def vcall(self,
module: 'values.Field',
graph: 'graphs.Graph',
inst: 'values.Object',
args: 'functions.FunctionArgInput',
context: 'functions.VEvalContext' = None,
line=-1):
assert (inst is None)
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
dtype_value = vargs[1]
if isinstance(dtype_value, values.StrValue):
if not dtype_value.has_constant_value():
utils.print_error('Failed to get dtype str ', line)
return None
dtype = utils.str_2_dtype(dtype_value.get_constant_value())
elif dtype_value is not None and not isinstance(
dtype_value, values.NoneValue):
# TODO : make better
dtype = np.array(1, dtype=dtype_value.func.dtype).dtype
else:
dtype = np.array(vargs[1].internal_value).dtype
node = nodes.NodeGenerate('zeros', funcArgs, line)
graph.add_node(node)
value = values.TensorValue()
value.dtype = dtype
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.Object(value)
def vcall(self,
module: 'values.Field',
graph: 'graphs.Graph',
inst: 'values.Object',
args: 'functions.FunctionArgInput',
context: 'functions.VEvalContext' = None,
line=-1):
assert (inst is None)
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
value = values.ListValue()
if isinstance(vargs[0], values.NoneValue):
node = nodes.NodeGenerate('List', [], line)
graph.add_node(node)
else:
node = nodes.NodeConvert('List', vargs[0], line)
graph.add_node(node)
if vargs[0].has_constant_value():
refs = []
for attr_or_ref in vargs[0].internal_value:
refs.append(
utils.try_get_obj(attr_or_ref, 'list',
utils.LineProperty()))
value.internal_value = refs
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.Object(value)
def vcall(self, module: 'values.Field', graph: 'graphs.Graph', inst: 'values.Object', args: 'functions.FunctionArgInput',
option: 'vevaluator.VEvalContext' = None, line=-1):
funcArgs = self.args.merge_inputs(inst, args)
if inst.in_container:
raise Exception('Invalid operation')
key_hashes = inst.get_value().internal_keys.keys()
attributes = inst.get_value().internal_values
vargs = []
vargs_ref = []
for hash in key_hashes:
varg = attributes.get_attribute(hash)
if varg.has_obj():
vargs.append(utils.try_get_obj(varg, 'dict_values', utils.LineProperty()).get_value())
vargs_ref.append(utils.try_get_obj(varg, 'dict_values', utils.LineProperty()))
else:
assert(False)
node = nodes.NodeGenerate('List', vargs , line)
graph.add_node(node)
value = values.ListValue(vargs_ref)
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return value
def vcall(self,
module: 'values.Field',
graph: 'graphs.Graph',
inst: 'values.Object',
args: 'functions.FunctionArgInput',
context: 'functions.VEvalContext' = None,
line=-1):
if context._for_unroll:
for ref in args.inputs:
if not ref.get_value().has_constant_value():
assert False, 'Loop unrolling was requested for non-constant sequence at %s' % line
refs = []
for num in range(*(ref.get_value().internal_value
for ref in args.inputs)):
refs.append(values.Object(values.NumberValue(num)))
value = values.ListValue(refs)
return values.Object(value)
else:
node = nodes.NodeGenerate('range',
[v.get_value() for v in args.inputs],
line)
graph.add_node(node)
value = values.RangeValue()
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):
node = nodes.NodeGenerate(
'range', [v.get_value() for v in args.inputs], line)
graph.add_node(node)
value = values.RangeValue()
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.ValueRef(value)
def vcall(self, module: 'Field', graph: 'Graph', inst: 'values.ValueRef', args: 'functions.FunctionArgInput', line=-1):
assert(inst is None)
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
value = values.ListValue()
if isinstance(vargs[0], values.NoneValue):
node = nodes.NodeGenerate('List', [], line)
graph.add_node(node)
else:
node = nodes.NodeConvert('List', vargs[0], line)
graph.add_node(node)
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.ValueRef(value)
def vcall(self,
module: 'Field',
graph: 'Graph',
inst: 'values.ValueRef',
args: 'functions.FunctionArgInput',
line=-1):
assert (inst is None)
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
dtype_value = vargs[1]
if isinstance(dtype_value, values.StrValue):
if not dtype_value.has_constant_value():
utils.print_error('Failed to get dtype str ', line)
return None
if dtype_value.get_constant_value() == 'q':
dtype = np.int64
elif dtype_value.get_constant_value() == 'i':
dtype = np.int32
elif dtype_value.get_constant_value() == 'g':
dtype = np.float64
elif dtype_value.get_constant_value() == 'f':
dtype = np.float32
else:
assert (False)
