def parse_instance(default_module,
name,
instance,
self_instance=None,
parse_shape=False) -> "Object":
from elichika.parser import values_builtin
if values_builtin.is_builtin_chainer_link(instance):
return Object(
values_builtin.ChainerLinkInstance(default_module, instance))
# need to check whether is value bool before check whether is value int
if isinstance(instance, bool):
return Object(BoolValue(instance))
if isinstance(instance, int):
return Object(NumberValue(instance))
if isinstance(instance, np.int32):
return Object(NumberValue(instance))
if isinstance(instance, np.int64):
return Object(NumberValue(instance))
if isinstance(instance, float):
return Object(NumberValue(instance))
if isinstance(instance, np.float32):
return Object(NumberValue(instance))
if isinstance(instance, np.float64):
return Object(NumberValue(instance))
if isinstance(instance, str):
return Object(StrValue(instance))
if isinstance(instance, list):
if parse_shape:
return Object(ListValue())
else:
print('List is not supported now!!!')
return Object(NumberValue(0.0))
if instance is inspect._empty:
return None
if inspect.isfunction(instance):
func = UserDefinedFunction(instance)
return Object(FuncValue(func, self_instance))
if inspect.ismethod(instance):
func = UserDefinedFunction(instance)
return Object(FuncValue(func, self_instance))
if inspect.isclass(instance):
func = functions.UserDefinedClassConstructorFunction(instance)
return Object(FuncValue(func, None))
if isinstance(instance, tuple) and 'Undefined' in instance:
shape = list(instance)
shape = -1 if shape == 'Undefined' else shape
tensorValue = TensorValue()
tensorValue.shape = tuple(shape)
return Object(tensorValue)
if isinstance(instance, np.ndarray):
tensorValue = TensorValue()
tensorValue.value = instance
tensorValue.shape = instance.shape
return Object(tensorValue)
if instance == inspect._empty:
return Object(NoneValue())
if instance is None:
return Object(NoneValue())
model_inst = UserDefinedInstance(default_module, instance, None,
isinstance(instance, chainer.Link))
return Object(model_inst)
def parse_instance(default_module, name, instance, self_instance=None):
from elichika.parser import values_builtin
if values_builtin.is_builtin_chainer_link(instance):
return values_builtin.ChainerLinkInstance(default_module, instance)
# need to check whether is value bool before check whether is value int
if isinstance(instance, bool):
return BoolValue(instance)
if isinstance(instance, int) or isinstance(instance, float):
return NumberValue(instance)
if isinstance(instance, str):
return StrValue(instance)
if isinstance(instance, list):
ret = ListValue()
ind = 0
for e in instance:
element_value = parse_instance(default_module, '', e)
ret.get_field().get_attribute(str(ind)).revise(element_value)
ind += 1
return ret
if instance is inspect._empty:
return None
if inspect.isfunction(instance):
func = UserDefinedFunction(instance)
return FuncValue(func, self_instance)
if inspect.ismethod(instance):
func = UserDefinedFunction(instance)
return FuncValue(func, self_instance)
if inspect.isclass(instance):
func = functions.UserDefinedClassConstructorFunction(instance)
return FuncValue(func, None)
if isinstance(instance, tuple) and 'Undefined' in instance:
shape = list(instance)
shape = -1 if shape == 'Undefined' else shape
tensorValue = TensorValue()
tensorValue.shape = tuple(shape)
return tensorValue
if isinstance(instance, np.ndarray):
tensorValue = TensorValue()
tensorValue.value = instance
tensorValue.shape = instance.shape
return tensorValue
if instance == inspect._empty:
return NoneValue()
if instance is None:
return NoneValue()
model_inst = UserDefinedInstance(default_module, instance, None,
isinstance(instance, chainer.Link))
return model_inst
def parse_instance(default_module, name, instance, self_instance=None, parse_shape=False, from_member = False) -> "ValueRef":
for converter in instance_converters:
ret = converter(default_module, instance)
if ret is not None:
return ValueRef(ret)
if inspect.ismethod(instance) or inspect.isfunction(instance):
if instance in function_converters.keys():
func = function_converters[instance]
return ValueRef(func)
# need to check whether is value bool before check whether is value int
if isinstance(instance, bool):
return ValueRef(BoolValue(instance))
if isinstance(instance, int):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.int32):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.int64):
return ValueRef(NumberValue(instance))
if isinstance(instance, float):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.float32):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.float64):
return ValueRef(NumberValue(instance))
if isinstance(instance, str):
return ValueRef(StrValue(instance))
if isinstance(instance, list):
if parse_shape:
return ValueRef(ListValue())
else:
print('List is not supported now!!!')
