def _Op(self, term):
spine = term.spine
args = term.args
# visit the innermost arguments, push those arguments on
# the instruction list first
self.visit(term.args)
fn, cost = lookup(term)
fargs = [self._vartable[a] for a in args]
# push the temporary for the result in the vartable
key = self.var(term)
# build the instruction & push it on the stack
inst = Instruction(str(fn.fn), fargs, lhs=key)
self._instructions.append(inst)
def _Arithmetic(self, term):
# All the function signatures are of the form
#
# Add(a,b)
#
# But the aterm expression for LLVM is expected to be
#
# Arithmetic(Add, ...)
#
# so we do this ugly hack to get the signature back to
# standard form
# -- hack --
op = term.args[0]
args = term.args[1:]
normal_term = AAppl(ATerm(op), args)
# --
assert isinstance(op, ATerm)
label = op.label
# Find us implementation for execution
# Returns either a ExternalF ( reference to a external C
# library ) or a PythonF, a Python callable. These can be
# anything, numpy ufuncs, numexpr, pandas, cmath whatever
from blaze.rts.funcs import lookup
# visit the innermost arguments, push those arguments on
# the instruction list first
self.visit(args)
fn, cost = lookup(normal_term)
fargs = [self._vartable[a] for a in args]
# push the temporary for the result in the vartable
key = self.var(term)
# build the instruction & push it on the stack
inst = Instruction(str(fn.fn), get_datashape(term), fargs, lhs=key)
self._instructions.append(inst)
def _Arithmetic(self, term):
# All the function signatures are of the form
#
# Add(a,b)
#
# But the aterm expression for LLVM is expected to be
#
# Arithmetic(Add, ...)
#
# so we do this ugly hack to get the signature back to
# standard form
# -- hack --
op = term.args[0]
args = term.args[1:]
normal_term = AAppl(ATerm(op), args)
# --
assert isinstance(op, ATerm)
label = op.label
# Find us implementation for execution
# Returns either a ExternalF ( reference to a external C
# library ) or a PythonF, a Python callable. These can be
# anything, numpy ufuncs, numexpr, pandas, cmath whatever
from blaze.rts.funcs import lookup
# visit the innermost arguments, push those arguments on
# the instruction list first
self.visit(args)
fn, cost = lookup(normal_term)
fargs = [self._vartable[a] for a in args]
# push the temporary for the result in the vartable
key = self.var(term)
# build the instruction & push it on the stack
inst = Instruction(str(fn.fn), get_datashape(term), fargs, lhs=key)
self._instructions.append(inst)
def test_match1():
expr = AAppl(ATerm('Add'), [AInt(1), AInt(2)])
fn, cost = lookup(expr)
assert fn.fn == add.fn.im_func
def test_match2():
expr = AAppl(ATerm('Mul'), [ATerm('Array'), ATerm('Array')])
fn, cost = lookup(expr)
assert fn.fn == multiply.fn.im_func
def test_match1():
expr = parse('Add(1,2)')
fn, cost = lookup(expr)
def test_match2():
expr = parse('Mul(1,2)')
fn, cost = lookup(expr)
def test_match2():
expr = AAppl(ATerm('Mul'), [ATerm('Array'), ATerm('Array')])
fn, cost = lookup(expr)
assert fn.fn == multiply.fn.im_func
def test_match1():
expr = AAppl(ATerm('Add'), [AInt(1), AInt(2)])
fn, cost = lookup(expr)
assert fn.fn == add.fn.im_func