docstr: Calls predict on fitted DragonNet.
  
  Args:
      X (np.matrix or np.array or pd.Dataframe): a feature matrix
  Returns:
      (np.ndarray): Predictions of treatment effects.
docstr_tok: ["Calls","predict","on","fitted","DragonNet",".","Args",":","X","(","np.matrix","or","np.array","or","pd.Dataframe",")",":","a","feature","matrix","Returns",":","(","np.ndarray",")",":","Predictions","of","treatment","effects","."]
code: def predict(self, X, treatment=None, y=None, p=None):
      """
      Calls predict on fitted DragonNet.
  
      Args:
          X (np.matrix or np.array or pd.Dataframe): a feature matrix
      Returns:
          (np.ndarray): Predictions of treatment effects.
      """
      return (
          self.cevae.ite(
              torch.tensor(X, dtype=torch.float),
              num_samples=self.num_samples,
              batch_size=self.batch_size,
          )
          .cpu()
          .numpy()
      )
  
file_path: causalml/causalml/inference/nn/cevae.py
imports: import logging
  import torch
  from pyro.contrib.cevae import CEVAE
  from causalml.inference.meta.utils import convert_pd_to_np
label_desc: Use image node_id 3 for calling the CEVAE obj's underlying member method code with example usage: obj.predict(X, treatment, y, p) and returns: self