elif dtype_value is not None and not isinstance(
dtype_value, values.NoneValue):
# TODO : make better
dtype = np.array(1, dtype=dtype_value.func.dtype).dtype
elif isinstance(vargs[0], values.TensorValue):
dtype = vargs[0].dtype
else:
dtype = None
node = nodes.NodeGenerate('array', funcArgs, line)
graph.add_node(node)
value = values.TensorValue()
value.dtype = dtype
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
return values.ValueRef(value)
def veval_ast_list(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
assert (isinstance(astc.nast, gast.gast.List))
'''
Ex. [],[x,y,z]
TODO : Initializer
'''
lineprop = utils.LineProperty(astc.lineno, astc.filename)
elts = []
for elt in astc.nast.elts:
elt_ = veval_ast(astc.c(elt), local_field, graph)
elt_obj = try_get_ref(elt_, 'list', lineprop)
elts.append(elt_obj)
node = nodes.NodeGenerate('List', [elt.get_value() for elt in elts],
lineprop)
graph.add_node(node)
value = values.ListValue(elts)
node.set_outputs([value])
return values.ValueRef(value)
def veval_ast_tuple(astc: 'AstContext',
local_field: 'values.Field',
graph: 'Graph',
option: 'VEvalOption' = None):
assert (isinstance(astc.nast, gast.gast.Tuple))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
if option is not None and option.eval_as_written_target:
vs = []
for v in astc.nast.elts:
a_ = veval_ast(astc.c(v), local_field, graph, option=option)
vs.append(a_)
return vs
else:
vs_ref = []
vs = []
for v in astc.nast.elts:
a_ = veval_ast(astc.c(v), local_field, graph, option=option)
v_ = try_get_ref(a_, 'tuple', lineprop)
if v_ is None:
utils.print_warning('Unknown tuple element {}'.format(v),
lineprop)
return None
vs_ref.append(v_)
vs.append(v_.get_value())
v_.in_container = True
tuple_value = values.TupleValue(vs_ref)
node = nodes.NodeGenerate('Tuple', vs, line=lineprop)
node.set_outputs([tuple_value])
graph.add_node(node)
return values.ValueRef(tuple_value)
def veval_ast_listcomp(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
'''
Ex. [x for x in xx]
[elt for target in iter]
'''
assert (isinstance(astc.nast, gast.gast.ListComp))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
listcomp_guid = str(utils.get_guid())
listcomp_id = 'listcomp_' + listcomp_guid
body_id = 'listcomp_body_' + listcomp_guid
internal_counter_id = '@internal/listcomp_counter_' + listcomp_guid
internal_list_id = '@internal/listcomp_list_' + listcomp_guid
internal_cond_id = '@internal/listcomp_cond_' + listcomp_guid
generator = astc.nast.generators[0]
iter_value = try_get_value(
veval_ast(astc.c(generator.iter), local_field, graph), 'generator',
lineprop)
list_value = values.ListValue()
list_obj = values.ValueRef(list_value)
node_generate_list = nodes.NodeGenerate('List', [], lineprop)
node_generate_list.set_outputs([list_value])
graph.add_node(node_generate_list)
# body
target_name = ''
if isinstance(generator.target, gast.gast.Name):
target_name = generator.target.id
else:
if config.show_warnings:
print('This for is not supported. in L.{}'.format(astc.lineno))
return None
counter_value = values.NumberValue(None)
counter_value.dtype = np.array(0).dtype
counter_value.name = internal_counter_id
cond_value = values.BoolValue(None)
cond_value.name = internal_cond_id
# set values with internal name
local_field.get_attribute(internal_list_id).revise(list_obj)
values.push_history(listcomp_id)
body_graph = Graph()
body_graph.root_graph = graph.root_graph
body_graph.name = 'Body_' + listcomp_guid
node_forgen = nodes.NodeForGenerator(counter_value, iter_value)
target_ref = iter_value.get_iterator()
if target_ref is None:
target_ref = values.ValueRef(values.UnknownValue())
if config.show_warnings:
print('unknown iteratable type in L.{}'.format(lineprop))
target_value = target_ref.get_value()
node_forgen.set_outputs([target_ref.get_value()])
local_field.get_attribute(target_name).revise(target_ref)
body_graph.add_node(node_forgen)
elt = veval_ast(astc.c(astc.nast.elt), local_field, body_graph)
elt_obj = try_get_ref(elt, 'listcomp', lineprop)
finput = functions.FunctionArgInput()
finput.inputs.append(elt_obj)
append_value = local_field.get_attribute(internal_list_id).get_ref(
).get_field().get_attribute('append').get_ref().get_value()
append_value.func.vcall(
None, body_graph,
local_field.get_attribute(internal_list_id).get_ref(), finput,
lineprop)
value_inputs = values.get_inputs()
value_outputs = values.get_outputs()
values.pop_history()
inputs = []
outputs = []
# default input for subgraph's input
body_graph.add_input_value(counter_value)
body_graph.add_input_value(cond_value)
