def test_functions():
value = random.randint(-100, 100)
value2 = random.randint(1, 100)
assert round(c.sin(value)) == round(math.sin(
value)), "Sin function is not working, you studied this in 10.."
assert round(c.cos(value)) == round(math.cos(
value)), "Cos function is not working, you studied this in 10.."
assert round(c.tan(value)) == round(math.tan(
value)), "Tan function is not working, you studied this in 10.."
assert round(c.tanh(value)) == round(math.tanh(
value)), "Tanh function is not working, you studied this in 10.."
assert round(c.sigmoid(value)) == round(
(1 / (1 + math.exp(-value))
)), "Sigmoid function is not working, this is the basic of DNN.."
assert round(c.relu(value)) == round(max(
0, value)), "Relu function is not working, this is the basic of DNN,,"
assert round(c.log(value2)) == round(math.log(
value2)), "Log function is not working, you studied this in 10.."
assert round(c.e(value)) == round(math.exp(
value)), "Exp function is not working, you studied this in 10.."
assert [
0.0003282279149649954, 0.0024252944769113903, 0.01792063694632493,
0.0008922159768423478, 0.9784336246849563
] == c.softmax([1, 3, 5, 2,
9]), "Softmax not working bro.. how will you make NN then"
def test_softmax():
"""
Test the method softmax in the calculator package
:return: None
"""
output = calculator.softmax([1, 2, 3])
assert output == [0.033120396946264216, 0.06624079389252843, 0.09936119083879263]
output = derivatives.derivative_softmax([1, 2], [1, 1])
assert output == [-1, 0]
def test_all_function_check():
import calculator
assert calculator.sin(math.pi / 2) == 1
assert calculator.cos(math.pi) == -1
assert calculator.tan(0) == 0
assert calculator.tanh(0) == 0
assert calculator.softmax([1,
2]) == [0.2689414213699951, 0.7310585786300049]
assert calculator.e(0) == 1
assert calculator.log(10, base=10) == 1
assert calculator.relu(10) == 10
assert calculator.relu(-10) == 0
assert calculator.sigmoid(0) == 0.5
def test():
abs_tol = 0.001
rel_tol = 0.001
test_value = 25
# ================= testing sin =====================
assert math.isclose(
calculator.sin(test_value), -0.132, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.sin(test_value)}',
f'expected : {-0.132}')
assert math.isclose(
derivatives.sin(test_value), 0.991, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.sin(test_value)}',
f'expected : {0.991}')
# ================= testing cosine =====================
assert math.isclose(
calculator.cos(test_value), 0.991, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.cos(test_value)}',
f'expected : {0.991}')
assert math.isclose(
derivatives.cos(test_value), 0.132, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.cos(test_value)}',
f'expected : {0.132}')
# ================= testing exponential =====================
assert math.isclose(
calculator.exp(test_value),
72004899337,
rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.exp(test_value)}',
f'expected : {72004899337}')
assert math.isclose(
derivatives.exp(test_value),
72004899337,
rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.exp(test_value)}',
f'expected : {72004899337}')
# ================= testing log =====================
assert math.isclose(
calculator.log(test_value), 3.218, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.log(test_value)}',
f'expected : {3.218}')
assert math.isclose(
derivatives.log(test_value), 0.04, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.log(test_value)}',
f'expected : {0.04}')
# ================= testing relu =====================
assert math.isclose(
calculator.relu(test_value), 25, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.relu(test_value)}',
f'expected : {25}')
assert math.isclose(
derivatives.relu(test_value), 1, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.relu(test_value)}',
f'expected : {1}')
# ================= testing sigmoid =====================
assert math.isclose(
calculator.sigmoid(test_value),
0.999,
rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.sigmoid(test_value)}',
f'expected : {0.999}')
assert math.isclose(
derivatives.sigmoid(test_value),
1.388794386457827062508E-11,
rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.sigmoid(test_value)}',
f'expected : {1.388794386457827062508E-11}')
# ================= testing Softmax =====================
assert math.isclose(
calculator.softmax(test_value), 1, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.softmax(test_value)}',
f'expected : {1}')
# assert math.isclose(derivatives.softmax(test_value), 0.04 ,
# rel_tol=abs_tol,
# abs_tol=abs_tol),(f'actual : {derivatives.softmax(test_value)}',
# f'expected : {0.04}' )
# ================= testing tan =====================
assert math.isclose(
calculator.tan(test_value), -0.133, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {calculator.tan(test_value)}',
f'expected : {-0.133}')
assert math.isclose(
derivatives.tan(test_value), 2.017, rel_tol=abs_tol,
abs_tol=abs_tol), (f'actual : {derivatives.tan(test_value)}',
f'expected : {2.017}')
def test_softmax_import():
softmax_output = calculator.softmax([1, 5])
assert np.allclose(softmax_output, np.array(
[0.01798621,
0.98201379])), "softmax function in calculor has wrong implementation"
def test_function_dsoftmax():
assert derivatives.dsoftmax(calculator.softmax([num,num])).all() == np.array([[ 0.25, -0.25], [-0.25, 0.25]]).all(), 'dSoftmax implemenation failed'
def test_function_softmax():
assert calculator.softmax([num,num]) == [0.5, 0.5], 'Softmax implemenation failed'
def test_softmax_min_args():
with pytest.raises(ValueError):
calc.softmax(1)
def test_softmax():
out = (0.09003057317038046, 0.24472847105479767, 0.6652409557748219)
exp_out = calc.softmax(1, 2, 3)
for i, j in zip(out, exp_out):
assert math.isclose(i, j), 'Check your softmax function'
def test_type_error():
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.sin("60")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.cos("-45")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.tan("4.5")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.tanh("50")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.relu("1.3")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.sigmoid("2.4")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.euler("4")
with pytest.raises(TypeError, match=r".*invalid type*"):
calculator.softmax([10, "2", "3"])
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.log("5", 10)
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
calculator.log(3, "10")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_sin("45")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_cos("4.5")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_tan("45")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_tanh([1, 3])
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_euler("10")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_sigmoid("3")
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_relu("-5")
with pytest.raises(TypeError, match=r".*invalid type*"):
derivatives.d_softmax([20, "3", 5])
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_log("5", 20)
with pytest.raises(TypeError, match=r".*Input value of invalid type*"):
derivatives.d_log(5, "20")
def test_softmax_len():
assert calculator.softmax(mmatrix_single) == 'ERROR!!, more than one value is required'
def test_softmax():
print(calculator.softmax(mmatrix))
def test_sigmoid():
assert [0.8807970779778823,
0.11920292202211755] == list(calculator.softmax([5, 3]))
def test_softmax():
assert calculator.softmax(5) == 1.0
def test_softmax():
# assert (calc.softmax([4,5,6,7]) == softmax([4,5,6,7])).any()
assert np.allclose(calc.softmax([4, 5, 6, 7]), softmax([4, 5, 6, 7]))