code: def _check_input(self, x, y):
      input_feature_num = x.shape[-1]
      input_output_dim = y.shape[-1]
      if input_feature_num is None:
          raise ValueError("input x is None!")
      if input_output_dim is None:
          raise ValueError("input y is None!")
  
      if (
          self.feature_num is not None
          and self.feature_num != input_feature_num
      ):
          raise ValueError(
              "input x has different feature number (the shape of last dimension) "
              "{} with the fitted model, which is {}.".format(
                  input_feature_num, self.feature_num
              )
          )
      if (
          self.output_dim is not None
          and self.output_dim != input_output_dim
      ):
          raise ValueError(
              "input y has different prediction size (the shape of last dimension) "
              "of {} with the fitted model, which is {}.".format(
                  input_output_dim, self.output_dim
              )
          )
      return input_feature_num, input_output_dim
  
imports: import pickle
  import numpy
  import time
  from tensorflow.keras.models import Model
  from tensorflow.keras.layers import *
  from tensorflow.keras.initializers import TruncatedNormal, Constant
  import tensorflow.keras.backend
  import tensorflow
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.model.abstract import BaseModel
label_desc: Use image node_id 9 for calling the MTNetKeras obj's underlying member method code with example usage: obj._check_input(x, y) and returns: input_feature_num,  input_output_dim