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)