# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """ test instance""" import numpy as np import pytest import mindspore.nn as nn from mindspore import Tensor, Parameter from mindspore import context context.set_context(mode=context.GRAPH_MODE) def test_isinstance(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.int_member = 1 self.float_member = 1.0 self.bool_member = True self.string_member = "abcd" self.tensor_member = Tensor(np.arange(4)) self.tuple_member = (1, 1.0, True, "abcd", self.tensor_member) self.list_member = list(self.tuple_member) self.weight = Parameter(1.0) self.empty_list = [] self.dict_member = {"x": Tensor(np.arange(4)), "y": Tensor(np.arange(5))} self.empty_dict = {} def construct(self, x, y): is_int = isinstance(self.int_member, int) is_float = isinstance(self.float_member, float) is_bool = isinstance(self.bool_member, bool) bool_is_int = isinstance(self.bool_member, (((int,)), float)) is_string = isinstance(self.string_member, str) is_parameter = isinstance(self.weight, Parameter) parameter_is_tensor = isinstance(self.weight, ((Tensor, float), int)) is_tensor_const = isinstance(self.tensor_member, Tensor) is_tensor_var = isinstance(x, Tensor) is_tuple_const = isinstance(self.tuple_member, tuple) is_tuple_var = isinstance((x, 1, 1.0, y), tuple) is_list_const = isinstance(self.list_member, list) is_list_var = isinstance([x, 1, 1.0, y], list) is_dict_const = isinstance(self.dict_member, dict) is_dict_var = isinstance({"x": x, "y": y}, dict) is_empty_dic = isinstance(self.empty_dict, dict) is_list_or_tensor = isinstance([x, y], (Tensor, list)) is_int_or_float_or_tensor_or_tuple = isinstance(x, (Tensor, tuple, int, float)) float_is_int = isinstance(self.float_member, int) bool_is_string = isinstance(self.bool_member, str) tensor_is_tuple = isinstance(x, tuple) tuple_is_list = isinstance(self.tuple_member, list) is_empty_list = isinstance(self.empty_list, list) return is_int, is_float, is_bool, bool_is_int, is_string, is_parameter, \ parameter_is_tensor, is_tensor_const, is_tensor_var, \ is_tuple_const, is_tuple_var, is_list_const, is_list_var, is_empty_list, \ is_dict_const, is_dict_var, is_empty_dic, \ is_int_or_float_or_tensor_or_tuple, is_list_or_tensor, \ float_is_int, bool_is_string, tensor_is_tuple, tuple_is_list net = Net() x = Tensor(np.arange(4)) y = Tensor(np.arange(5)) assert net(x, y) == (True,) * 19 + (False,) * 4 def test_isinstance_not_supported(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = (11, 22, 33, 44) def construct(self): return isinstance(self.value, None) net = Net() with pytest.raises(TypeError) as err: net() assert "The second arg of 'isinstance' must be a type or a tuple of types, but got a NoneType" in str(err.value) def test_isinstance_second_arg_is_list(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = (11, 22, 33, 44) def construct(self): return isinstance(self.value, [tuple, int, float]) net = Net() with pytest.raises(TypeError) as err: net() assert "The second arg of 'isinstance' must be a type or a tuple of types, but got a list" in str(err.value)