code: def build_linear_keras_sequential_model_no_input_layer(
      input_shape, weights
  ):
      return tf.keras.Sequential(
          [
              tf.keras.layers.Dense(
                  weights.shape[-1],
                  use_bias=False,
                  input_shape=input_shape,
                  kernel_initializer=tf.keras.initializers.Constant(
                      weights
                  ),
              ),
          ]
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  from absl.testing import parameterized
  import neural_structured_learning.configs
  from neural_structured_learning.keras import adversarial_regularization
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 2 for calling a global function with example usage: build_linear_keras_sequential_model_no_input_layer(input_shape, weights) and returns: tf