def veval(op: 'nodes.BinOpType', left: 'values.Value', right: 'values.Value', lineprop : 'utils.LineProperty'):
if isinstance(left, values.ListValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.TupleValue):
return functions.generate_value_with_same_type(left)
return functions.generate_value_with_same_type(left)
def veval(op: 'nodes.BinOpType', left: 'values.Value', right: 'values.Value',
lineprop: 'utils.LineProperty'):
initialize_lazy()
if isinstance(left, values.ListValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.TupleValue):
return functions.generate_value_with_same_type(left)
if isinstance(right, values.NumberValue) or isinstance(
right, values.TensorValue):
if not isinstance(left, values.NumberValue) and not isinstance(
left, values.TensorValue):
utils.print_warning('Unestimated type is on left', lineprop)
left = values.NumberValue(0.0)
left_type = left.dtype
right_type = right.dtype
if not config.float_restrict:
if left_type == utils.dtype_float64:
left_type = utils.dtype_float32
if right_type == utils.dtype_float64:
right_type = utils.dtype_float32
if left_type is None:
left_type = np.array(0.0, np.float32).dtype
if right_type is None:
right_type = np.array(0.0, np.float32).dtype
result_type = None
for v in binop_type_table:
if v[0] == op and v[1] == left_type and v[2] == right_type:
result_type = v[3]
break
assert (result_type is not None)
if isinstance(right, values.TensorValue):
return functions.generate_value_with_type(right, type_=result_type)
else:
return functions.generate_value_with_type(left, type_=result_type)
return values.Value()
def veval_ast_aug_assign(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
assert (isinstance(astc.nast, gast.gast.AugAssign))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
target = veval_ast(astc.c(astc.nast.target), local_field, graph)
value = veval_ast(astc.c(astc.nast.value), local_field, graph)
target_value = try_get_value(target, 'aug_assign', lineprop)
value_value = try_get_value(value, 'aug_assign', lineprop)
binop = nodes.BinOpType.Unknown
if isinstance(astc.nast.op, gast.Add):
binop = nodes.BinOpType.Add
if isinstance(astc.nast.op, gast.Sub):
binop = nodes.BinOpType.Sub
node_aug_assign = nodes.NodeAugAssign(target_value, value_value, binop,
astc.lineno)
graph.add_node(node_aug_assign)
# TODO : estimate type
new_value = functions.generate_value_with_same_type(target_value)
node_aug_assign.set_outputs([new_value])
target.get_ref().revise(new_value)
def revise(self, value: 'Value', update_parent=True):
super().revise(value)
if not update_parent:
return
assert isinstance(self.parent_object, Object)
target_value = utils.try_get_value(self.parent_object,
'subscript_object', -1)
revision_value = utils.try_get_value(self.value, 'subscript_object',
-1)
subscript_value = utils.try_get_value(self.subscript,
'subscript_object', -1)
if isinstance(subscript_value, TupleValue):
# ex. x[1,2]
if subscript_value.has_constant_value():
subscripts = [
utils.try_get_value(x, 'subscript', -1)
for x in subscript_value.get_constant_value()
]
else:
if config.show_warnings:
assert False, "This subscript is not supported."
else:
# ex. x[1]
subscripts = [subscript_value]
node = nodes.NodeSetItem(target_value, subscripts, revision_value)
ret_value = functions.generate_value_with_same_type(target_value)
node.set_outputs([ret_value])
self.graph.add_node(node)
self.parent_object.revise(ret_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)
node = nodes.NodeCall(self, funcArgs, line)
if inst.in_container:
raise Exception('Invalid operation')
old_v = inst.get_value()
new_v = functions.generate_value_with_same_type(old_v)
# estimate a type contained
if old_v.has_constant_value():
new_v.internal_value = list(old_v.internal_value)
for v in funcArgs.inputs[1:]:
new_v.append(v)
# update value
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 veval(op: 'nodes.UnaryOpType', value: 'values.Value'):
if isinstance(value, values.NumberValue):
if value.internal_value is not None:
if op == nodes.UnaryOpType.UAdd:
return values.NumberValue(value.internal_value)
if op == nodes.UnaryOpType.USub:
return values.NumberValue(-value.internal_value)
else:
return functions.generate_value_with_same_type(value)
else:
return functions.generate_value_with_same_type(value)
if isinstance(value, values.BoolValue):
return functions.generate_value_with_same_type(value)
if op == nodes.UnaryOpType.Not and isinstance(value, values.ListValue):
return values.BoolValue(None)
return values.Value()
def vcall(self,
module: 'values.Field',
graph: 'graphs.Graph',
inst: 'values.Object',
args: 'functions.FunctionArgInput',
context: 'functions.VEvalContext' = None,
line=-1):
