code: def deeplearning_no_hidden():
      iris_hex = h2o.import_file(
          path=pyunit_utils.locate("smalldata/iris/iris.csv")
      )
  
      hh = H2ODeepLearningEstimator(
          hidden=[], loss="CrossEntropy", export_weights_and_biases=True
      )
      hh.train(x=list(range(4)), y=4, training_frame=iris_hex)
      hh.show()
      weights1 = hh.weights(0)
      assert weights1.shape[0] == 3
      assert weights1.shape[1] == 4
  
imports: from builtins import range
  import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.deeplearning import H2ODeepLearningEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: deeplearning_no_hidden() without return types