Fix model reporting in tensorflow 2.13 does not work properly (#1112)

examples/frameworks/keras/keras_v3.py

@@ -0,0 +1,28 @@
+import numpy as np
+import keras
+from clearml import Task
+
+
+def get_model():
+    # Create a simple model.
+    inputs = keras.Input(shape=(32,))
+    outputs = keras.layers.Dense(1)(inputs)
+    model = keras.Model(inputs, outputs)
+    model.compile(optimizer=keras.optimizers.Adam(), loss="mean_squared_error")
+    return model
+
+Task.init(project_name="examples", task_name="keras_v3")
+
+model = get_model()
+
+test_input = np.random.random((128, 32))
+test_target = np.random.random((128, 1))
+model.fit(test_input, test_target)
+
+model.save("my_model.keras")
+
+reconstructed_model = keras.models.load_model("my_model.keras")
+
+np.testing.assert_allclose(
+    model.predict(test_input), reconstructed_model.predict(test_input)
+)