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
node = nodes.NodeCall(self, funcArgs, 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):
assert (inst is None)
funcArgs = self.args.merge_inputs(inst, args)
vargs = funcArgs.get_value().inputs
node = nodes.NodeCall(self, funcArgs, 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.ValueRef(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 veval_ast_subscript(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
'''
Ex. x[1], x[y,z]
'''
assert (isinstance(astc.nast, gast.gast.Subscript))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
def veval_with_default(nast, default_value):
if nast is None:
ret = values.NumberValue(default_value)
ret.name = '@SliceDefault'
return ret
obj = veval_ast(astc.c(nast), local_field, graph)
return try_get_value(obj, 'subscript', lineprop)
def get_slice_indices(slice):
if slice.lower is None and slice.upper is None and slice.step is None:
return []
indices = [
veval_with_default(slice.lower, 0),
veval_with_default(slice.upper, utils.slice_int_max)
]
if slice.step is not None:
indices.append(veval_with_default(slice.step, 1))
return indices
value = veval_ast(astc.c(astc.nast.value), local_field, graph)
value_value = try_get_value(value, 'subscript', lineprop)
if isinstance(astc.nast.slice, gast.gast.Index):
slice_ = veval_ast(astc.c(astc.nast.slice.value), local_field, graph)
slice_value = try_get_value(slice_, 'subscript', lineprop)
if isinstance(slice_value, values.TupleValue):
# ex. x[1,2]
if slice_value.has_constant_value():
values_ = [
try_get_value(x, 'subscript', lineprop)
for x in slice_value.get_constant_value()
]
node = nodes.NodeGetItem(value_value, values_, line=lineprop)
else:
if config.show_warnings:
print('This subscript is not supported. in L.{}'.format(
astc.lineno))
node = nodes.NodeInvalid(line=lineprop)
else:
# ex. x[1]
node = nodes.NodeGetItem(value_value, [slice_value])
if isinstance(value_value,
values.ListValue) and value_value.vtype != None:
ret_value = value_value.vtype()
ret_value.dtype = value_value.dtype
elif isinstance(value_value,
values.TupleValue) and value_value.vtype != None:
ret_value = value_value.vtype()
ret_value.dtype = value_value.dtype
else:
ret_value = values.UnknownValue()
node.set_outputs([ret_value])
graph.add_node(node)
return values.ValueRef(ret_value)
elif isinstance(astc.nast.slice, gast.gast.Slice):
indices = get_slice_indices(astc.nast.slice)
node = nodes.NodeSlice(value_value, indices, [len(indices)])
ret_value = functions.generate_value_with_same_type(value_value)
node.set_outputs([ret_value])
graph.add_node(node)
return values.ValueRef(ret_value)
elif isinstance(astc.nast.slice, gast.gast.ExtSlice):
indices = []
slice_specs = []
for dim in astc.nast.slice.dims:
if isinstance(dim, gast.gast.Index):
indices.append(
try_get_value(
veval_ast(astc.c(dim.value), local_field, graph),
'subscript', lineprop))
slice_specs.append(1)
elif isinstance(dim, gast.gast.Slice):
ni = get_slice_indices(dim)
indices.extend(ni)
slice_specs.append(len(ni))
else:
assert False, 'Unknown slice: %s in %s' % (dim, nast.slice)
node = nodes.NodeSlice(value_value, indices, slice_specs)
ret_value = functions.generate_value_with_same_type(value_value)
node.set_outputs([ret_value])
graph.add_node(node)
return values.ValueRef(ret_value)
return None
def veval_ast_if(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
assert (isinstance(astc.nast, gast.gast.If))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
# if condition
test = veval_ast(astc.c(astc.nast.test), local_field, graph)
test_value = try_get_value(test, 'if', lineprop)
id_str = str(utils.get_guid())
if_id = 'if_' + id_str
true_id = 'true_' + id_str
false_id = 'false_' + id_str
# True
values.push_history(true_id)
true_graph = Graph()
true_graph.root_graph = graph.root_graph
true_graph.name = 'True'
true_body = veval_ast(astc.c(astc.nast.body), local_field, true_graph)
true_value_inputs = values.get_inputs()
true_value_outputs = values.get_outputs()
values.pop_history()
# False
values.push_history(false_id)
false_graph = Graph()
false_graph.root_graph = graph.root_graph
false_graph.name = 'False'
false_body = veval_ast(astc.c(astc.nast.orelse), local_field, false_graph)
false_value_inputs = values.get_inputs()
false_value_outputs = values.get_outputs()
values.pop_history()
# generate pairs
value_pairs = {}
for v in true_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]['true_input_value'] = v.input_value
value_pairs[key]['true_input_body_value'] = v.value
value_pairs[key]['true_input_obj'] = v.obj
for v in true_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]['true_output_body_value'] = v.value
