In this article, we are going to see how to check if a tensor is contiguous or not in PyTorch.
A contiguous tensor could be a tensor whose components are stored in a contiguous order without having any empty space between them. We can check if a tensor is contiguous or not by using the Tensor.is_contiguous() method.
Tensor.is_contiguous() method
This method helps us to identify whether a tensor is contiguous or not. This method returns True if a tensor is contiguous else it will return False. Use the below syntax to understand how to check if a tensor is contiguous or not in PyTorch.
Syntax – Tensor.is_contiguous()
Example 1:
In the following program, we are going to check whether a tensor is contiguous or not.
Python3
# import torch library import torch # create torch tensors tens_1 = torch.tensor([1., 2., 3., 4., 5.]) # display tensors print("\n First Tensor - ", tens_1) # check this tensor is contiguous or not output_1 = tens_1.is_contiguous() # display output print("\n This tensor is contiguous - ", output_1) |
Output:
Example 2:
In the following program, we are going to see transpose of a tensor is contiguous or not.
Python3
# import torch library import torch # define a torch tensor tens = torch.tensor([[10., 20., 30.], [40., 50., 60.]]) # transpose of the above defined tensor tens_transpose = tens.transpose(0, 1) # display tensors print("\n Original Tensor \n", tens) print("\n Transpose of original Tensor \n", tens_transpose) # check if a tensor and it's transpose are # contiguous or not Output_1 = tens.is_contiguous() print("\n Original Tensor is contiguous - ", Output_1) Output_2 = tens_transpose.is_contiguous() print("\n Transpose of original Tensor is contiguous - ", Output_2) |
Output:
