mindspore.ops.Depend

class mindspore.ops.Depend

Depend is used for processing dependency operations.

In most scenarios, if operators have IO side effects or memory side effects, they will be executed according to the user’s semantics. In some scenarios, if the two operators A and B have no order dependency, and A must be executed before B, we recommend using Depend to specify their execution order. The usage method is as follows:

a = A(x)                --->        a = A(x)
b = B(y)                --->        y = Depend(y, a)
                        --->        b = B(y)

Inputs:

• value (Tensor) - the real value to return for depend operator.

• expr (Expression) - the expression to execute with no outputs.

Outputs:

Tensor, the value passed by last operator.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> import mindspore
>>> import mindspore.nn as nn
>>> import mindspore.ops as ops
>>> from mindspore import Tensor
>>> class Net(nn.Cell):
...     def __init__(self):
...         super(Net, self).__init__()
...         self.softmax = ops.Softmax()
...         self.depend = ops.Depend()
...
...     def construct(self, x, y):
...         mul = x * y
...         y = self.depend(y, mul)
...         ret = self.softmax(y)
...         return ret
...
>>> x = Tensor(np.ones([4, 5]), dtype=mindspore.float32)
>>> y = Tensor(np.ones([4, 5]), dtype=mindspore.float32)
>>> net = Net()
>>> output = net(x, y)
>>> print(output)
[[0.2 0.2 0.2 0.2 0.2]
 [0.2 0.2 0.2 0.2 0.2]
 [0.2 0.2 0.2 0.2 0.2]
 [0.2 0.2 0.2 0.2 0.2]]