def get_cfa_and_namedblocks(self, fn):
fid = FunctionIdentity.from_function(fn)
bc = ByteCode(func_id=fid)
cfa = self.cfa(bc)
namedblocks = self._scan_namedblocks(bc, cfa)
#### To debug, uncomment below
# print(bc.dump())
# print("IDOMS")
# for k, v in sorted(cfa.graph.immediate_dominators().items()):
# print('{} -> {}'.format(k, v))
# print("DOMFRONT")
# for k, vs in sorted(cfa.graph.dominance_frontier().items()):
# print('{} -> {}'.format(k, vs))
# print(namedblocks)
# cfa.graph.render_dot().view()
return cfa, namedblocks
def get_func_ir(func):
func_id = FunctionIdentity.from_function(func)
bc = ByteCode(func_id=func_id)
interp = Interpreter(func_id)
func_ir = interp.interpret(bc)
return func_ir
axpy[blocks, threads](r, a, x, y) # Sanity check assert (np.all(r == a * x + y)) # Python bytecode from dis import dis # noqa dis(axpy.py_func) # Bytecode interpretation from numba.core.bytecode import ByteCode, FunctionIdentity # noqa from numba.core.interpreter import Interpreter # noqa fi = FunctionIdentity.from_function(axpy.py_func) interp = Interpreter(fi) bc = ByteCode(fi) ir = interp.interpret(bc) # Control flow analysis interp.cfa.dump() dg = interp.cfa.graph.render_dot() dg.render() # or just dg in notebook # Data flow analysis interp.dfa.infos # Numba IR
