mirror of https://github.com/m-labs/artiq
133 lines
3.9 KiB
Python
133 lines
3.9 KiB
Python
r"""
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The :mod:`math_fns` module lists math-related functions from NumPy recognized
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by the ARTIQ compiler so host function objects can be :func:`match`\ ed to
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the compiler type metadata describing their core device analogue.
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"""
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from collections import OrderedDict
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import numpy
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from . import builtins, types
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# Some special mathematical functions are exposed via their scipy.special
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# equivalents. Since the rest of the ARTIQ core does not depend on SciPy,
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# gracefully handle it not being present, making the functions simply not
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# available.
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try:
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import scipy.special as scipy_special
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except ImportError:
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scipy_special = None
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#: float -> float numpy.* math functions for which llvm.* intrinsics exist.
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unary_fp_intrinsics = [(name, "llvm." + name + ".f64") for name in [
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"sin",
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"cos",
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"exp",
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"exp2",
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"log",
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"log10",
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"log2",
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"fabs",
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"floor",
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"ceil",
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"trunc",
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"sqrt",
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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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unary_fp_runtime_calls = [
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("tan", "tan"),
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("arcsin", "asin"),
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("arccos", "acos"),
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("arctan", "atan"),
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("sinh", "sinh"),
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("cosh", "cosh"),
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("tanh", "tanh"),
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("arcsinh", "asinh"),
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("arccosh", "acosh"),
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("arctanh", "atanh"),
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("expm1", "expm1"),
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("cbrt", "cbrt"),
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]
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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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("tan", "tan"),
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("arcsin", "asin"),
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("arccos", "acos"),
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("arctan", "atan"),
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("sinh", "sinh"),
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("cosh", "cosh"),
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("tanh", "tanh"),
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("arcsinh", "asinh"),
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("arccosh", "acosh"),
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("arctanh", "atanh"),
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("expm1", "expm1"),
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("cbrt", "cbrt"),
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]
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scipy_special_unary_runtime_calls = [
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("erf", "erf"),
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("erfc", "erfc"),
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("gamma", "tgamma"),
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("gammaln", "lgamma"),
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("j0", "j0"),
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("j1", "j1"),
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("y0", "y0"),
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("y1", "y1"),
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]
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# Not mapped: jv/yv, libm only supports integer orders.
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#: (float, float) -> float numpy.* math functions lowered to runtime calls.
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binary_fp_runtime_calls = [
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("arctan2", "atan2"),
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("copysign", "copysign"),
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("fmax", "fmax"),
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("fmin", "fmin"),
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# ("ldexp", "ldexp"), # One argument is an int; would need a bit more plumbing.
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("hypot", "hypot"),
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("nextafter", "nextafter"),
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]
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#: Array handling builtins (special treatment due to allocations).
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numpy_builtins = ["transpose"]
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def fp_runtime_type(name, arity):
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args = [("arg{}".format(i), builtins.TFloat()) for i in range(arity)]
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return types.TExternalFunction(
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OrderedDict(args),
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builtins.TFloat(),
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name,
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# errno isn't observable from ARTIQ Python.
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flags={"nounwind", "nowrite"},
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broadcast_across_arrays=True)
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math_fn_map = {
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getattr(numpy, symbol): fp_runtime_type(mangle, arity=1)
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for symbol, mangle in (unary_fp_intrinsics + unary_fp_runtime_calls)
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}
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for symbol, mangle in binary_fp_runtime_calls:
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math_fn_map[getattr(numpy, symbol)] = fp_runtime_type(mangle, arity=2)
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for name in numpy_builtins:
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math_fn_map[getattr(numpy, name)] = types.TBuiltinFunction("numpy." + name)
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if scipy_special is not None:
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for symbol, mangle in scipy_special_unary_runtime_calls:
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math_fn_map[getattr(scipy_special, symbol)] = fp_runtime_type(mangle, arity=1)
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def match(obj):
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return math_fn_map.get(obj, None)
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