max_memory_allocated¶

paddle.device.cuda. max_memory_allocated ( device=None ) [source]

Return the peak size of gpu memory that is allocated to tensor of the given device.

Note

The size of GPU memory allocated to tensor is 256-byte aligned in Paddle, which may larger than the memory size that tensor actually need. For instance, a float32 0-D Tensor with shape [] in GPU will take up 256 bytes memory, even though storing a float32 data requires only 4 bytes.

Parameters

device (paddle.CUDAPlace or int or str, optional) – The device, the id of the device or the string name of device like ‘gpu:x’. If device is None, the device is the current device. Default: None.

Returns

The peak size of gpu memory that is allocated to tensor of the given device, in bytes.

Return type

int

Examples

>>> 
>>> import paddle
>>> paddle.device.set_device('gpu')

>>> max_memory_allocated_size = paddle.device.cuda.max_memory_allocated(paddle.CUDAPlace(0))
>>> max_memory_allocated_size = paddle.device.cuda.max_memory_allocated(0)
>>> max_memory_allocated_size = paddle.device.cuda.max_memory_allocated("gpu:0")