.from_numpy()

The .from_numpy() function in PyTorch creates a tensor from a NumPy array, sharing the underlying memory. Changes to the NumPy array will affect the tensor. However, only in-place operations on the tensor will affect the NumPy array, while operations that create new tensors will not.

Syntax

torch.from_numpy(ndarray)

• ndarray: A NumPy array to be converted into a PyTorch tensor. It must be a NumPy array with a supported dtype (e.g., float32, int64).

Example

The following example uses the .from_numpy() function to convert a NumPy array into a PyTorch tensor:

import numpy as np
import torch

# Create a NumPy array
np_array = np.array([1, 2, 3, 4])

# Convert NumPy array to a PyTorch tensor (shared memory)
tensor = torch.from_numpy(np_array)
print(tensor)

The output is:

tensor([1, 2, 3, 4])