code: def predict(self, X):
      # pylint: disable=no-member
  
      X = check_array(X, accept_sparse=True)
      check_is_fitted(self, "is_fitted_")
  
      X = torch.tensor(X, dtype=torch.float32).to(self.device)
      predictions = np.empty(len(X), dtype=int)
      for i, rows in enumerate(X):
          rows = Variable(rows.view(-1, self.input_size))
          outputs = self.network(rows)
  
          _, predicted = torch.max(outputs.data, 1)
          predictions[i] = int(predicted)
      return predictions.reshape(-1, 1)
  
imports: from abc import abstractmethod
  import numpy
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.validation import check_X_y, assert_all_finite, check_array, check_is_fitted
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 4 for calling the PytorchClassifier obj's underlying member method code with example usage: obj.predict(X) and returns: predictions