def generate_copied_value(value: 'values.Value'): assert(isinstance(value, values.Value)) if isinstance(value, values.NumberValue): copied = values.NumberValue(value.internal_value) copied.dtype = value.dtype return copied if isinstance(value, values.TensorValue): copied = values.TensorValue() copied.value = value.value copied.shape = value.shape copied.dtype = value.dtype return copied if isinstance(value, values.ListValue): copied = values.ListValue() copied.dtype = value.dtype copied.vtype = value.vtype if value.internal_value is not None: copied.internal_value = value.internal_value.copy() return copied if isinstance(value, values.NoneValue): copied = values.NoneValue() return copied if isinstance(value, values.BoolValue): copied = values.BoolValue(value.internal_value) return copied if isinstance(value, values.StrValue): copied = values.StrValue(value.internal_value) return copied if isinstance(value, values.RangeValue): copied = values.RangeValue() return copied if isinstance(value, values.TupleValue): if value.internal_value is not None: copied = values.TupleValue(value.internal_value.copy()) else: copied = values.TupleValue(value.internal_value) copied.dtype = value.dtype copied.vtype = value.vtype return copied if config.show_warnings: print('Unknown type {} is copied'.format(value)) return values.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.TupleValue() value.name = '@F.{}.{}'.format(line, self.name) node.set_outputs([value]) graph.add_node(node) return values.ValueRef(value)
def make_attribute(value): if isinstance(value, list): for i in range(len(value)): value[i] = make_attribute(value[i]) if isinstance(value, functions.FunctionArgValueInput): converted = {} ret = functions.FunctionArgValueInput() for v in value.inputs: converted_v = make_attribute(v) ret.inputs.append(converted_v) converted[v] = converted_v keywords_ = {} for k, v in value.keywords.items(): if v in converted.keys(): keywords_[k] = converted[v] else: keywords_[k] = make_attribute(v) ret.keywords = keywords_ return ret if isinstance(value, values.TupleValue) and value.internal_value is not None: vs = [] for v in value.internal_value: if isinstance(v, values.Object): v = v.get_value() vs.append(v) ret = values.TupleValue(vs) ret.name = value.name ret.generator = value.generator return ret if isinstance(value, values.Object): return value.get_value() return value
def vcall(self, module: 'values.Field', graph: 'graphs.Graph', inst: 'values.Object', args: 'functions.FunctionArgInput', option: 'vevaluator.VEvalContext' = None, line=-1): chainer_link = chainer_links[type(self.owner.inst)] if len(self.args.args_list) == 0: if chainer_link.args is None: self.args.add_arg('self', None) self.args.add_arg('x', None) else: for arg in chainer_link.args: self.args.add_arg(arg[0], arg[1]) vargs = self.args.merge_inputs(inst, args) node = nodes.NodeCall(self, vargs, line) graph.add_node(node) if chainer_link.get_ret is not None: ret = chainer_link.get_ret() node.set_outputs(ret) return values.Object( values.TupleValue([values.Object(v) for v in ret])) else: 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.Object(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 generate_value_with_same_type(value: 'values.Value', is_dummy_value = False, suffix_type = SuffixType.Unknown): assert(isinstance(value, values.Value)) ret = None if isinstance(value, values.TensorValue): ret = values.TensorValue() ret.shape = value.shape ret.dtype = value.dtype elif isinstance(value, values.NumberValue): dtype = None if value.internal_value is None: dtype = value.dtype elif isinstance(value.internal_value, int): dtype = np.array(value.internal_value).dtype elif isinstance(value.internal_value, float): dtype = np.array(value.internal_value).dtype ret = values.NumberValue(None) ret.dtype = dtype elif isinstance(value, values.StrValue): ret = values.StrValue(None) elif isinstance(value, values.BoolValue): ret = values.BoolValue(None) elif isinstance(value, values.ListValue): ret = values.ListValue(None) ret.dtype = value.dtype ret.vtype = value.vtype elif isinstance(value, values.NoneValue): ret = values.NoneValue() elif isinstance(value, values.TupleValue): ret = values.TupleValue() ret.dtype = value.dtype ret.vtype = value.vtype elif isinstance(value, values.RangeValue): ret = values.RangeValue() elif isinstance(value, values.UnknownValue): ret = values.UnknownValue() elif ret is None and isinstance(value, values.Value): ret = values.Value() else: assert(False) assert(ret is not None) ret.is_dummy_value = is_dummy_value if suffix_type == SuffixType.Unknown: ret.name = value.name + '_st' elif suffix_type == SuffixType.Unused: ret.name = value.name + '_unused' elif suffix_type == SuffixType.Dummy: ret.name = value.name + '_dummy' elif suffix_type == SuffixType.Input: ret.name = value.name + '_in' else: assert(False) return ret
def ret_tuple(funcArgs = None): ret = values.TupleValue() ret.vtype = values.TensorValue return ret
def ret_tuple(): ret = values.TupleValue() ret.vtype = values.TensorValue return ret