code: def get_test_model():
      """Model taken from https://docs.larq.dev/larq/tutorials/mnist/#create-the-model."""
  
      # All quantized layers except the first will use the same options
      kwargs = {
          "input_quantizer": "ste_sign",
          "kernel_quantizer": "ste_sign",
          "kernel_constraint": "weight_clip",
      }
  
      model = tf.keras.models.Sequential()
  
      # In the first layer we only quantize the weights and not the input
      model.add(
          lq.layers.QuantConv2D(
              32,
              (3, 3),
              kernel_quantizer="ste_sign",
              kernel_constraint="weight_clip",
              use_bias=False,
              input_shape=(28, 28, 1),
          )
      )
      model.add(tf.keras.layers.MaxPooling2D((2, 2)))
      model.add(tf.keras.layers.BatchNormalization(scale=False))
  
      model.add(
          lq.layers.QuantConv2D(64, (3, 3), use_bias=False, **kwargs)
      )
      model.add(tf.keras.layers.MaxPooling2D((2, 2)))
      model.add(tf.keras.layers.BatchNormalization(scale=False))
  
      model.add(
          lq.layers.QuantConv2D(64, (3, 3), use_bias=False, **kwargs)
      )
      model.add(tf.keras.layers.BatchNormalization(scale=False))
      model.add(tf.keras.layers.Flatten())
  
      model.add(lq.layers.QuantDense(64, use_bias=False, **kwargs))
      model.add(tf.keras.layers.BatchNormalization(scale=False))
      model.add(lq.layers.QuantDense(10, use_bias=False, **kwargs))
      model.add(tf.keras.layers.BatchNormalization(scale=False))
      model.add(tf.keras.layers.Activation("softmax"))
      return model
  
file_path: compute-engine/larq_compute_engine/mlir/python/converter_test.py
imports: import sys
  import unittest
  from unittest import mock
  import tensorflow
  import larq
  from tensorflow.python.eager import context
  from larq_compute_engine.mlir.python.converter import convert_keras_model
  from larq_compute_engine.mlir._tf_tfl_flatbuffer import convert_saved_model_to_tflite_flatbuffer
label_desc: Use image node_id 1 for calling a global function with example usage: get_test_model() and returns: model