data.detach().cpu().numpy()作用

import torch

if __name__ == '__main__':
	if torch.cuda.is_available():
		device = 'cuda'
	else:
		device = 'cpu'
	data = torch.rand(2,3, requires_grad=True)
	print(data)
	
	data_detach = data.detach()
	print('detach():', data_detach )
	
	data_cpu = data.detach().cpu()
	print('detach().cpu():', data_cpu)
	
	data_numpy = data.detach().cpu().numpy()
	print('detach().cpu().numpy():', data_numpy)
	

附官方文档：

https://pytorch.org/docs/stable/autograd.html?highlight=detach#torch.Tensor.detach

• detach()
  Returns a new Tensor, detached from the current graph.The result will never require gradient.
• cpu()
  Returns a copy of this object in CPU memory.If this object is already in CPU memory and on the correct device, then no copy is performed and the original object is returned.
• numpy()
  Returns self tensor as a NumPy ndarray. This tensor and the returned ndarray share the same underlying storage. Changes to self tensor will be reflected in the ndarray and vice versa.