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.all — PyTorch 1.10.1 documentation
pytorch.org › docs › stabletorch.all(input, dim, keepdim=False, *, out=None) → Tensor For each row of input in the given dimension dim , returns True if all elements in the row evaluate 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.
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torch.allclose — PyTorch 1.10.1 documentation
pytorch.org › docs › stabletorch.allclose(input, other, rtol=1e-05, atol=1e-08, equal_nan=False) → bool This function checks if all input and other satisfy the condition: \lvert \text {input} - \text {other} \rvert \leq \texttt {atol} + \texttt {rtol} \times \lvert \text {other} \rvert ∣input− other∣ ≤ atol+rtol× ∣other∣ elementwise, for all elements of input and other.