How to convert a NumPy ndarray to a PyTorch Tensor and vice versa?

PythonPyTorchServer Side ProgrammingProgramming

A PyTorch tensor is like numpy.ndarray. The difference between these two is that a tensor utilizes the GPUs to accelerate numeric computation. We convert a numpy.ndarray to a PyTorch tensor using the function torch.from_numpy(). And a tensor is converted to numpy.ndarray using the .numpy() method.

Steps

  • Import the required libraries. Here, the required libraries are torch and numpy.

  • Create a numpy.ndarray or a PyTorch tensor.

  • Convert the numpy.ndarray to a PyTorch tensor using torch.from_numpy() function or convert the PyTorch tensor to numpy.ndarray using the .numpy() method.

  • Finally, print the converted tensor or numpy.ndarray.

Example 1

The following Python program converts a numpy.ndarray to a PyTorch tensor.

# import the libraries
import torch
import numpy as np

# Create a numpy.ndarray "a"
a = np.array([[1,2,3],[2,1,3],[2,3,5],[5,6,4]])
print("a:\n", a)

print("Type of a :\n", type(a))
# Convert the numpy.ndarray to tensor
t = torch.from_numpy(a)
print("t:\n", t)
print("Type after conversion:\n", type(t))

Output

When you run the above code, it will produce the following output

a:
[[1 2 3]
[2 1 3]
[2 3 5]
[5 6 4]]
Type of a :
<class 'numpy.ndarray'>
t:
tensor([[1, 2, 3],
         [2, 1, 3],
         [2, 3, 5],
         [5, 6, 4]], dtype=torch.int32)
Type after conversion:
<class 'torch.Tensor'>

Example 2

The following Python program converts a PyTorch tensor to a numpy.ndarray.

# import the libraries
import torch
import numpy

# Create a tensor "t"
t = torch.Tensor([[1,2,3],[2,1,3],[2,3,5],[5,6,4]])
print("t:\n", t)
print("Type of t :\n", type(t))

# Convert the tensor to numpy.ndarray
a = t.numpy()
print("a:\n", a)
print("Type after conversion:\n", type(a))

Output

When you run the above code, it will produce the following output

t:
tensor([[1., 2., 3.],
         [2., 1., 3.],
         [2., 3., 5.],
         [5., 6., 4.]])
Type of t :
<class 'torch.Tensor'>
a:
[[1. 2. 3.]
[2. 1. 3.]
[2. 3. 5.]
[5. 6. 4.]]
Type after conversion:
<class 'numpy.ndarray'>
raja
Published on 06-Nov-2021 09:37:24
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