maxframe.tensor.arange#

maxframe.tensor.arange(*args, **kwargs)[source]#

Return evenly spaced values within a given interval.

Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns a tensor rather than a list.

When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use linspace for these cases.

Parameters:

  • start (number, optional) – Start of interval. The interval includes this value. The default start value is 0.

  • stop (number) – End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point round-off affects the length of out.

  • step (number, optional) – Spacing between values. For any output out, this is the distance between two adjacent values, out[i+1] - out[i]. The default step size is 1. If step is specified as a position argument, start must also be given.

  • dtype (dtype) – The type of the output tensor. If dtype is not given, infer the data type from the other input arguments.

  • gpu (bool, optional) – Allocate the tensor on GPU if True, False as default

Returns:

arange – Tensor of evenly spaced values.

For floating point arguments, the length of the result is ceil((stop - start)/step). Because of floating point overflow, this rule may result in the last element of out being greater than stop.

Return type:

Tensor

See also

linspace

Evenly spaced numbers with careful handling of endpoints.

ogrid

Tensors of evenly spaced numbers in N-dimensions.

mgrid

Grid-shaped tensors of evenly spaced numbers in N-dimensions.

Examples

>>> import maxframe.tensor as mt

>>> mt.arange(3).execute()
array([0, 1, 2])
>>> mt.arange(3.0).execute()
array([ 0.,  1.,  2.])
>>> mt.arange(3,7).execute()
array([3, 4, 5, 6])
>>> mt.arange(3,7,2).execute()
array([3, 5])
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