maxframe.tensor.sinh#

maxframe.tensor.sinh(x, out=None, where=None, **kwargs)[source]#

Hyperbolic sine, element-wise.

Equivalent to 1/2 * (mt.exp(x) - mt.exp(-x)) or -1j * mt.sin(1j*x).

Parameters:

x (array_like) – Input tensor.
out (Tensor, None, or tuple of Tensor and None, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where (array_like, optional) – Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs

Returns:

y – The corresponding hyperbolic sine values.

Return type:

Tensor

Notes

If out is provided, the function writes the result into it, and returns a reference to out. (See Examples)

References

M. Abramowitz and I. A. Stegun, Handbook of Mathematical Functions. New York, NY: Dover, 1972, pg. 83.

Examples

>>> import maxframe.tensor as mt

>>> mt.sinh(0).execute()
0.0
>>> mt.sinh(mt.pi*1j/2).execute()
1j
>>> mt.sinh(mt.pi*1j).execute() # (exact value is 0)
1.2246063538223773e-016j
>>> # Discrepancy due to vagaries of floating point arithmetic.

>>> # Example of providing the optional output parameter
>>> out1 = mt.zeros(1)
>>> out2 = mt.sinh([0.1], out1)
>>> out2 is out1
True

>>> # Example of ValueError due to provision of shape mis-matched `out`
>>> mt.sinh(mt.zeros((3,3)),mt.zeros((2,2))).execute()
Traceback (most recent call last):
...
ValueError:  operators could not be broadcast together with shapes (3,3) (2,2)

maxframe.tensor.sinh#

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