def Generator(arguments):
properties = arguments.get(name, None)
if properties is None: return arguments
desc_name = name_v2 if name_v2 else name
if name_v2: del arguments[name]
if not isinstance(properties, (list, tuple)):
properties = [properties]
# Check whether to use desc
tensor_in_properties = False
for property in properties:
if isinstance(property, Tensor):
tensor_in_properties = True
if tensor_in_properties:
properties_t = []
for property in properties:
if isinstance(property, Tensor):
if as_target:
if not 'extra_inputs' in arguments:
arguments['extra_inputs'] = []
arguments['extra_inputs'].extend([property])
properties_t.append(property.name)
else:
properties_t.append(Tensor.convert_to(property, dtype).name)
arguments[desc_name] = None
arguments[desc_name + '_desc'] = properties_t
else:
arguments[desc_name] = properties
return arguments
def Impl(*args, **kwargs):
inputs = args[0]
if isinstance(inputs, (list, tuple)):
dtype = None
for input in inputs:
if isinstance(input, Tensor) and \
input.dtype is not None:
dtype = input.dtype
break
for i, input in enumerate(inputs):
if not isinstance(input, Tensor):
inputs[i] = Tensor.convert_to(input, dtype)
return op_func(inputs + list(args[1:]), **kwargs)
else:
if not isinstance(inputs, Tensor):
inputs = Tensor.convert_to(inputs)
return op_func([inputs] + list(args[1:]), **kwargs)
