def test_Softmax(): def init(input_shape, output_shape): return Softmax() generic_test_module_derivative_amount(init, mean_squared_loss, shape_generator=same_generator)
def test_MatrixMultModel(): def init(input_shape, output_shape): return MatrixMult([input_shape[1], output_shape[1]]) generic_test_module_optimize(init, mean_squared_loss) generic_test_module_derivative_amount(init, mean_squared_loss, shape_generator=alt_generator)
def generic_test_Convolution_derivative_amount(conv_cls): def shape_generator(): return ([[1, 12, 12, 2], [0, 0, 0, 0]], [[1, 10, 10, 3], [0, 0, 0, 0]]) def init_fnc(input_shape, output_shape): return conv_cls(input_shape[1:], 3, output_shape[-1]) generic_test_module_derivative_amount(init_fnc, mean_squared_loss, shape_generator)
def generic_test_Pool_derivative_amount(pool): def shape_generator(): return ([[1, 12, 12, 2], [0, 0, 0, 0]], [[1, 6, 6, 2], [0, 0, 0, 0]]) def init_fnc(input_shape, output_shape): return pool(2) generic_test_module_derivative_amount(init_fnc, mean_squared_loss, shape_generator, ratio_skips=0.05)