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Updated 4 years ago
PyTorch and tensors
I/O
One of the hairiest problems is always data loading and converting from one library to another. We'll take a look at examples of this, specifically interacting with Numpy. It is also important to create dummy tensors to test, we'll see this too.
- from_numpy
- numpy
- zeros
- new_zeros
- rand
# Import torch and other required modules
import torch
Function 1 - torch.from_numpy
It is very common to need to interact with numpy, converting arrays to and from Pytorch tensors.
# Example 1 - Get a tensor from a numpy array
import numpy as np
np_inputs = np.array([[1, 2], [3, 4.]])
print(np_inputs)
tensor_input = torch.from_numpy(np_inputs)
print(tensor_input)
[[1. 2.]
[3. 4.]]
tensor([[1., 2.],
[3., 4.]], dtype=torch.float64)
Simple list to numpy array, numpy array to tensor example.