code: def test_keras_fit():
      model = tf.keras.Sequential([tf.keras.layers.Dense(1)])
      model.compile(loss="mse", metrics=[RSquare()])
      data = tf.data.Dataset.from_tensor_slices(
          (
              tf.random.normal(shape=(100, 1)),
              tf.random.normal(shape=(100, 1)),
          )
      )
      data = data.batch(10)
      model.fit(x=data, validation_data=data)
  
imports: import numpy
  import pytest
  import tensorflow
  from sklearn.metrics import r2_score
  from tensorflow_addons.metrics import RSquare
  from tensorflow_addons.metrics.r_square import _VALID_MULTIOUTPUT
label_desc: Use image node_id 14 for calling a global function with example usage: test_keras_fit() without return types