TorchLean API

FloatLib.Floats.Formats.BinaryInterchange.Operations.Classification.Predicates

Binary classification predicates #

The finite classes partition every descriptor's finite values. In particular, subnormal fields remain finite under every exceptional-value policy, whereas zero fields alone do not imply zero in FNUZ. The finite hypothesis in isZero_iff_fields_of_isFinite excludes its NaN.

For a finite value, zero means that both magnitude fields vanish.

Every subnormal field pattern is finite, including under the FNUZ policy.

The normal predicate uses the descriptor's finiteness policy and nonzero exponent.

Normal values are exactly the finite values that are neither zero nor subnormal.

Finiteness is the union of zero, subnormal, and normal classification.

Zero and subnormal classification are disjoint.

Signaling and quiet NaNs partition NaNs under every supported encoding policy.

Every signaling NaN is a NaN. Non-IEEE policies have no signaling NaNs.

@[simp]

Every exact-width binary datum is canonical, including every NaN payload.

Canonical classification agrees with exact reconstruction of all stored fields. This reconstruction preserves signaling bits and payloads as well as finite data.