def veval_ast_unary_op(astc: 'AstContext', local_field: 'values.Field', graph: 'graphs.Graph'): """ eval unary operation. Ex. -xx """ assert (isinstance(astc.nast, gast.gast.UnaryOp)) lineprop = utils.LineProperty(astc.lineno) unaryop = nodes.UnaryOpType.Unknown if isinstance(astc.nast.op, gast.UAdd): unaryop = nodes.UnaryOpType.UAdd if isinstance(astc.nast.op, gast.USub): unaryop = nodes.UnaryOpType.USub if isinstance(astc.nast.op, gast.Not): unaryop = nodes.UnaryOpType.Not operand = veval_ast(astc.c(astc.nast.operand), local_field, graph) operand_value = try_get_value(operand, 'unary', lineprop) node = nodes.NodeUnaryOp(operand_value, unaryop) ret_value = veval_unary.veval(unaryop, operand_value) node.set_outputs([ret_value]) graph.add_node(node) return values.ValueRef(ret_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) 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) 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 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 dtype_value is not None and not isinstance(dtype_value, values.NoneValue): # TODO : make better dtype = utils.int_2_numpy_type(dtype_value.internal_value) 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.ValueRef(value)
def veval_ast_bin_op(astc: 'AstContext', local_field: 'values.Field', graph: 'Graph'): """ eval binary operation. Ex. a + b, b // c, etc """ assert (isinstance(astc.nast, gast.gast.BinOp)) lineprop = utils.LineProperty(astc.lineno) left = veval_ast(astc.c(astc.nast.left), local_field, graph) right = veval_ast(astc.c(astc.nast.right), local_field, graph) left_value = try_get_value(left, 'compare', lineprop) right_value = try_get_value(right, 'compare', 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 if isinstance(astc.nast.op, gast.Mult): binop = nodes.BinOpType.Mul node_bin_op = nodes.NodeBinOp(left_value, right_value, binop, astc.lineno) ret_value = veval_bin.veval(binop, left_value, right_value) node_bin_op.set_outputs([ret_value]) graph.add_node(node_bin_op) return values.ValueRef(ret_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 return_value_or_ref(obj: 'value.Object'): if isinstance(obj.get_value(), values.NumberValue): return values.ValueRef(obj.get_value()) if isinstance(obj.get_value(), values.StrValue): return values.ValueRef(obj.get_value()) if isinstance(obj.get_value(), values.BoolValue): return values.ValueRef(obj.get_value()) if isinstance(obj.get_value(), values.NoneValue): return values.ValueRef(obj.get_value()) if isinstance(obj.get_value(), values.TupleValue): return values.ValueRef(obj.get_value()) return obj
def apply_to_object(self, obj: 'values.ValueRef'): super().apply_to_object(obj) children = values.ValueRef( values.FuncValue(ChainerChainListChildrenFunction(self), obj)) obj.get_field().get_attribute('children').revise(children) forward_func = obj.try_get_and_store_obj('forward', None) if forward_func is not None: obj.get_field().get_attribute('__call__').revise(forward_func) obj.get_field().get_attribute('forward').revise(forward_func)
def veval_ast_name_constant(astc: 'AstContext', local_field: 'values.Field', graph: 'Graph'): ''' Ex. True ''' assert (isinstance(astc.nast, gast.gast.NameConstant)) lineprop = utils.LineProperty(astc.lineno) ret = None if astc.nast.value == True: ret = values.ValueRef(values.BoolValue(True)) if astc.nast.value == False: ret = values.ValueRef(values.BoolValue(False)) if astc.nast.value is None: ret = values.ValueRef(values.NoneValue()) name = values.create_ref_value_name_with_constant(ret) ret.name = name ret.get_value().name = name return ret
def add_arg(self, name, value): if isinstance(value, values.Value): value = values.ValueRef(value) assert not (name in self.args.keys()) fa = FunctionArg(name, value) self.args_list.append(fa) self.args[fa.name] = fa
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 add_chainer_funtion(name:'str', func, ret_value_func = None): if ret_value_func is None: f = values.FuncValue( functions_builtin.ChainerFunction(func), None) else: f = values.FuncValue( functions_builtin.ChainerFunction(func, ret_value_func=ret_value_func), None) f_dict.get_field().get_attribute(name).revise(values.ValueRef(f)) values.function_converters[func] = f
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 value = values.ListValue(self.owner.children) return values.ValueRef(value)
def veval_ast_str(astc: 'AstContext', local_field: 'values.Field', graph: 'Graph'): ''' Ex. "str" ''' assert (isinstance(astc.nast, gast.gast.Str)) lineprop = utils.LineProperty(astc.lineno) value = values.StrValue(astc.nast.s) ret = values.ValueRef(value) name = values.create_ref_value_name_with_constant(ret) ret.name = name ret.get_value().name = name return ret
