def test_layer_activation_relu():
layer = nn.Layer(2, 2, activation="relu")
layer.weights = np.array([[0, 1], [-2, 0]])
layer.bias = np.array([[1, 1]])
X = np.array([[1, 1]])
A = layer.A_function(X)
assert (A == np.array([[0, 2]])).all()
def test_layer_Z_function():
layer = nn.Layer(2, 2)
layer.weights = np.array([[0, 1], [-1, 0]])
layer.bias = np.array([[1, 1]])
X = np.array([[1, 1]])
Z = layer.Z_function(X)
assert (Z == np.array([[0, 2]])).all()
def test_layer_weights_weight_shape():
layer = nn.Layer(2, 2)
assert layer.weights.shape == (2, 2)
def test_layer_d_relu():
layer = nn.Layer(2, 2, activation="relu")
z = np.array([[0, 20], [-2, 0]])
relu_z = layer.d_relu(z)
assert (relu_z == np.array([[0, 1], [0, 0]])).all()
def test_layer_weights_nodes():
layer = nn.Layer(2, 2)
assert layer.nodes == 2
def test_layer_weights_bias_shape():
layer = nn.Layer(2, 2)
assert layer.bias.shape == (1, 2)