code: def keras_model_1d(request):
      model_type = request.param["model_type"]
      keepdims = request.param["keepdims"]
      model = Sequential()
      if model_type == "avg":
          model.add(
              GlobalAveragePooling1D(
                  input_shape=(in_shape, in_filt), keepdims=keepdims
              )
          )
      elif model_type == "max":
          model.add(
              GlobalMaxPooling1D(
                  input_shape=(in_shape, in_filt), keepdims=keepdims
              )
          )
      model.compile()
      return model, model_type, keepdims
  
file_path: hls4ml/test/pytest/test_globalpooling.py
imports: from pathlib import Path
  import numpy
  import pytest
  from tensorflow.keras.layers import GlobalAveragePooling1D, GlobalAveragePooling2D, GlobalMaxPooling1D, GlobalMaxPooling2D
  from tensorflow.keras.models import Sequential
  import hls4ml
label_desc: Use image node_id 2 for calling a global function with example usage: keras_model_1d(request) and returns: model,  model_type,  keepdims