code: def toy_model_sign(**kwargs):
      img = tf.keras.layers.Input(shape=(224, 224, 3))
      x = lq.layers.QuantConv2D(
          256,
          kernel_size=3,
          strides=1,
          padding="same",
          pad_values=1,
          input_quantizer="ste_sign",
          kernel_quantizer="ste_sign",
          kernel_constraint="weight_clip",
      )(img)
      x = lq.quantizers.SteSign()(x)
      return tf.keras.Model(inputs=img, outputs=x)
  
file_path: compute-engine/larq_compute_engine/tests/strip_lcedequantize_test.py
imports: import sys
  import larq
  import pytest
  import tensorflow
  from larq_compute_engine.mlir.python.converter import convert_keras_model
  from larq_compute_engine.mlir.python.util import strip_lcedequantize_ops
label_desc: Use image node_id 1 for calling a global function with example usage: toy_model_sign() and returns: tf