torch.Tensor — PyTorch 1.10.1 documentation
https://pytorch.org/docs/stable/tensorstorch.ByteTensor. /. 1. Sometimes referred to as binary16: uses 1 sign, 5 exponent, and 10 significand bits. Useful when precision is important at the expense of range. 2. Sometimes referred to as Brain Floating Point: uses 1 sign, 8 exponent, and 7 significand bits. Useful when range is important, since it has the same number of exponent bits ...
torch.masked_select — PyTorch 1.10.1 documentation
pytorch.org › docs › stabletorch.masked_select. Returns a new 1-D tensor which indexes the input tensor according to the boolean mask mask which is a BoolTensor. The shapes of the mask tensor and the input tensor don’t need to match, but they must be broadcastable. input ( Tensor) – the input tensor. out ( Tensor, optional) – the output tensor.
torch.Tensor — PyTorch 1.10.1 documentation
pytorch.org › docs › stabletorch.ByteTensor. /. 1. Sometimes referred to as binary16: uses 1 sign, 5 exponent, and 10 significand bits. Useful when precision is important at the expense of range. 2. Sometimes referred to as Brain Floating Point: uses 1 sign, 8 exponent, and 7 significand bits. Useful when range is important, since it has the same number of exponent bits ...
Python Examples of torch.BoolTensor
www.programcreek.com › 116185 › torchThe following usage are allowed: 1. `new_boxes = boxes [3]`: return a `Boxes` which contains only one box. 2. `new_boxes = boxes [2:10]`: return a slice of boxes. 3. `new_boxes = boxes [vector]`, where vector is a torch.BoolTensor with `length = len (boxes)`. Nonzero elements in the vector will be selected.