class_docstr: Abstract base class for DeepChem models.
class_docstr_tok: ["Abstract","base","class","for","DeepChem","models","."]
docstr: Makes predictions on given batch of new data.
  
  Parameters
  ----------
  X: np.ndarray
      Features
docstr_tok: ["Makes","predictions","on","given","batch","of","new","data",".","Parameters","--","--","--","--","--","X",":","np.ndarray","Features"]
code: def predict_on_batch(self, X: np.typing.ArrayLike):
      """
      Makes predictions on given batch of new data.
  
      Parameters
      ----------
      X: np.ndarray
          Features
      """
      raise NotImplementedError(
          "Each model is responsible for its own predict_on_batch method."
      )
  
imports: import os
  import shutil
  import tempfile
  import logging
  from typing import List, Optional, Sequence
  import numpy
  from deepchem.data import Dataset
  from deepchem.metrics import Metric
  from deepchem.trans import Transformer, undo_transforms
  from deepchem.utils.evaluate import Evaluator
  from deepchem.utils.typing import OneOrMany
label_desc: Use image node_id 4 for calling the Model obj's underlying member method code with example usage: obj.predict_on_batch(X) without return types