class_docstr: This callback allows counting model parameters during training.
  
  Attributes:
      num_parameters: The number of parameters of the model. This attribute should only be
          accessed after training.
class_docstr_tok: ["This","callback","allows","counting","model","parameters","during","training",".","Attributes",":","num_parameters",":","The","number","of","parameters","of","the","model",".","This","attribute","should","only","be","accessed","after","training","."]
code: def on_network_initialization_end(
      self, network: nn.HybridBlock
  ) -> None:
      self.num_parameters = sum(
          np.prod(p.shape) for p in network.collect_params().values()
      )
  
imports: import numpy
  from mxnet.gluon import nn
  from .base import Callback
label_desc: Use image node_id 2 for calling the ParameterCountCallback obj's underlying member method code with example usage: obj.on_network_initialization_end(network) without return types