code: def test_depthwise2d(backend, io_type):
      """
      Test proper handling of DepthwiseConv2D
      """
      X = np.random.rand(10, 32, 32, 3)
      X = (
          np.round(X * 2**10) * 2**-10
      )  # make it an exact ap_fixed<16,6>
      model = tf.keras.models.Sequential()
      model.add(
          DepthwiseConv2D(kernel_size=(3, 3), input_shape=(32, 32, 3))
      )
      model.compile()
  
      config = hls4ml.utils.config_from_keras_model(
          model, granularity="name", default_precision="fixed<32,12>"
      )
      output_dir = str(
          test_root_path
          / f"hls4mlprj_keras_api_depthwiseconv2d_{backend}_{io_type}"
      )
      hls_model = hls4ml.converters.convert_from_keras_model(
          model,
          hls_config=config,
          output_dir=output_dir,
          backend=backend,
          io_type=io_type,
      )
      hls_model.compile()
  
      y_qkeras = model.predict(X)
      y_hls4ml = hls_model.predict(X)
  
      np.testing.assert_allclose(
          y_qkeras,
          y_hls4ml.reshape(y_qkeras.shape),
          rtol=1e-2,
          atol=0.01,
      )
  
file_path: hls4ml/test/pytest/test_keras_api.py
imports: import math
  from pathlib import Path
  import numpy
  import pytest
  import tensorflow
  from tensorflow.keras.layers import ELU, Activation, AveragePooling1D, AveragePooling2D, Conv1D, Conv2D, Dense, DepthwiseConv1D, DepthwiseConv2D, LeakyReLU, MaxPooling1D, MaxPooling2D, PReLU
  import hls4ml
label_desc: Use image node_id 5 for calling a global function with example usage: test_depthwise2d(backend, io_type) without return types