Show activity on this post. You can use: print (dictionary [IntTensor.data [0]]) The key you're using is an object of type autograd.Variable . .data gives the tensor and the index 0 can be used to access the element. Share. Follow this answer to receive notifications. edited Dec 1 '17 at 7:52. answered Dec 1 '17 at 7:44.
05.05.2017 · In modern PyTorch, you just say float_tensor.double() to cast a float tensor to double tensor. There are methods for each type you want to cast to. If, ... tensor_one.int() : converts the tensor_one type to torch.int32. 6 Likes. mathematics (Rajan paudel) April 5, 2020, ...
We start by generating a PyTorch Tensor that’s 3x3x3 using the PyTorch random function. x = torch.rand (3, 3, 3) We can check the type of this variable by using the type functionality. type (x) We see that it is a FloatTensor. To convert this FloatTensor to a double, define the variable double_x = x.double (). double_x = x.double ()
16.09.2019 · I’m new in Pytorch and I would like to know if there’s a good way to convert an int pointer to a new tensor using Libtorch in c++. Thank you very much! LeviViana (Levi Viana) September 16, 2019, 8:44am #2. Yes there is a good way: use torch::from_blob.
How to convert a pytorch tensor of ints to a tensor of booleans? What you're looking for is to generate a boolean mask for the given integer tensor. For this, you can simply check for the condition: "whether the values in the tensor are greater than 0" using simple comparison operator ( > ) or using torch.gt() , which would then give us the desired result.
torch.as_tensor(data, dtype=None, device=None) → Tensor Convert the data into a torch.Tensor. If the data is already a Tensor with the same dtype and device , no copy will be performed, otherwise a new Tensor will be returned with computational graph retained if data Tensor has requires_grad=True.