def test_part_c():
data = np.loadtxt('data/data.asc').T.reshape(1, 24, -1)
cnn = cnn_solution.CNN_C()
weights = np.load('weights/mlp_weights_part_c.npy')
cnn.init_weights(weights)
expected_result = np.load('autograde/res_c.npy')
result = cnn(data)
try:
assert(type(result)==type(expected_result))
assert(result.shape==expected_result.shape)
assert(np.allclose(result,expected_result))
return True
except Exception as e:
traceback.print_exc()
return False
def test_part_c():
data = np.loadtxt('data/data.asc').T.reshape(1, 24, -1)
cnn = cnn_solution.CNN_C()
weights = np.load('weights/mlp_weights_part_c.npy', allow_pickle=True)
cnn.init_weights(weights)
expected_result = np.load('autograde/res_c.npy')
result = cnn(data)
try:
assert (type(result) == type(expected_result))
assert (
result.shape == expected_result.shape
), "result: {}, expected: {} \n*********expected_Result************\n{}".format(
result.shape, expected_result.shape, expected_result)
assert (
np.allclose(result, expected_result)
), "\n***********result*************\n{}, \n*********expected_Result************\n{}".format(
result, expected_result)
return True
except Exception as e:
traceback.print_exc()
return False