torch.FloatTensor

torch.FloatTensor is a class in PyTorch that represents a tensor of floating-point numbers. It is a multidimensional array that can hold any number of elements of the same data type (i.e., float).

Here's an example of creating a 2D tensor of floating-point numbers in PyTorch:

import torch

# create a 2D tensor of size 3x2
x = torch.FloatTensor([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])

print(x)

Output:

tensor([[ 1.,  2.],
        [ 3.,  4.],
        [ 5.,  6.]])

In this example, we create a 2D tensor with 3 rows and 2 columns, where each element is a floating-point number. We pass a list of lists of these numbers to the `torch.FloatTensor()` constructor function.

Note that we can perform various operations on this tensor, such as addition, subtraction, multiplication, and division, using PyTorch's built-in functions.