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
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.
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.
out[i+1] - out[i]
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
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
ceil((stop - start)/step)
Evenly spaced numbers with careful handling of endpoints.
Tensors of evenly spaced numbers in N-dimensions.
Grid-shaped tensors of evenly spaced numbers in N-dimensions.
>>> import mars.tensor as mt
array([0, 1, 2])
array([ 0., 1., 2.])
array([3, 4, 5, 6])