mindspore.hal.memory_stats

mindspore.hal.memory_stats(device_target=None)[source]

Returns status information queried from the memory pool, this api will be deprecated and removed in future versions, please use the api mindspore.runtime.memory_stats() instead.

Note

For the CPU device, a dictionary with empty data is always returned.

Parameters: device_target (str, optional) – The target device specified, should be one of "CPU" , "GPU" and "Ascend" . Default None , represents the current device set by context.
Returns: dict, the queried memory information.

Examples

>>> import mindspore
>>> a = mindspore.tensor(mindspore.ops.ones([1, 2]), mindspore.float32)
>>> b = mindspore.tensor(mindspore.ops.ones([1, 2]), mindspore.float32)
>>> c = mindspore.ops.add(a, b).asnumpy()
>>> print(mindspore.hal.memory_stats())
{'total_reserved_memory': 1073741824, 'total_allocated_memory': 1024, 'total_idle_memory': 1073740800,
'total_eager_free_memory': 0, 'max_reserved_memory': 1073741824, 'max_allocated_memory': 1536,
'common_mem_pool_stats': {'block_unit_size': 1073741824, 'block_counts': 1, 'blocks_info':
{<capsule object NULL at 0x7f7e8c27b030>: {'block_stream_id': 0, 'block_memory_size': 1073741824}}},
'persistent_mem_pool_stats': {'block_unit_size': 1073741824, 'block_counts': 0, 'blocks_info': {}}}