def vcall(self, module: 'Field', graph: 'Graph', inst: 'values.ValueRef', args: 'functions.FunctionArgInput', line=-1): node = nodes.NodeLen( args.inputs[0].get_value(), # TODO: Check this. line) graph.add_node(node) value = values.NumberValue(None) 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: '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.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: '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 veval_ast_compare(astc: 'AstContext', local_field: 'values.Field', graph: 'Graph'): """ eval Compare. Ex. a >= b, a != b, a is b, etc """ assert (isinstance(astc.nast, gast.gast.Compare)) lineprop = utils.LineProperty(astc.lineno) left = veval_ast(astc.c(astc.nast.left), local_field, graph) right = veval_ast(astc.c(astc.nast.comparators[0]), local_field, graph) left_value = try_get_value(left, 'compare', lineprop) right_value = try_get_value(right, 'compare', lineprop) compare = nodes.CompareType.unknown if isinstance(astc.nast.ops[0], gast.Eq): compare = nodes.CompareType.Eq if isinstance(astc.nast.ops[0], gast.NotEq): compare = nodes.CompareType.NotEq if isinstance(astc.nast.ops[0], gast.Is): compare = nodes.CompareType.Is if isinstance(astc.nast.ops[0], gast.IsNot): compare = nodes.CompareType.IsNot if isinstance(astc.nast.ops[0], gast.Gt): compare = nodes.CompareType.Gt if isinstance(astc.nast.ops[0], gast.GtE): compare = nodes.CompareType.GtE if isinstance(astc.nast.ops[0], gast.Lt): compare = nodes.CompareType.Lt if isinstance(astc.nast.ops[0], gast.LtE): compare = nodes.CompareType.LtE node_compare = nodes.NodeCompare(left_value, right_value, compare, astc.lineno) ret_value = values.BoolValue(None) ret_value.name = '@{}'.format(lineprop) node_compare.set_outputs([ret_value]) graph.add_node(node_compare) return values.ValueRef(ret_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) 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 vcall(self, module: 'values.Field', graph: 'graphs.Graph', inst: 'values.ValueRef', args: 'FunctionArgInput', line=-1): ret = values.ValueRef( values.UserDefinedInstance(module, None, self.classinfo)) inst = ret func_field = values.Field() func_field.set_module(module) # add args funcArgs = self.args.merge_inputs(inst, args) for k, v in funcArgs.keywords.items(): func_field.get_field().get_attribute(k).revise(v) astc = vevaluator.AstContext(self.ast.body, self.lineno - 1) vevaluator.veval_ast(astc, func_field, graph) return ret
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) # 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() 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(body_cond_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 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 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, astc.lineno) node.set_outputs(outputs) node_input.set_outputs(node_input_outputs) graph.add_node(node) return None
def apply_to_object(self, obj: 'values.ValueRef'): self.func = values.ValueRef( values.FuncValue(ChainerLinkFunction(self), obj)) obj.get_field().get_attribute('forward').revise(self.func)
def __init__(self): super().__init__() self.name = 'list' self.args.add_arg('value', values.ValueRef(values.NoneValue()))
def convert_model(model: 'chainer.Chain', args=[]): # reset values values.reset_field_and_attributes() utils.reset_guid() values.instance_converters.clear() def instance_converter(m, i): if links_builtin.is_builtin_chainer_link(i): return links_builtin.ChainerLinkInstance(m, i) return None values.instance_converters.append(instance_converter) # generate default module default_module = values.Module(sys.modules[model.__module__]) # chainer chainer_module_name = get_module_name( C, default_module.internal_module) if chainer_module_name != '': c_dict = values.ValueRef(values.ModuleValue()) # a substitute of Variable c_variable = values.FuncValue(functions_ndarray.NDArrayFunction(), None) c_dict.get_field().get_attribute('Variable').revise(values.ValueRef(c_variable)) default_module.set_default_value(chainer_module_name, c_dict) # chainer.functions chainer_functions_module_name = get_module_name( F, default_module.internal_module) if chainer_functions_module_name != '': f_dict = values.ValueRef(values.ModuleValue()) def add_chainer_funtion(name:'str', func, ret_value_func = None): if ret_value_func is None: f = values.FuncValue( functions_builtin.ChainerFunction(func), None) else: f = values.FuncValue( functions_builtin.ChainerFunction(func, ret_value_func=ret_value_func), None) f_dict.get_field().get_attribute(name).revise(values.ValueRef(f)) values.function_converters[func] = f def ret_tuple(): return values.TupleValue() add_chainer_funtion('relu', F.relu) add_chainer_funtion('softmax', F.softmax) add_chainer_funtion('softmax_cross_entropy', F.softmax_cross_entropy) add_chainer_funtion('pad_sequence', F.pad_sequence) add_chainer_funtion('average_pooling_2d', F.average_pooling_2d) add_chainer_funtion('unpooling_2d', F.unpooling_2d) add_chainer_funtion('reshape', F.reshape) add_chainer_funtion('split_axis', F.split_axis, ret_value_func=ret_tuple) add_chainer_funtion('reshape', F.reshape) add_chainer_funtion('swapaxes', F.swapaxes) add_chainer_funtion('dropout', F.dropout) add_chainer_funtion('concat', F.concat) add_chainer_funtion('matmul', F.matmul) add_chainer_funtion('max_pooling_2d', F.max_pooling_2d) add_chainer_funtion('resize_images', F.resize_images) if int(chainer.