I wrote a float16/half-precision module here:
https://github.com/m-paradox/numpy_half
I've tested it with NumPy 1.3.0 and the latest trunk. With it, you can do
things like this:
>>> import numpy as np, half as h
>>> np.array([0,0.1,1.0/3.0], dtype='float16')
array([ 0. , 0.09997559, 0.33325195], dtype=float16)
>>> a = h.float16(1.5)
>>> print a
1.5
>>> a.dtype
dtype('float16')
Many functions aren't implemented, so things like this don't work:
>>> np.arange(10, dtype='float16')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: no fill-function for data-type.
Also, because of bug #809, it looks like there's no way to nicely support
'<f2' or '>f2'.
>>> np.array([10], dtype='f2')
array([ 10.], dtype=float16)
>>> np.array([10], dtype='<f2')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: data type not understood
What would need to be done to build it in as a supported NumPy data type?
-Mark
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