body_graph.add_input_value(iter_value)
# default output for subgraph's output
body_graph.add_output_value(cond_value)
body_graph.add_output_value(iter_value)
# default output
outputs.append(functions.generate_value_with_same_type(iter_value))
# generate pairs
value_pairs = {}
for v in value_inputs:
key = str(v.field.id) + '_' + v.name
if not (key in value_pairs.keys()):
value_pairs[key] = {}
value_pairs[key]['field'] = v.field
value_pairs[key]['name'] = v.name
value_pairs[key]['input_value'] = v.input_value
value_pairs[key]['input_body_value'] = v.value
for v in value_outputs:
key = str(v.field.id) + '_' + v.name
if not (key in value_pairs.keys()):
value_pairs[key] = {}
value_pairs[key]['field'] = v.field
value_pairs[key]['name'] = v.name
value_pairs[key]['output_body_value'] = v.value
value_pairs[key]['output_obj'] = v.obj
# remove iterator
removed_name = str(local_field.id) + '_' + target_value.name
del value_pairs[removed_name]
for k, v in value_pairs.items():
name = v['name']
field = v['field']
if 'input_body_value' in v:
inputs.append(v['input_value'])
body_graph.add_input_value(v['input_body_value'])
else:
temp_value1 = functions.generate_value_with_same_type(
v['output_body_value'])
temp_value2 = functions.generate_value_with_same_type(
v['output_body_value'])
inputs.append(temp_value1)
body_graph.add_input_value(temp_value2)
if 'output_body_value' in v:
body_graph.add_output_value(v['output_body_value'])
output_value = functions.generate_value_with_same_type(
v['output_body_value'])
outputs.append(output_value)
if 'output_obj' in v:
obj = v['output_obj']
obj.revise(output_value)
field.get_attribute(name).revise(obj)
elif field.get_attribute(name).has_obj():
field.get_attribute(name).get_ref().revise(output_value)
else:
field.get_attribute(name).revise(values.ValueRef(output_value))
else:
temp_value1 = v['input_body_value']
temp_value2 = functions.generate_value_with_same_type(
v['input_body_value'])
body_graph.add_output_value(temp_value1)
outputs.append(temp_value2)
node = nodes.NodeListcomp(iter_value, inputs, body_graph, astc.lineno)
node.set_outputs(outputs)
graph.add_node(node)
return local_field.get_attribute(internal_list_id).get_ref()
def parse_instance(default_module,
name,
instance,
self_instance=None,
from_member=False,
root_graph: 'graphs.Graph' = None) -> "Object":
for converter in instance_converters:
ret = converter(default_module, instance)
if ret is not None:
return Object(ret)
#if inspect.ismethod(instance) or inspect.isfunction(instance) or isinstance(instance, np.ufunc):
if isinstance(instance, collections.Hashable):
if instance in function_converters.keys():
func = function_converters[instance]
return Object(func)
# 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 instance is inspect._empty:
return None
if inspect.ismethod(instance):
func = UserDefinedFunction(instance)
return Object(FuncValue(func, self_instance, default_module))
if inspect.isfunction(instance):
func = UserDefinedFunction(instance)
if from_member:
return Object(FuncValue(func, self_instance, default_module))
else:
return Object(FuncValue(func, None, default_module))
if inspect.isclass(instance):
func = functions.UserDefinedClassConstructorFunction(instance)
return Object(FuncValue(func, None, default_module))
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 Object(ret)
if isinstance(instance, dict):
keys = []
values = []
for key, value in instance.items():
keys.append(parse_instance(default_module, '', key))
values.append(parse_instance(default_module, '', value))
ret = DictValue(keys, values)
return Object(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 Object(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 Object(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 Object(ret)
if isinstance(instance, np.ndarray):
tensorValue = TensorValue(instance)
tensorValue.value = instance
tensorValue.shape = instance.shape
return Object(tensorValue)
if isinstance(instance, chainer.Variable):
tensorValue = TensorValue(instance.data)
tensorValue.value = instance.data
tensorValue.shape = instance.data.shape
return Object(tensorValue)
if instance == inspect._empty:
return Object(NoneValue())
if instance is None:
return Object(NoneValue())
if utils.is_disabled_module(instance):
return None
if inspect.ismodule(instance):
value = ModuleValue(instance)
return Object(value)
module = Object(ModuleValue(sys.modules[instance.__module__]))
model_inst = UserDefinedInstance(module, instance, None)
return Object(model_inst)
