mirror of https://github.com/m-labs/artiq.git
compiler: Support common numpy.* math functions
Relies on the runtime to provide the necessary (libm-compatible) functions. The test is nifty, but a bit brittle; if this breaks in the future because of optimizer changes, do not hesitate to convert this into a more pedestrian test case.
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@ -14,7 +14,7 @@ from pythonparser import lexer as source_lexer, parser as source_parser
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from Levenshtein import ratio as similarity, jaro_winkler
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from Levenshtein import ratio as similarity, jaro_winkler
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from ..language import core as language_core
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from ..language import core as language_core
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from . import types, builtins, asttyped, prelude
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from . import types, builtins, asttyped, math_fns, prelude
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from .transforms import ASTTypedRewriter, Inferencer, IntMonomorphizer, TypedtreePrinter
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from .transforms import ASTTypedRewriter, Inferencer, IntMonomorphizer, TypedtreePrinter
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from .transforms.asttyped_rewriter import LocalExtractor
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from .transforms.asttyped_rewriter import LocalExtractor
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@ -246,7 +246,8 @@ class ASTSynthesizer:
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loc=begin_loc.join(end_loc))
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loc=begin_loc.join(end_loc))
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elif inspect.isfunction(value) or inspect.ismethod(value) or \
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elif inspect.isfunction(value) or inspect.ismethod(value) or \
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isinstance(value, pytypes.BuiltinFunctionType) or \
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isinstance(value, pytypes.BuiltinFunctionType) or \
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isinstance(value, SpecializedFunction):
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isinstance(value, SpecializedFunction) or \
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isinstance(value, numpy.ufunc):
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if inspect.ismethod(value):
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if inspect.ismethod(value):
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quoted_self = self.quote(value.__self__)
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quoted_self = self.quote(value.__self__)
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function_type = self.quote_function(value.__func__, self.expanded_from)
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function_type = self.quote_function(value.__func__, self.expanded_from)
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@ -1057,7 +1058,11 @@ class Stitcher:
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host_function = function
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host_function = function
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if function in self.functions:
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if function in self.functions:
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pass
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return self.functions[function]
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math_type = math_fns.match(function)
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if math_type is not None:
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self.functions[function] = math_type
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elif not hasattr(host_function, "artiq_embedded") or \
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elif not hasattr(host_function, "artiq_embedded") or \
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(host_function.artiq_embedded.core_name is None and
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(host_function.artiq_embedded.core_name is None and
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host_function.artiq_embedded.portable is False and
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host_function.artiq_embedded.portable is False and
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@ -0,0 +1,42 @@
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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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#: 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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"rint",
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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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]
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def unary_fp_type(name):
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return types.TExternalFunction(OrderedDict([("arg", builtins.TFloat())]),
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builtins.TFloat(), name)
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numpy_map = {
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getattr(numpy, symbol): unary_fp_type(mangle)
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for symbol, mangle in (unary_fp_intrinsics + unary_fp_runtime_calls)
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}
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def match(obj):
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return numpy_map.get(obj, None)
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@ -0,0 +1,30 @@
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# RUN: env ARTIQ_DUMP_LLVM=%t %python -m artiq.compiler.testbench.embedding %s
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# RUN: OutputCheck %s --file-to-check=%t.ll
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from artiq.language.core import *
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from artiq.language.types import *
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import numpy
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@kernel
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def entrypoint():
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# LLVM's constant folding for transcendental functions is good enough that
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# we can do a basic smoke test by just making sure the module compiles and
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# all assertions are statically eliminated.
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# CHECK-NOT: assert
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assert numpy.sin(0.0) == 0.0
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assert numpy.cos(0.0) == 1.0
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assert numpy.exp(0.0) == 1.0
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assert numpy.exp2(1.0) == 2.0
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assert numpy.log(numpy.exp(1.0)) == 1.0
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assert numpy.log10(10.0) == 1.0
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assert numpy.log2(2.0) == 1.0
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assert numpy.fabs(-1.0) == 1.0
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assert numpy.floor(42.5) == 42.0
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assert numpy.ceil(42.5) == 43.0
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assert numpy.trunc(41.5) == 41.0
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assert numpy.rint(41.5) == 42.0
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assert numpy.tan(0.0) == 0.0
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assert numpy.arcsin(0.0) == 0.0
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assert numpy.arccos(1.0) == 0.0
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assert numpy.arctan(0.0) == 0.0
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