return ValueRef(NumberValue(0.0))
if instance is inspect._empty:
return None
if inspect.ismethod(instance):
func = UserDefinedFunction(instance)
return ValueRef(FuncValue(func, self_instance))
if inspect.isfunction(instance):
func = UserDefinedFunction(instance)
if from_member:
return ValueRef(FuncValue(func, self_instance))
else:
return ValueRef(FuncValue(func, None))
if inspect.isclass(instance):
func = functions.UserDefinedClassConstructorFunction(instance)
return ValueRef(FuncValue(func, None))
if isinstance(instance, tuple) and 'Undefined' in instance:
shape = list(instance)
shape = -1 if shape == 'Undefined' else shape
tensorValue = TensorValue()
tensorValue.shape = tuple(shape)
return ValueRef(tensorValue)
if isinstance(instance, tuple):
value_in_tuple = []
for v in instance:
o = parse_instance(default_module, '', v)
value_in_tuple.append(o)
return ValueRef(TupleValue(value_in_tuple))
if isinstance(instance, np.ndarray):
tensorValue = TensorValue(instance)
tensorValue.value = instance
tensorValue.shape = instance.shape
return ValueRef(tensorValue)
if instance == inspect._empty:
return ValueRef(NoneValue())
if instance is None:
return ValueRef(NoneValue())
model_inst = UserDefinedInstance(
default_module, instance, None, isinstance(instance, chainer.Link))
return ValueRef(model_inst)
def parse_instance(default_module, name, instance, self_instance=None, from_member = False, root_graph : 'graphs.Graph' = None) -> "ValueRef":
for converter in instance_converters:
ret = converter(default_module, instance)
if ret is not None:
return ValueRef(ret)
if inspect.ismethod(instance) or inspect.isfunction(instance):
if instance in function_converters.keys():
func = function_converters[instance]
return ValueRef(func)
# need to check whether is value bool before check whether is value int
if isinstance(instance, bool):
return ValueRef(BoolValue(instance))
if isinstance(instance, int):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.int32):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.int64):
return ValueRef(NumberValue(instance))
if isinstance(instance, float):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.float32):
return ValueRef(NumberValue(instance))
if isinstance(instance, np.float64):
return ValueRef(NumberValue(instance))
if isinstance(instance, str):
return ValueRef(StrValue(instance))
if instance is inspect._empty:
return None
if inspect.ismethod(instance):
func = UserDefinedFunction(instance)
return ValueRef(FuncValue(func, self_instance))
if inspect.isfunction(instance):
func = UserDefinedFunction(instance)
if from_member:
return ValueRef(FuncValue(func, self_instance))
else:
return ValueRef(FuncValue(func, None))
if inspect.isclass(instance):
func = functions.UserDefinedClassConstructorFunction(instance)
return ValueRef(FuncValue(func, None))
if isinstance(instance, list):
if root_graph is None:
value_in_tuple = []
for v in instance:
o = parse_instance(default_module, '', v)
value_in_tuple.append(o)
ret = ListValue(value_in_tuple)
else:
value_in_tuple = []
vs = []
for v in instance:
o = parse_instance(default_module, '', v)
value_in_tuple.append(o)
value = o.get_value()
if isinstance(value, TupleValue):
assert(False)
if isinstance(value, ListValue):
assert(False)
vs.append(value)
node = nodes.NodeGenerate('List', vs)
ret = ListValue(value_in_tuple)
node.set_outputs([ret])
root_graph.add_initial_node(node)
ret.estimate_type()
return ValueRef(ret)
if isinstance(instance, tuple) and 'Undefined' in instance:
shape = list(instance)
shape = -1 if shape == 'Undefined' else shape
tensorValue = TensorValue()
tensorValue.shape = tuple(shape)
return ValueRef(tensorValue)
if isinstance(instance, tuple):
if root_graph is None:
value_in_tuple = []
for v in instance:
o = parse_instance(default_module, '', v)
value_in_tuple.append(o)
return ValueRef(TupleValue(value_in_tuple))
else:
value_in_tuple = []
vs = []
for v in instance:
o = parse_instance(default_module, '', v)
value_in_tuple.append(o)
value = o.get_value()
if isinstance(value, TupleValue):
assert(False)
if isinstance(value, ListValue):
assert(False)
vs.append(value)
node = nodes.NodeGenerate('Tuple', vs)
ret = TupleValue(value_in_tuple)
node.set_outputs([ret])
root_graph.add_initial_node(node)
return ValueRef(ret)
if isinstance(instance, np.ndarray):
tensorValue = TensorValue(instance)
tensorValue.value = instance
tensorValue.shape = instance.shape
return ValueRef(tensorValue)
if instance == inspect._empty:
return ValueRef(NoneValue())
if instance is None:
return ValueRef(NoneValue())
model_inst = UserDefinedInstance(default_module, instance, None)
return ValueRef(model_inst)