The title says it all. I want to convert a `PyTorch autograd.Variable`

to its equivalent `numpy`

array. In their official documentation they advocated using `a.numpy()`

to get the equivalent `numpy`

array (for `PyTorch tensor`

). But this gives me the following error:

Traceback (most recent call last): File "stdin", line 1, in module File "/home/bishwajit/anaconda3/lib/python3.6/site-packages/torch/autograd/variable.py", line 63, in

getattrraise AttributeError(name) AttributeError: numpy

Is there any way I can circumvent this?

numpypytorchtensor answered 10 months ago Bishwajit Purkaystha #1

I have found the way. Actually, I can first extract the `Tensor`

data from the `autograd.Variable`

by using `a.data`

. Then the rest part is really simple. I just use `a.data.numpy()`

to get the equivalent `numpy`

array. Here's the steps:

```
a = a.data # a is now torch.Tensor
a = a.numpy() # a is now numpy array
```

answered 10 months ago blitu12345 #2

Two possible case

**Using GPU:**If you try to convert a cuda float-tensor directly to numpy like shown below,it will throw an error.x.data.numpy()

*RuntimeError: numpy conversion for FloatTensor is not supported*So, you cant covert a cuda float-tensor directly to numpy,

**instead you have to convert it into a cpu float-tensor first, and try converting into numpy, like shown below.**x.data.cpu().numpy()

**Using CPU:**Converting a CPU tensor is straight forward.x.data.numpy()