def test_elu_operator_with_scalar_and_array(): runtime = get_runtime() data_value = np.array([[-5, 1], [-2, 3]], dtype=np.float32) alpha_value = np.float32(3) model = ng.elu(data_value, alpha_value) computation = runtime.computation(model) result = computation() expected = np.array([[-2.9797862, 1.], [-2.5939941, 3.]], dtype=np.float32) assert np.allclose(result, expected)
def test_elu_operator_with_scalar(): runtime = get_runtime() data_value = np.array([[-5, 1], [-2, 3]], dtype=np.float32) alpha_value = np.float32(3) data_shape = [2, 2] parameter_data = ng.parameter(data_shape, name='Data', dtype=np.float32) model = ng.elu(parameter_data, alpha_value) computation = runtime.computation(model, parameter_data) result = computation(data_value) expected = np.array([[-2.9797862, 1.], [-2.5939941, 3.]], dtype=np.float32) assert np.allclose(result, expected)
def test_elu_operator_with_parameters(): runtime = get_runtime() data_shape = [2, 2] alpha_shape = [2] parameter_data = ng.parameter(data_shape, name='Data', dtype=np.float32) parameter_alpha = ng.parameter(alpha_shape, name='Alpha', dtype=np.float32) model = ng.elu(parameter_data, parameter_alpha) computation = runtime.computation(model, parameter_data, parameter_alpha) value_data = np.array([[-5, 1], [-2, 3]], dtype=np.float32) value_alpha = np.array([3, 3], dtype=np.float32) result = computation(value_data, value_alpha) expected = np.array([[-2.9797862, 1.], [-2.5939941, 3.]], dtype=np.float32) assert np.allclose(result, expected)