def vcall(self, module : 'Field', graph : 'Graph', inst : 'values.Object', args : 'functions.FunctionArgInput', line = -1):
node = nodes.NodeCall(self, [inst.get_value()], line)
value = values.ListValue()
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
# TODO should make tuple
graph.add_node(node)
return values.Object(value)
def vcall(self, module : 'Field', graph : 'Graph', inst : 'values.Object', args = [], line = -1):
funcArgs = self.parse_args(args)
vargs = self.get_values(funcArgs)
node = nodes.NodeCall(self, vargs, line)
graph.add_node(node)
value = functions.generate_value_with_same_type(vargs[0])
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.Object(value)
def vcall(self, module: 'Field', graph: 'Graph', inst: 'values.ValueRef', args: 'functions.FunctionArgInput', line=-1):
funcArgs = self.args.merge_inputs(inst, args)
node = nodes.NodeCall(self, funcArgs, line)
graph.add_node(node)
#value = functions.generate_value_with_same_type(vargs[0])
value = self.ret_value_func()
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.ValueRef(value)
def vcall(self, module : 'Field', graph : 'Graph', inst : 'values.Object', args = [], line = -1):
assert(len(args) == 0)
node = nodes.NodeCall(self, [inst.get_value()] + [v.obj.get_value() for v in args], line)
value = values.ListValue()
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
# TODO should make tuple
graph.add_node(node)
return values.Object(value)
def vcall(self,
module: 'values.Field',
graph: 'core.Graph',
inst: 'values.Value',
args=[],
line=-1):
assert (len(args) == 1)
node = nodes.NodeCall(self, [v.value for v in args], line)
inst.modify(node, None)
graph.add_node(node)
return values.NoneValue()
def vcall(self,
module: 'values.Field',
graph: 'core.Graph',
inst: 'Value',
args=[],
line=-1):
funcArgs = self.parse_args(args)
node = nodes.NodeCall(self, [v.value for v in funcArgs], line)
graph.add_node(node)
value = functions.generate_value_with_same_type(funcArgs[0].value)
node.set_outputs([value])
return value
def vcall(self, module : 'Field', graph : 'Graph', inst : 'values.Object', args = [], line = -1):
assert(len(args) == 1)
node = nodes.NodeCall(self, [inst.get_value()] + [v.obj.get_value() for v in args], line)
old_v = inst.get_value()
new_v = functions.generate_value_with_same_type(old_v)
inst.revise(new_v)
new_v.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([new_v])
graph.add_node(node)
return values.NoneValue()
def vcall(self, module: 'Field', graph: 'Graph', inst: 'values.ValueRef', args: 'functions.FunctionArgInput', line=-1):
funcArgs = self.args.merge_inputs(inst, args)
node = nodes.NodeCall(self, funcArgs, line)
old_v = inst.get_value()
new_v = functions.generate_value_with_same_type(old_v)
inst.revise(new_v)
new_v.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([new_v])
graph.add_node(node)
return values.NoneValue()
def vcall(self,
module: 'values.Field',
graph: 'Graph',
inst: 'Object',
args: 'functions.FunctionArgInput',
line=-1):
node = nodes.NodeCall(self, [v.get_value() for v in args.inputs], line)
graph.add_node(node)
value = values.TensorValue()
estimate_shape = chainer_links[type(self.owner.inst)].estimate_shape
if estimate_shape is not None:
value.shape = estimate_shape(self.owner.inst, args)
node.set_outputs([value])
return values.Object(value)
def vcall(self,
module: 'values.Field',
graph: 'Graph',
inst: 'values.ValueRef',
args: 'functions.FunctionArgInput',
line=-1):
vargs = self.args.merge_inputs(inst, args)
node = nodes.NodeCall(self, vargs, line)
graph.add_node(node)
value = values.TensorValue()
estimate_shape = chainer_links[type(self.owner.inst)].estimate_shape
if estimate_shape is not None:
value.shape = estimate_shape(self.owner.inst, vargs)
node.set_outputs([value])
return values.ValueRef(value)
def vcall(self,
module: 'Field',
graph: 'Graph',
inst: 'values.ValueRef',
args: 'functions.FunctionArgInput',
line=-1):
args = functions.FunctionArgInput()
args.inputs.append(inst)
args.keywords['self'] = inst
node = nodes.NodeCall(self, args, line)
value = values.NumberValue(None)
value.dtype = np.array(0).dtype
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
graph.add_node(node)
return values.ValueRef(value)
def vcall(self,
module: 'Field',
graph: 'Graph',
inst: 'values.ValueRef',
args: 'functions.FunctionArgInput',
line=-1):
args = functions.FunctionArgInput()
args.inputs.append(inst)
args.keywords['self'] = inst
node = nodes.NodeCall(self, args, line)
value = values.ListValue()
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
# TODO should make tuple
graph.add_node(node)
return values.ValueRef(value)
def vcall(self,
module: 'values.Field',
graph: 'Graph',
inst: 'Object',
args=[],
line=-1):
node = nodes.NodeCall(self, [v.obj.get_value() for v in args], line)
graph.add_node(node)
value = values.TensorValue()
# TODO refactor
if (isinstance(self.owner.inst, chainer.links.Linear)):
cn = self.owner.inst # type: chainer.links.Linear
if isinstance(args[0].obj.get_value(), values.TensorValue) and len(
args[0].obj.get_value().shape) >= 2:
value.shape = (args[0].obj.get_value().shape[0], cn.out_size)
if (isinstance(self.owner.inst, chainer.links.Convolution2D)):
value = functions.generate_tensor_value_with_undefined_shape_size(
args[0].obj.get_value())
node.set_outputs([value])
return values.Object(value)
