mirror of https://github.com/m-labs/artiq.git
compiler: Implement numpy.rint() using llvm.round()
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@ -15,8 +15,20 @@ unary_fp_intrinsics = [(name, "llvm." + name + ".f64") for name in [
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"floor",
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"floor",
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"ceil",
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"ceil",
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"trunc",
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"trunc",
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"rint",
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]] + [
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]]
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# numpy.rint() seems to (NumPy 1.19.0, Python 3.8.5, Linux x86_64)
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# implement round-to-even, but unfortunately, rust-lang/libm only
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# provides round(), which always rounds away from zero.
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#
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# As there is no equivalent of the latter in NumPy (nor any other
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# basic rounding function), expose round() as numpy.rint anyway,
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# even if the rounding modes don't match up, so there is some way
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# to do rounding on the core device. (numpy.round() has entirely
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# different semantics; it rounds to a configurable number of
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# decimals.)
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("rint", "llvm.round.f64"),
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]
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#: float -> float numpy.* math functions lowered to runtime calls.
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#: float -> float numpy.* math functions lowered to runtime calls.
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unary_fp_runtime_calls = [
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unary_fp_runtime_calls = [
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@ -90,6 +90,6 @@ class CompareHostDeviceTest(ExperimentCase):
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]
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]
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for name in names:
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for name in names:
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op = "numpy.{}(a)".format(name)
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op = "numpy.{}(a)".format(name)
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print(op)
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# Avoid 0.5, as numpy.rint's rounding mode currently doesn't match.
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self._test_unaryop(op, 0.5)
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self._test_unaryop(op, 0.51)
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self._test_unaryop(op, numpy.array([[0.3, 0.4], [0.5, 0.6]]))
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self._test_unaryop(op, numpy.array([[0.3, 0.4], [0.51, 0.6]]))
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