# Customizing **bprop** Function

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Users can customize backpropagation (calculation) function of the nn.Cell object, thus control the process of the nn.Cell object gradient calculation, locating gradient problems.

Custom bprop functions are used by: adding a user-defined bprop function to the defined nn. Cell object. The training process uses user-defined bprop functions to generate reverse graphs.

The sample code is as follows:

```python
ms.set_context(mode=ms.PYNATIVE_MODE)

class Net(nn.Cell):
    def construct(self, x, y):
        z = x * y
        z = z * y
        return z

    def bprop(self, x, y, out, dout):
        x_dout = x + y
        y_dout = x * y
        return x_dout, y_dout

grad_all = ops.GradOperation(get_all=True)
output = grad_all(Net())(ms.Tensor(1, ms.float32), ms.Tensor(2, ms.float32))
print(output)
```