def type_inference_stage(typingctx,
interp,
args,
return_type,
locals={},
raise_errors=True):
if len(args) != interp.arg_count:
raise TypeError("Mismatch number of argument types")
warnings = errors.WarningsFixer(errors.NumbaWarning)
infer = typeinfer.TypeInferer(typingctx, interp, warnings)
with typingctx.callstack.register(infer, interp.func_id, args):
# Seed argument types
for index, (name, ty) in enumerate(zip(interp.arg_names, args)):
infer.seed_argument(name, index, ty)
# Seed return type
if return_type is not None:
infer.seed_return(return_type)
# Seed local types
for k, v in locals.items():
infer.seed_type(k, v)
infer.build_constraint()
# return errors in case of partial typing
errs = infer.propagate(raise_errors=raise_errors)
typemap, restype, calltypes = infer.unify(raise_errors=raise_errors)
# Output all Numba warnings
warnings.flush()
return _TypingResults(typemap, restype, calltypes, errs)
def type_inference_stage(typingctx, interp, args, return_type, locals={}):
if len(args) != interp.arg_count:
raise TypeError("Mismatch number of argument types")
warnings = errors.WarningsFixer(errors.NumbaWarning)
infer = typeinfer.TypeInferer(typingctx, interp, warnings)
# Seed argument types
for index, (name, ty) in enumerate(zip(interp.bytecode.arg_names, args)):
infer.seed_argument(name, index, ty)
# Seed return type
if return_type is not None:
infer.seed_return(return_type)
# Seed local types
for k, v in locals.items():
infer.seed_type(k, v)
infer.build_constraint()
infer.propagate()
typemap, restype, calltypes = infer.unify()
# Output all Numba warnings
warnings.flush()
return typemap, restype, calltypes
