[Bugfix][Frontend][Keras] Add a check to reject the invalid input shape

python/tvm/relay/frontend/keras.py

@@ -1429,6 +1429,12 @@ def _check_model_is_tf_keras():
     def _convert_input_layer(keras_layer):
         input_name = keras_layer.name
         input_shape = shape[input_name] if shape is not None and input_name in shape else None
+        if len(input_shape) > 1 and any(dim <= 0 for dim in input_shape[1:]):
+            msg = (
+               "Expected input's non-batch dimensions to have positive length, "
+                f"but the input has a shape of {input_shape}"
+            )
+            raise RuntimeError(msg)
         etab.set_expr(input_name, new_var(input_name, shape=input_shape))
 
     def _convert_layer(keras_layer, etab, scope=""):

tests/python/frontend/keras/test_forward.py

@@ -297,6 +297,12 @@ def test_forward_pool(self, keras_mod):
         y = keras_mod.layers.AveragePooling2D((3, 3), strides=(1, 1), padding="same")(data)
         keras_model = keras_mod.models.Model(data, y)
         verify_keras_frontend(keras_model)
+        # reject the invalid input shape
+        data = keras_mod.layers.Input(shape=(0, 3, 6, 4))
+        x = keras_mod.layers.GlobalAveragePooling3D()(data)
+        keras_model = keras_mod.models.Model(data, x)
+        with pytest.raises(RuntimeError):
+            verify_model(keras_model)
 
     def test_forward_conv1d(self, keras_mod):
         """test_forward_conv1d"""