mindspore.ops.AssignAdd

class mindspore.ops.AssignAdd

Updates a Parameter by adding a value to it.

Inputs of variable and value comply with the implicit type conversion rules to make the data types consistent. If they have different data types, the lower priority data type will be converted to the relatively highest priority data type. If value is a number, the number is automatically converted to Tensor, and the data type is consistent with the Tensor data type involved in the operation.

Note

Since variable is a data type Parameter, the data type cannot be changed, so only the type of value is allowed to be promoted to the type of variable. And the conversion type supported by different devices will be different, it is recommended to use the same data type when using this operator.

Inputs:

• variable (Parameter) - The Parameter. \((N,*)\) where \(*\) means, any number of additional dimensions, its rank should be less than 8.

• value (Union[numbers.Number, Tensor]) - The value to be added to the variable. It must have the same shape as variable if it is a Tensor. it is recommended to use the same data type when using this operator.

Outputs:

Tensor, has the same data type and shape as original variable.

Raises

• TypeError – If value is neither Number nor Tensor.

• RuntimeError – If the data type of variable and value conversion of Parameter is required when data type conversion of Parameter is not supported.

Supported Platforms:

Ascend GPU CPU

Examples

>>> class Net(nn.Cell):
...     def __init__(self):
...         super(Net, self).__init__()
...         self.AssignAdd = ops.AssignAdd()
...         self.variable = mindspore.Parameter(initializer(1, [1], mindspore.int64), name="global_step")
...
...     def construct(self, x):
...         self.AssignAdd(self.variable, x)
...         return self.variable
...
>>> net = Net()
>>> value = Tensor(np.ones([1]).astype(np.int64)*100)
>>> output = net(value)
>>> print(net.variable.asnumpy())
[101]