forked from mindspore-Ecosystem/mindspore
141 lines
3.3 KiB
Python
141 lines
3.3 KiB
Python
# 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 syntax for logic expression """
|
|
|
|
import numpy as np
|
|
|
|
import mindspore.nn as nn
|
|
from mindspore import context
|
|
from mindspore.common.tensor import Tensor
|
|
|
|
context.set_context(mode=context.GRAPH_MODE)
|
|
|
|
|
|
class MemberIn(nn.Cell):
|
|
def __init__(self):
|
|
super(MemberIn, self).__init__()
|
|
self.m = 1
|
|
|
|
def construct(self, x, y):
|
|
in_v = x in y
|
|
return in_v
|
|
|
|
|
|
class MemberInSpec(nn.Cell):
|
|
def __init__(self, x, y):
|
|
super(MemberInSpec, self).__init__()
|
|
self.x = x
|
|
self.y = y
|
|
|
|
|
|
def construct(self, x, y):
|
|
in_v = self.x in self.y
|
|
return in_v
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_int():
|
|
net = MemberIn()
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_list_int():
|
|
net = MemberIn()
|
|
ret = net(1, [1, 2])
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_list_str():
|
|
net = MemberInSpec(1, ["1", "2"])
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_list_combine():
|
|
net = MemberInSpec(1, ["1", 2])
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_tuple_int():
|
|
net = MemberIn()
|
|
ret = net(1, (1, 2))
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_tuple_str():
|
|
net = MemberInSpec(1, ("1", 2))
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_dict_str():
|
|
dict_y = {"1": 2, "2": 3}
|
|
net = MemberInSpec(1, dict_y)
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_str_in_dict_str():
|
|
dict_y = {"1": 2, "2": 3}
|
|
net = MemberInSpec("1", dict_y)
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_str_in_dict_combine():
|
|
dict_y = {"1": 2, 2: 3}
|
|
net = MemberInSpec("1", dict_y)
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_int_in_dict_combine():
|
|
dict_y = {"1": 2, 2: 3}
|
|
net = MemberInSpec(1, dict_y)
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_tensor_in_list_tensor():
|
|
net = MemberIn()
|
|
x = Tensor(np.ones([2, 2], np.int32))
|
|
y = Tensor(np.zeros([2, 2], np.int32))
|
|
ret = net(x, [x, y])
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_tensor_in_list_combine():
|
|
x = Tensor(np.ones([2, 2], np.int32))
|
|
y = Tensor(np.zeros([2, 2], np.int32))
|
|
net = MemberInSpec(x, [y, "a"])
|
|
ret = net(1, 2)
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_tensor_in_tuple_tensor():
|
|
net = MemberIn()
|
|
x = Tensor(np.ones([2, 2], np.int32))
|
|
y = Tensor(np.zeros([2, 2], np.int32))
|
|
ret = net(x, (x, y))
|
|
print(ret)
|
|
|
|
|
|
def test_ms_syntax_operator_tensor_in_tuple_combine():
|
|
x = Tensor(np.ones([2, 2], np.int32))
|
|
net = MemberInSpec(x, (x, "a"))
|
|
ret = net(1, 2)
|
|
print(ret)
|