value_pairs[key]['true_output_obj'] = v.obj
for v in false_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]['false_input_value'] = v.input_value
value_pairs[key]['false_input_body_value'] = v.value
value_pairs[key]['false_input_obj'] = v.obj
for v in false_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]['false_output_body_value'] = v.value
value_pairs[key]['false_output_obj'] = v.obj
inputs = []
outputs = []
for k, v in value_pairs.items():
name = v['name']
field = v['field']
input_value = None
true_input_body_value = None
false_input_body_value = None
# search input value
if 'true_input_value' in v:
input_value = v['true_input_value']
elif 'false_input_value' in v:
input_value = v['false_input_value']
if input_value is not None:
if 'true_input_body_value' in v:
true_input_body_value = v['true_input_body_value']
else:
true_input_body_value = functions.generate_value_with_same_type(
input_value)
if 'false_input_body_value' in v:
false_input_body_value = v['false_input_body_value']
else:
false_input_body_value = functions.generate_value_with_same_type(
input_value)
true_output_body_value = None
false_output_body_value = None
output_value = None
# search output value
if 'true_output_body_value' in v:
true_output_body_value = v['true_output_body_value']
if 'false_output_body_value' in v:
false_output_body_value = v['false_output_body_value']
if true_output_body_value is not None or false_output_body_value is not None:
if true_output_body_value is None:
if true_input_body_value is not None:
# e.x. not changed
true_output_body_value = true_input_body_value
else:
# e.x. make a value in false statement
true_output_body_value = functions.generate_value_with_same_type(
false_output_body_value, is_dummy_value=True)
if false_output_body_value is None:
if false_input_body_value is not None:
# e.x. not changed
false_output_body_value = false_input_body_value
else:
# e.x. make a value in true statement
false_output_body_value = functions.generate_value_with_same_type(
true_output_body_value, is_dummy_value=True)
# check types between true and false
true_output_body_value_type = None
false_output_body_value_type = None
if true_output_body_value is not None and true_output_body_value.is_not_none_or_any_value(
):
true_output_body_value_type = true_output_body_value
if false_output_body_value is not None and false_output_body_value.is_not_none_or_any_value(
):
false_output_body_value_type = false_output_body_value
if true_output_body_value_type is not None and false_output_body_value_type is not None and type(
true_output_body_value_type) != type(
false_output_body_value_type):
utils.print_warning(
'Values with differenet type were generated {} between true ande false'
.format(k), lineprop)
if true_output_body_value_type != None:
output_value = functions.generate_value_with_same_type(
true_output_body_value_type)
elif false_output_body_value_type != None:
output_value = functions.generate_value_with_same_type(
false_output_body_value_type)
elif true_output_body_value is not None:
output_value = functions.generate_value_with_same_type(
true_output_body_value)
elif false_output_body_value is not None:
output_value = functions.generate_value_with_same_type(
false_output_body_value)
if input_value is not None:
inputs.append(input_value)
true_graph.add_input_value(true_input_body_value)
false_graph.add_input_value(false_input_body_value)
if output_value is not None:
outputs.append(output_value)
true_graph.add_output_value(true_output_body_value)
false_graph.add_output_value(false_output_body_value)
if 'true_output_obj' in v and not 'false_output_obj' in v:
obj = v['true_output_obj']
elif not 'true_output_obj' in v and 'false_output_obj' in v:
obj = v['false_output_obj']
elif 'true_output_obj' in v and 'false_output_obj' in v:
obj = None
else:
assert (False)
if obj is not None:
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))
node = nodes.NodeIf(test_value, inputs, true_graph, false_graph,
astc.lineno)
node.set_outputs(outputs)
graph.add_node(node)
return None
def veval_ast_for(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
'''
for target in iter:
...
'''
assert (isinstance(astc.nast, gast.gast.For))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
# for target in iter:
iter_ = veval_ast(astc.c(astc.nast.iter), local_field, graph)
input_iter_value = try_get_value(iter_, 'for', lineprop)
body_iter_value = functions.generate_value_with_same_type(
input_iter_value, suffix_type=functions.SuffixType.Input)
# get target name
target_name = ''
if isinstance(astc.nast.target, gast.gast.Name):
target_name = astc.nast.target.id
else:
if config.show_warnings:
print('This for is not supported. in L.{}'.format(astc.lineno))
