def test_linear_activation_forward(self):
A_prev, W, b = linear_activation_forward_test_case()
A, linear_activation_cache = tc.linear_activation_forward(
A_prev, W, b, activation="sigmoid")
print("With sigmoid: A = " + str(A))
A, linear_activation_cache = tc.linear_activation_forward(
A_prev, W, b, activation="relu")
print("With ReLU: A = " + str(A))
def test_linear_activation_backward(self):
AL, linear_activation_cache = linear_activation_backward_test_case()
dA_prev, dW, db = tc.linear_activation_backward(
AL, linear_activation_cache, activation="sigmoid")
print("sigmoid:")
print("dA_prev = " + str(dA_prev))
print("dW = " + str(dW))
print("db = " + str(db) + "\n")
dA_prev, dW, db = tc.linear_activation_backward(
AL, linear_activation_cache, activation="relu")
print("relu:")
print("dA_prev = " + str(dA_prev))
print("dW = " + str(dW))
print("db = " + str(db))
def test_update_parameters(self):
parameters, grads = update_parameters_test_case()
parameters = tc.update_parameters(parameters, grads, 0.1)
print("W1 = " + str(parameters["W1"]))
print("b1 = " + str(parameters["b1"]))
print("W2 = " + str(parameters["W2"]))
print("b2 = " + str(parameters["b2"]))
print("W3 = " + str(parameters["W3"]))
print("b3 = " + str(parameters["b3"]))
def test_L_model_backward(self):
X_assess, Y_assess, AL, caches = L_model_backward_test_case()
grads = tc.L_model_backward(AL, Y_assess, caches)
print("dW1 = " + str(grads["dW1"]))
print("db1 = " + str(grads["db1"]))
print("dA1 = " + str(grads["dA1"]))
def test_initialize_parameters(self):
parameters = tc.initialize_parameters(2, 2, 1)
print("W1 = " + str(parameters["W1"]))
print("b1 = " + str(parameters["b1"]))
print("W2 = " + str(parameters["W2"]))
print("b2 = " + str(parameters["b2"]))
def test_linear_backward(self):
dZ, linear_cache = linear_backward_test_case()
dA_prev, dW, db = tc.linear_backward(dZ, linear_cache)
print("dA_prev = " + str(dA_prev))
print("dW = " + str(dW))
print("db = " + str(db))
def test_compute_cost(self):
Y, AL = compute_cost_test_case()
print("cost = " + str(tc.compute_cost(AL, Y)))
def test_L_model_forward(self):
X, parameters = L_model_forward_test_case()
AL, caches = tc.L_model_forward(X, parameters)
print("AL = " + str(AL))
print("Length of caches list = " + str(len(caches)))
def test_linear_forward(self):
A, W, b = linear_forward_test_case()
Z, linear_cache = tc.linear_forward(A, W, b)
print("Z = " + str(Z))
def test_initialize_parameters_deep(self):
parameters = tc.initialize_parameters_deep([5, 4, 3])
print("W1 = " + str(parameters["W1"]))
print("b1 = " + str(parameters["b1"]))
print("W2 = " + str(parameters["W2"]))
print("b2 = " + str(parameters["b2"]))