mindspore.hal.memory_allocated
- mindspore.hal.memory_allocated(device_target=None)[source]
Returns the actual memory size currently occupied by Tensor.
Note
If device_target is not specified, get the device capability of the current backend set by context.
For the CPU backend, 0 is always returned.
- Parameters
device_target (str, optional) – The device name of backend, should be one of "CPU", "GPU" and "Ascend". Default value:
None
.- Returns
int, in Byte.
Examples
>>> import mindspore as ms >>> import numpy as np >>> from mindspore import Tensor, ops >>> a = Tensor(np.ones([1, 2]), ms.float32) >>> b = Tensor(np.ones([1, 2]), ms.float32) >>> c = ops.add(a, b).asnumpy() >>> print(ms.hal.memory_allocated()) 1024