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.any — PyTorch 1.10.1 documentation
pytorch.org › docs › stabletorch.any. input ( Tensor) – the input tensor. Tests if any element in input evaluates to True. This function matches the behaviour of NumPy in returning output of dtype bool for all supported dtypes except uint8 . For uint8 the dtype of output is uint8 itself. For each row of input in the given dimension dim , returns True if any element in ...
Pytorch-元素比较where, eq, any, all, gt - 知乎
https://zhuanlan.zhihu.com/p/411690219torch.any(input, dim, keepdim=False, *, out=None) -> Tensor 功能: For each row of input in the given dimension dim, returns True if any element in the row evaluates to True and False otherwise. If keepdim is True, the output tensor is of the same size as input except in the dimension dim where it is of size 1.
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 ...
What is the mechanism of "torch.Tensor in ... - Stack Overflow
https://stackoverflow.com › what-is...__contains__, (self,), self, element) if isinstance(element, (torch. ... b = tensor([[1, 1, 1], [4, 5, 6]]) >>> check_in = lambda x: torch.any(x == b.T).