def test_relu_2_backward(self):
print('\n==================================')
print(' Test ReLU backward ')
print('==================================')
np.random.seed(123)
relu = ReLU()
x = np.random.randn(7, 7)
d_prev = np.random.randn(*x.shape)
out = relu.forward(x)
dx = relu.backward(d_prev, 0.0)
correct_dx = [[0., -1.29408532, -1.03878821, 0., 0., 0.02968323, 0.],
[0., 1.75488618, 0., 0., 0., 0.79486267, 0.],
[
0., 0., 0.80723653, 0.04549008, -0.23309206,
-1.19830114, 0.19952407
], [0.46843912, 0., 1.16220405, 0., 0., 1.03972709, 0.],
[0., 0., 0., 0., 0., 0., 0.80730819],
[0., -1.0859024, -0.73246199, 0., 2.08711336, 0., 0.],
[
0., 0.18103513, 1.17786194, 0., 1.03111446,
-1.08456791, -1.36347154
]]
e = rel_error(correct_dx, dx)
print('dX relative difference:', e)
self.assertTrue(e <= 5e-08)
'================================ 2. ReLU =================================='
)
"""
* Correct ReLU *
Forward:
[1. 0. 3.]
Backward:
[-10 0 -30]
"""
relu = ReLU()
temp2 = np.array([1, -0.1, 3], dtype=np.float32)
temp3 = np.array([-10, -20, -30], dtype=np.float32)
print('ReLU Check')
print('Forward: \n', relu.forward(temp2))
print('Backward: \n', relu.backward(temp3))
print()
# ===========================================================================
print(
'=========================== 3. Convolution Layer =========================='
)
# Convolution with stride 1, no padding
in_channel = 1
out_channel = 3
kernel_size = 3
stride = 1
pad = 0
conv_layer = ConvolutionLayer(in_channel, out_channel, kernel_size, stride,