jax.numpy.finfo¶
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class
jax.numpy.finfo(dtype)[source]¶ Machine limits for floating point types.
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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
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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
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machar¶ The object which calculated these parameters and holds more detailed information.
- Type
MachAr
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max¶ The largest representable number.
- Type
floating point number of the appropriate type
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min¶ The smallest representable number, typically
-max.- Type
floating point number of the appropriate type
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minexp¶ The most negative power of the base (2) consistent with there being no leading 0’s in the mantissa.
- Type
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precision¶ The approximate number of decimal digits to which this kind of float is precise.
- Type
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resolution¶ The approximate decimal resolution of this type, i.e.,
10**-precision.- Type
floating point number of the appropriate type
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tiny¶ The smallest positive usable number. Type of tiny is an appropriate floating point type.
- 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.-
__init__()¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__()Initialize self.
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