使用Cuda将Pytorch张量转换为Numpy数组 [英] Convert Pytorch Tensor to Numpy Array using Cuda

问题描述

我想使用cuda将Pytorch张量转换为numpy数组:

I would like to convert a Pytorch tensor to numpy array using cuda:

这是不使用cuda时的代码行:

this is the code line while not using cuda:

A = self.tensor.weight.data.numpy()

A = self.tensor.weight.data.numpy()

如何使用cuda进行相同的操作? 据此: https://discuss. pytorch.org/t/how-to-to-transform-variable-into-numpy/104/3 似乎:

How can I do the same operation using cuda? According to this: https://discuss.pytorch.org/t/how-to-transform-variable-into-numpy/104/3 it seems:

A = self.tensor.weight.data.cpu().numpy()

A = self.tensor.weight.data.cpu().numpy()

推荐答案

我相信您还必须使用 .detach().我必须在使用CUDA和GPU的Colab上将Tensor转换为numpy数组.我这样做如下:

I believe you also have to use .detach(). I had to convert my Tensor to a numpy array on Colab which uses CUDA and GPU. I did it like the following:

embedding = learn.model.u_weight

embedding_list = list(range(0, 64382))

input = torch.cuda.LongTensor(embedding_list)
tensor_array = embedding(input)
# the output of the line bwlow is a numpy array
tensor_array.cpu().detach().numpy() 

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