def METHOD_NAME(layer, **kwargs):
    X = np.random.normal(size=(batch_size, N, F))
    if "target_shape" in kwargs:
        target_output_shape = kwargs.pop("target_shape")
    else:
        target_output_shape = (batch_size, kwargs.get("channels", F))
    X_in = Input(shape=(N, F))
    layer_instance = layer(**kwargs)
    output = layer_instance(X_in)
    model = Model(X_in, output)
    output = model(X)
    assert output.shape == target_output_shape
    assert output.shape == layer_instance.compute_output_shape(X.shape)
    _check_output_and_model_output_shapes(output.shape, model.output_shape)