def backward(self, grad_output):
input = self._saved_tensor
grad_input, self.grad_W, self.grad_b = conv2d_backward(input, grad_output, self.W, self.b, self.kernel_size, self.pad)
#print(grad_input)
#print(self.grad_W[0][0][0])
#print(self.grad_b)
return grad_input
def backward(self, grad_output):
input_with_pad = self._saved_tensor
grad_input, self.grad_W, self.grad_b = conv2d_backward(
input_with_pad, grad_output, self.W, self.b, self.kernel_size,
self.pad)
return grad_input
'[FAILED] conv2d_forward: bug in codes, can not run for inp.shape = (4, 3, 6, 6), w.shape = (4, 3, 2, 2), ker_size = 2, pad = 0'
)
else:
if test_conv_out.shape != out.shape:
print('[ERROR] conv2d_forward: output shape is not correct')
else:
diff = test_conv_out - out
if abs(diff).max() > 1e-5:
print('[ERROR] conv2d_forward: output value is not correct')
else:
print('[PASS] conv2d_forward: all correct')
flag = 1
try:
test_grad_inp, test_grad_w, test_grad_b = conv2d_backward(
inp, grad_out, w, b, 2, 0)
except:
print(
'[FAILED] conv2d_backward: bug in codes, can not run for inp.shape = (4, 3, 6, 6), grad.shape = (4, 4, 7, 7), w.shape = (4, 3, 2, 2), ker_size = 2, pad = 0'
)
flag = 0
else:
if test_grad_inp.shape != grad_inp.shape:
print('[ERROR] conv2d_backward: grad_input shape is not correct')
flag = 0
else:
diff = test_grad_inp - grad_inp
if abs(diff).max() > 1e-5:
print('[ERROR] conv2d_backward: grad_input value is not correct')
flag = 0