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nir: fix constant evaluation of fddx/fddy sourcing Inf & NaN constant

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A derivative of NaN is NaN.

Reviewed-by: Faith Ekstrand <faith.ekstrand@collabora.com>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/24792>
This commit is contained in:
Marek Olšák
2023-07-08 18:00:45 -04:00
parent 8780f66c3a
commit ee225e31c1
1 changed files with 2 additions and 2 deletions
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4
src/compiler/nir/nir_opcodes.py
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@@ -332,12 +332,12 @@ unop_convert("frexp_sig", tfloat, tfloat, "int n; dst = frexp(src0, &n);")
deriv_template = """ deriv_template = """
Calculate the screen-space partial derivative using {} derivatives of the input Calculate the screen-space partial derivative using {} derivatives of the input
with respect to the {}-axis. The constant folding is trivial as the derivative with respect to the {}-axis. The constant folding is trivial as the derivative
of a constant is 0. of a constant is 0 if the constant is not Inf or NaN.
""" """
for mode, suffix in [("either fine or coarse", ""), ("fine", "_fine"), ("coarse", "_coarse")]: for mode, suffix in [("either fine or coarse", ""), ("fine", "_fine"), ("coarse", "_coarse")]:
for axis in ["x", "y"]: for axis in ["x", "y"]:
unop(f"fdd{axis}{suffix}", tfloat, "0.0", unop(f"fdd{axis}{suffix}", tfloat, "isfinite(src0) ? 0.0 : NAN",
description = deriv_template.format(mode, axis.upper())) description = deriv_template.format(mode, axis.upper()))
# Floating point pack and unpack operations. # Floating point pack and unpack operations.