jax.numpy.finfo
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jax.numpy.finfo¶
- class jax.numpy.finfo(dtype)[source]¶
Machine limits for floating point types.
- eps¶
The difference between 1.0 and the next smallest representable float larger than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard,
eps = 2**-52
, approximately 2.22e-16.- Type
- epsneg¶
The difference between 1.0 and the next smallest representable float less than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard,
epsneg = 2**-53
, approximately 1.11e-16.- Type
- machar¶
The object which calculated these parameters and holds more detailed information.
Deprecated since version 1.22.
- Type
MachAr
- max¶
The largest representable number.
- Type
floating point number of the appropriate type
- min¶
The smallest representable number, typically
-max
.- Type
floating point number of the appropriate type
- minexp¶
The most negative power of the base (2) consistent with there being no leading 0’s in the mantissa.
- Type
- precision¶
The approximate number of decimal digits to which this kind of float is precise.
- Type
- resolution¶
The approximate decimal resolution of this type, i.e.,
10**-precision
.- Type
floating point number of the appropriate type
- smallest_normal¶
The smallest positive floating point number with 1 as leading bit in the mantissa following IEEE-754 (see Notes).
- Type
- smallest_subnormal¶
The smallest positive floating point number with 0 as leading bit in the mantissa following IEEE-754.
- Type
- Parameters
dtype (float, dtype, or instance) – Kind of floating point data-type about which to get information.
See also
Notes
For developers of NumPy: do not instantiate this at the module level. The initial calculation of these parameters is expensive and negatively impacts import times. These objects are cached, so calling
finfo()
repeatedly inside your functions is not a problem.Note that
smallest_normal
is not actually the smallest positive representable value in a NumPy floating point type. As in the IEEE-754 standard 1, NumPy floating point types make use of subnormal numbers to fill the gap between 0 andsmallest_normal
. However, subnormal numbers may have significantly reduced precision 2.References
- 1
IEEE Standard for Floating-Point Arithmetic, IEEE Std 754-2008, pp.1-70, 2008, http://www.doi.org/10.1109/IEEESTD.2008.4610935
- 2
Wikipedia, “Denormal Numbers”, https://en.wikipedia.org/wiki/Denormal_number
- __init__()¶
Methods
__init__
()Attributes
The object which calculated these parameters and holds more detailed information.
Return the value for the smallest normal.
Return the value for tiny, alias of smallest_normal.