PyTorch torch.rand Function
Pytorch torch Reference Manual
torch.randIt is a function in PyTorch used to create random tensors from a uniform distribution [0, 1).
This is commonly used in deep learning for scenarios such as initialization, generating random masks, and so on.
Function Definition
torch.rand(*size, dtype=None, device=None, requires_grad=False)
Parameters:
*size(int): Shape of the tensor.dtype(torch.dtype, optional): Data type.device(torch.device, optional): Device.requires_grad(bool, optional): Whether gradient computation is needed.
Return Value:
torch.Tensor: Returns a tensor containing random numbers in the range [0, 1).
Usage Examples
Example 1: Create a Random Tensor
Example
import torch
# Create a 3x4 random tensor
x = torch.rand(3, 4)
print(x)
print("Range: [{:.4f}, {:.4f})".format(x.min().item(), x.max().item()))
# Create a 3x4 random tensor
x = torch.rand(3, 4)
print(x)
print("Range: [{:.4f}, {:.4f})".format(x.min().item(), x.max().item()))
The output result is:
tensor([[0.6272, 0.1802, 0.8336, 0.3900],
[0.2188, 0.6593, 0.3598, 0.4021],
[0.9247, 0.0144, 0.2587, 0.6634]])
范围: [0.0144, 0.9247)
Example 2: Create a Random Mask
Example
import torch
# Create a random mask with 50% probability
mask = torch.rand(10) > 0.5
print("Mask:", mask)
print("True count:", mask.sum().item())
# Create a random mask with 50% probability
mask = torch.rand(10) > 0.5
print("Mask:", mask)
print("True count:", mask.sum().item())
Other Extensions