Open In App

How to Convert Pytorch tensor to Numpy array?

Improve
Improve
Like Article
Like
Save
Share
Report

In this article, we are going to convert Pytorch tensor to NumPy array.

Method 1: Using numpy().

Syntax: tensor_name.numpy()

Example 1: Converting one-dimensional a tensor to NumPy array

Python3




# importing torch module
import torch
  
# import numpy module
import numpy
  
# create one dimensional tensor with
# float type elements
b = torch.tensor([10.12, 20.56, 30.00, 40.3, 50.4])
  
print(b)
  
# convert this into numpy array using
# numpy() method
b = b.numpy()
  
# display
b


Output:

tensor([10.1200, 20.5600, 30.0000, 40.3000, 50.4000])
array([10.12, 20.56, 30.  , 40.3 , 50.4 ], dtype=float32)

Example 2: Converting two-dimensional tensors to NumPy array

Python3




# importing torch module
import torch
  
# import numpy module
import numpy
  
# create two dimensional tensor with
# integer type elements
b = torch.tensor([[1, 2, 3, 4, 5], [3, 4, 5, 6, 7], 
                  [4, 5, 6, 7, 8]])
  
print(b)
  
# convert this into numpy array using
# numpy() method
b = b.numpy()
  
# display
b


Output:

tensor([[1, 2, 3, 4, 5],
       [3, 4, 5, 6, 7],
       [4, 5, 6, 7, 8]])
array([[1, 2, 3, 4, 5],
      [3, 4, 5, 6, 7],
      [4, 5, 6, 7, 8]])

Method 2: Using numpy.array() method.

This is also used to convert a tensor into NumPy array.

Syntax: numpy.array(tensor_name)

Example: Converting two-dimensional tensor to NumPy array

Python3




# importing torch module
import torch
  
# import numpy module
import numpy
  
# create two dimensional tensor with 
# integer type elements
b = torch.tensor([[1, 2, 3, 4, 5], [3, 4, 5, 6, 7], 
                  [4, 5, 6, 7, 8]])
  
print(b)
  
# convert this into numpy array using 
# numpy.array() method
b = numpy.array(b)
  
# display
b


Output:

tensor([[1, 2, 3, 4, 5],
       [3, 4, 5, 6, 7],
       [4, 5, 6, 7, 8]])
array([[1, 2, 3, 4, 5],
      [3, 4, 5, 6, 7],
      [4, 5, 6, 7, 8]])


Last Updated : 30 Jun, 2021
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads