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How to access the metadata of a tensor in PyTorch?
We access the size (or shape) of a tensor and the number of elements in the tensor as the metadata of the tensor. To access the size of a tensor, we use the .size() method and the shape of a tensor is accessed using .shape.
Both .size() and .shape produce the same result. We use the torch.numel() function to find the total number of elements in the tensor.
Steps
Import the required library. Here, the required library is torch. Make sure that you have installed torch.
Define a PyTorch tensor.
Find the metadata of the tensor. Use .size() and .shape to access the size and shape of the tensor. Use torch.numel() to access the number of elements in the tensor.
Print the tensor and the metadata for better understanding.
Example 1
# Python Program to access meta-data of a Tensor
# import necessary libraries
import torch
# Create a tensor of size 4x3
T = torch.Tensor([[1,2,3],[2,1,3],[2,3,5],[5,6,4]])
print("T:\n", T)
# Find the meta-data of tensor
# Find the size of the above tensor "T"
size_T = T.size()
print("size of tensor T:\n", size_T)
# Other method to get size using .shape
print("Shape of tensor:\n", T.shape)
# Find the number of elements in the tensor "T"
num_T = torch.numel(T)
print("Number of elements in tensor T:\n", num_T)Output
When you run the above Python 3 code, it will produce the following output.
T: tensor([[1., 2., 3.], [2., 1., 3.], [2., 3., 5.], [5., 6., 4.]]) size of tensor T: torch.Size([4, 3]) Shape of tensor: torch.Size([4, 3]) Number of elements in tensor T: 12
Example 2
# Python Program to access meta-data of a Tensor
# import the libraries
import torch
# Create a tensor of random numbers
T = torch.randn(4,3,2)
print("T:\n", T)
# Find the meta-data of tensor
# Find the size of the above tensor "T"
size_T = T.size()
print("size of tensor T:\n", size_T)
# Other method to get size using .shape
print("Shape of tensor:\n", T.shape)
# Find the number of elements in the tensor "T"
num_T = torch.numel(T)
print("Number of elements in tensor T:\n", num_T)Output
When you run the above Python 3 code, it will produce the following output.
T: tensor([[[-1.1806, 0.5569], [ 2.2237, 0.9709], [ 0.4775, -0.2491]], [[-0.9703, 1.9916], [ 0.1998, -0.6501], [-0.7489, -1.3013]], [[ 1.3191, 2.0049], [-0.1195, 0.1860], [-0.6061, -1.2451]], [[-0.6044, 0.6153], [-2.2473, -0.1531], [ 0.5341, 1.3697]]]) size of tensor T: torch.Size([4, 3, 2]) Shape of tensor: torch.Size([4, 3, 2]) Number of elements in tensor T: 24
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