PyTorch .tensor()

The .tensor() function in PyTorch creates a tensor from a given data input.

Syntax

torch.tensor(data, dtype=None, device=None, requires_grad=False)

• data: This required parameter represents the input data for the tensor. The data must be array-like (e.g., list, tuple) or scalar.
• dtype: This optional parameter specifies the desired type for the returned tensor. If not provided, the data type is inferred from the data.
• device: This optional parameter specifies the desired device of the returned tensor. Common values are 'cpu' or 'cuda'. If not specified, the tensor is created on the default device.
• requires_grad: This optional parameter determines if autograd should record the operations on the returned tensor. The default value is False.

Example

The following example shows how to use the .tensor() function:

import torch

t1 = torch.tensor(3)
print(t1, '\n')

t2 = torch.tensor([[1.0, 3.0, 5.0], [2.0, 6.0, 0.0]])
print(t2)

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The code above generates the following output:

tensor(3)

tensor([[1., 3., 5.],
        [2., 6., 0.]])

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