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torch.arange — PyTorch 2.12 documentation

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Returns a 1-D tensor of size ⌈ end − start step ⌉ ⌈ step end−start ​ ⌉ with values from the interval [start, end) taken with common difference step beginning from start. Note: When using floating-point dtypes (especially reduced precision types like bfloat16), the results may be affected by floating-point rounding behavior. Some values in the sequence might not be exactly representable in certain floating-point formats, which can lead to repeated values or unexpected rounding. For precise sequences, it is recommended to use integer dtypes instead of floating-point dtypes. Note that non-integer step is subject to floating point rounding errors when comparing against end; to avoid inconsistency, we advise subtracting a small epsilon from end in such cases. start (Number, optional) – the starting value for the set of points. Default: 0. end (Number) – the ending value for the set of points step (Number, optional) – the gap between each pair of adjacent points. Default: 1. out (Tensor,

torch.arange # torch. arange ( start=0 , end , step=1 , * , out=None , dtype=None , layout=torch.strided , device=None , requires_grad=False ) → Tensor # Returns a 1-D tensor of size ⌈ end − start step ⌉ \left\lceil \frac{\text{end} - \text{start}}{\text{step}} \right\rceil ⌈ step end − start ​ ⌉ with values from the interval [start, end) taken with common difference step beginning from start . Note: When using floating-point dtypes (especially reduced precision types like bfloat16 ), the results may be affected by floating-point rounding behavior. Some values in the sequence might not

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