code: def test_pointwiseconv2d(
      chans, padds, strides, backend, io_type, strategy
  ):
      model = tf.keras.models.Sequential()
      input_shape = (28, 28, 3)
      model.add(
          Conv2D(
              filters=32,
              kernel_size=(1, 1),
              strides=strides,
              padding=padds,
              input_shape=input_shape,
              kernel_initializer="normal",
              use_bias=False,
              data_format=chans,
          )
      )
  
      model.compile(optimizer="adam", loss="mse")
      X_input = np.random.rand(100, *input_shape)
      keras_prediction = model.predict(X_input)
  
      default_precision = "fixed<32, 9>"
  
      config = hls4ml.utils.config_from_keras_model(
          model, default_precision=default_precision
      )
      config["Model"]["Strategy"] = strategy
      stride_cfg = (
          str(strides)
          .replace(", ", "_")
          .replace("(", "")
          .replace(")", "")
      )
      output_dir = str(
          test_root_path
          / "hls4mlprj_pointwise2d_{}_strides_{}_{}_padding_{}_{}_{}".format(
              chans, stride_cfg, padds, backend, io_type, strategy
          )
      )
  
      hls_model = hls4ml.converters.convert_from_keras_model(
          model,
          hls_config=config,
          output_dir=output_dir,
          io_type=io_type,
          backend=backend,
      )
      hls_model.compile()
      hls_prediction = hls_model.predict(X_input).reshape(
          keras_prediction.shape
      )
  
      if not (backend == "Quartus" and io_type == "io_stream"):
          # Quartus io_stream does not currently have a special pointwise implementation
          assert (
              "Pointwise"
              in list(hls_model.graph.values())[1].class_name
          )
      np.testing.assert_allclose(
          hls_prediction, keras_prediction, rtol=0, atol=0.001
      )
  
file_path: hls4ml/test/pytest/test_pointwiseconv.py
imports: from pathlib import Path
  import numpy
  import pytest
  import tensorflow
  from tensorflow.keras.layers import Conv1D, Conv2D
  import hls4ml
label_desc: Use image node_id 2 for calling a global function with example usage: test_pointwiseconv2d(chans, padds, strides, backend, io_type, strategy) without return types