__version__[0]) >= 6: add_chainer_funtion('roi_max_pooling_2d', F.roi_max_pooling_2d) add_chainer_funtion('roi_average_pooling_2d', F.roi_average_pooling_2d) add_chainer_funtion('roi_max_align_2d', F.roi_max_align_2d) add_chainer_funtion('roi_average_align_2d', F.roi_average_align_2d) default_module.set_default_value(chainer_functions_module_name, f_dict) # numpy numpy_module_name = get_module_name(np, default_module.internal_module) if numpy_module_name != '': f_dict = values.ValueRef(values.ModuleValue()) f_array = values.FuncValue(functions_ndarray.NDArrayFunction(), None) f_dict.get_field().get_attribute('array').revise(values.ValueRef(f_array)) f_zeros = values.FuncValue(functions_ndarray.NDArrayZerosFunction(), None) f_dict.get_field().get_attribute('zeros').revise(values.ValueRef(f_zeros)) f_full = values.FuncValue(functions_ndarray.NDArrayFullFunction(), None) f_dict.get_field().get_attribute('full').revise(values.ValueRef(f_full)) f_ceil = values.FuncValue(functions_ndarray.NDArrayCeilFunction(), None) f_dict.get_field().get_attribute('ceil').revise(values.ValueRef(f_ceil)) f_dict.get_field().get_attribute('int32').revise( values.ValueRef(values.NumberValue(utils.numpy_type_2_int(np.int32)))) f_dict.get_field().get_attribute('float32').revise( values.ValueRef(values.NumberValue(utils.numpy_type_2_int(np.float32)))) default_module.set_default_value(numpy_module_name, f_dict) m_range = values.FuncValue(functions_builtin.RangeFunction(), None) default_module.set_default_value('range', values.ValueRef(m_range)) m_list = values.FuncValue(functions_builtin.ListFunction(), None) default_module.set_default_value('list', values.ValueRef(m_list)) model_inst = values.parse_instance(default_module, '', model) forward_func = model_inst.try_get_and_store_obj('forward') # convert args finput = functions.FunctionArgInput() value_args = [] ind = 0 node_input = nodes.NodeInput('input') for arg in args: varg = values.parse_instance(default_module, '', arg, None, True) varg.name = 'in_' + str(ind) varg.get_value().name = 'in_' + str(ind) # make value unknown # if isinstance(varg.get_value(), values.TupleValue): # for i in range(len(varg.get_value().internal_value)): # varg.get_value().internal_value[i] = None # else: varg.get_value().internal_value = None finput.inputs.append(varg) value_args.append(varg.get_value()) ind += 1 node_input.set_outputs(value_args) graph = Graph() graph.add_node(node_input) forward_func_value = forward_func.get_value() ret = forward_func_value.func.vcall( default_module, graph, forward_func_value.obj, finput) assert(ret is None or isinstance(ret, values.ValueRef)) def try_get_value(value) -> 'values.Value': if isinstance(value, values.Value): return value if isinstance(value, values.ValueRef): return value.get_value() if isinstance(value, values.Attribute): return value.get_ref().get_value() if ret is None or isinstance(ret, values.NoneValue): if config.show_warnings: print('Failed to compile. output is None.') return (value_args, None, graph) ret_ = [] if isinstance(ret.get_value(), values.TupleValue): if ret.get_value().internal_value is not None: for v in ret.get_value().internal_value: assert(v is not None) ret_.append(try_get_value(v)) else: ret_ = [ret.get_value()] elif isinstance(ret, list): ret_ = [r.get_value() for r in ret] else: ret_ = [ret.get_value()] for v in value_args: graph.add_input_value(v) for v in ret_: graph.add_output_value(v) return (value_args, ret_, graph)
def veval_ast_if(astc: 'AstContext', local_field: 'values.Field', graph: 'Graph'): assert (isinstance(astc.nast, gast.gast.If)) lineprop = utils.LineProperty(astc.lineno) # 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' 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' 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 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 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 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 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 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 if 'true_output_body_value' in v: true_output_body_value = v['true_output_body_value'] else: true_output_body_value = true_input_body_value if 'false_output_body_value' in v: false_output_body_value = v['false_output_body_value'] else: false_output_body_value = false_input_body_value # TODO check types between true and false if true_output_body_value is not None or false_output_body_value is not None: output_value = functions.generate_value_with_same_type( true_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 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_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) 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(astc.lineno)) target_value = target_ref.get_value() node_forgen.set_outputs([target_ref.get_value()]) local_field.get_attribute(target_name, from_module=False).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( local_field.module, 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 # 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 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) 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]) ret_value = values.Value() 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