return None
# unroll?
if isinstance(input_iter_value,
values.ListValue) and input_iter_value.has_constant_value(
) and input_iter_value.dtype is None:
return veval_ast_for_unroll(astc, target_name, input_iter_value,
local_field, graph)
for_guid = utils.get_guid()
for_id = 'for_' + str(for_guid)
body_id = 'body_' + str(for_guid)
values.push_history(for_id)
# body
body_graph = Graph()
body_graph.root_graph = graph.root_graph
body_graph.name = 'Body_' + str(for_guid)
# generate a node for input
node_input = nodes.NodeInput('input')
body_graph.add_node(node_input)
body_counter_value = values.NumberValue(None)
body_counter_value.dtype = np.array(0).dtype
body_counter_value.name = 'for_counter_' + str(for_guid)
body_cond_value = values.BoolValue(None)
body_cond_value.name = 'for_cond_' + str(for_guid)
# create a node to lookup a value from sequence
node_forgen = nodes.NodeForGenerator(body_counter_value, body_iter_value)
# generate iterator
target_ref = input_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(astc.lineno))
target_value = target_ref.get_value()
node_forgen.set_outputs([target_ref.get_value()])
target_attribute = local_field.get_attribute(target_name)
target_attribute.revise(target_ref)
body_graph.add_node(node_forgen)
# veval body
body = veval_ast(astc.c(astc.nast.body), local_field, body_graph)
value_inputs = values.get_inputs()
value_outputs = values.get_outputs()
break_attribute = local_field.get_attribute('#keepgoing')
if break_attribute.has_obj():
break_attribute_ref = break_attribute.get_ref()
break_attribute_value = break_attribute_ref.get_value()
else:
break_attribute_value = body_cond_value
values.pop_history()
inputs = []
outputs = []
node_input_outputs = []
# default input for subgraph's input
body_graph.add_input_value(body_counter_value)
body_graph.add_input_value(body_cond_value)
body_graph.add_input_value(body_iter_value)
# default output for subgraph's output
body_graph.add_output_value(break_attribute_value)
body_graph.add_output_value(body_iter_value)
# default output
outputs.append(functions.generate_value_with_same_type(input_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
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'],
is_dummy_value=True,
suffix_type=functions.SuffixType.Dummy)
temp_value2 = functions.generate_value_with_same_type(
v['output_body_value'], suffix_type=functions.SuffixType.Dummy)
inputs.append(temp_value1)
body_graph.add_input_value(temp_value2)
node_input_outputs.append(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.NodeFor(input_iter_value, inputs, body_graph, body_cond_value,
astc.lineno)
node.set_outputs(outputs)
node_input.set_outputs(node_input_outputs)
graph.add_node(node)
return None
def ret_same(funcArgs):
return functions.generate_value_with_same_type(funcArgs.keywords['x'].get_value())
def veval(op: 'nodes.BinOpType', left: 'values.Value', right: 'values.Value',
lineprop: 'utils.LineProperty'):
initialize_lazy()
if isinstance(left, values.ListValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.TupleValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.StrValue):
if not (isinstance(right, values.NumberValue) or isinstance(
right, values.StrValue) or isinstance(right, values.BoolValue)
or isinstance(right, values.TupleValue)):
assert False
if not (left.has_constant_value() or right.has_constant_value()):
assert False
if op == nodes.BinOpType.Add:
if not isinstance(right, values.StrValue):
assert False
return values.StrValue(left.internal_value + right.internal_value)
elif op == nodes.BinOpType.Mod:
right_internal_value = right.internal_value
if isinstance(right, values.TupleValue):
values_ = []
for ref in right_internal_value:
if not (isinstance(ref.get_value(), values.NumberValue)
or isinstance(ref.get_value(), values.StrValue)
or isinstance(ref.get_value(), values.BoolValue)):
assert False
if not ref.get_value().has_constant_value():
assert False
values_.append(ref.get_value())
right_internal_value = tuple(value.internal_value
for value in values_)
return values.StrValue(left.internal_value % right_internal_value)
return values.StrValue("")
if isinstance(right, values.NumberValue) or isinstance(
right, values.TensorValue):
if not isinstance(left, values.NumberValue) and not isinstance(
left, values.TensorValue):
utils.print_warning('Unestimated type is on left', lineprop)
left = values.NumberValue(0.0)
left_type = left.dtype
right_type = right.dtype
if not config.float_restrict:
if left_type == utils.dtype_float64:
left_type = utils.dtype_float32
if right_type == utils.dtype_float64:
right_type = utils.dtype_float32
if left_type is None:
left_type = np.array(0.0, np.float32).dtype
if right_type is None:
right_type = np.array(0.0, np.float32).dtype
result_type = None
for v in binop_type_table:
if v[0] == op and v[1] == left_type and v[2] == right_type:
result_type = v[3]
break
assert (result_type is not None)
if isinstance(right, values.TensorValue):
return functions.generate_value_with_type(right, type_=result_type)
else:
return functions.generate_value_with_type(left, type_=result_type)
return values.Value()