to(c.device)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/graphs/gatv2/experiment.py
imports: import torch
  from torch import nn
  from labml import experiment
  from labml.configs import option
  from labml_helpers.module import Module
  from labml_nn.graphs.gat.experiment import Configs
  from labml_nn.graphs.gatv2 import GraphAttentionV2Layer
label_desc: Use image node_id 1 for calling a global function with example usage: gat_v2_model(c) and returns: GATv2