def _type_infer_method(context, ext_type, method, method_name, class_dict):
if method_name not in ext_type.methoddict:
return
signature = ext_type.get_signature(method_name)
restype, argtypes = signature.return_type, signature.args
class_dict[method_name] = method
func_signature, symtab, ast = pipeline.infer_types(
context, method.py_func, restype, argtypes)
ext_type.add_method(method_name, func_signature)
def wrapper(numba_func, *args, **kwargs):
# Infer argument types
arguments = args + tuple(kwargs[k] for k in sorted(kwargs))
types = tuple(context.typemapper.from_python(value) for value in arguments)
if types in _func_cache:
compiled_numba_func = _func_cache[types]
else:
# Infer the return type
func_signature, symtab, ast = pipeline.infer_types(context, f, argtypes=types)
decorator = jit(restype=func_signature.return_type, argtypes=types, target=target)
compiled_numba_func = decorator(f)
_func_cache[types] = compiled_numba_func
return numba_func.invoke_compiled(compiled_numba_func, *args, **kwargs)
def wrapper(numba_func, *args, **kwargs):
# Infer argument types
arguments = args + tuple(kwargs[k] for k in sorted(kwargs))
types = tuple(
context.typemapper.from_python(value) for value in arguments)
if types in _func_cache:
compiled_numba_func = _func_cache[types]
else:
# Infer the return type
func_signature, symtab, ast = pipeline.infer_types(
context, f, argtypes=types)
decorator = jit(restype=func_signature.return_type,
argtypes=types,
target=target)
compiled_numba_func = decorator(f)
_func_cache[types] = compiled_numba_func
return numba_func.invoke_compiled(compiled_numba_func, *args,
**kwargs)
def infer(func, argtypes):
sig, symtab, ast = pipeline.infer_types(decorators.context, func,
argtypes=argtypes)
return sig, symtab
def infer(func, argtypes):
sig, symtab, ast = pipeline.infer_types(decorators.context,
func,
argtypes=argtypes)
return sig, symtab
