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361 lines
8.8 KiB
361 lines
8.8 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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""" test control ops """
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import numpy as np
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import mindspore as ms
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from mindspore import nn
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from mindspore import Tensor
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from mindspore import context
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE)
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def cond_data_test(x_init, y_init):
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class Net(nn.Cell):
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def __init__(self):
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""""""
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super(Net, self).__init__()
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self.square = P.Square()
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self.add = P.TensorAdd()
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self.value = Tensor(np.full((1), 3, dtype=np.float32))
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self.switch = P.GeSwitch()
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self.merge = P.Merge()
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self.less = P.Less()
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def construct(self, x, y):
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cond = self.less(x, y)
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st1, sf1 = self.switch(x, cond)
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st2, sf2 = self.switch(y, cond)
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add_ret = self.add(st1, st2)
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st3, sf3 = self.switch(self.value, cond)
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sq_ret = self.square(sf3)
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ret = self.merge((add_ret, sq_ret))
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return ret[0]
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x = Tensor(x_init, dtype=ms.float32)
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y = Tensor(y_init, dtype=ms.float32)
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net = Net()
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output = net(x, y)
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return output
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def test_cond_data_true():
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output = cond_data_test(3, 8)
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print("test_cond_data_true:", output)
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def test_cond_data_false():
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output = cond_data_test(8, 3)
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print("test_cond_data_false:", output)
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def if_compile_test(x_init, y_init):
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class Net(nn.Cell):
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def __init__(self):
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""""""
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super(Net, self).__init__()
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self.square = P.Square()
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self.add = P.TensorAdd()
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self.value = Tensor(3, dtype=ms.float32)
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self.switch = P.GeSwitch()
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self.merge = P.Merge()
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self.less = P.Less()
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def construct(self, x, y):
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cond = self.less(x, y)
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ret = self.value
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if cond:
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ret = self.add(x, ret)
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ret = self.add(y, ret)
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else:
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ret = self.square(self.value)
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return ret
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x = Tensor(x_init, dtype=ms.float32)
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y = Tensor(y_init, dtype=ms.float32)
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net = Net()
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output = net(x, y)
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return output
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def test_if_none():
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class Net(nn.Cell):
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def __init__(self, z: None):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = None
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net = Net(z)
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assert net(x, y) == y
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def test_if_str_is_not_none_right():
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class Net(nn.Cell):
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def __init__(self, z: str):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z == None:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = "ok"
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net = Net(z)
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assert net(x, y) == y
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def test_if_str_is_not_none_left():
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class Net(nn.Cell):
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def __init__(self, z: str):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if None == self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = "ok"
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net = Net(z)
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assert net(x, y) == y
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def test_if_none_equal_none():
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class Net(nn.Cell):
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def __init__(self, z: None):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z == None:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = None
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net = Net(z)
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assert net(x, y) == x
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def test_if_str_is_null():
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class Net(nn.Cell):
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def __init__(self, z: str):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = ""
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net = Net(z)
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assert net(x, y) == y
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def test_if_str_is_true():
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class Net(nn.Cell):
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def __init__(self, z: str):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 9, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = "ok"
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net = Net(z)
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assert net(x, y) == x
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def test_if_str_equal():
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class Net(nn.Cell):
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def __init__(self, z: str):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z == "ok":
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = "ok"
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net = Net(z)
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assert net(x, y) == x
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def test_if_tuple_is_null():
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class Net(nn.Cell):
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def __init__(self, z: tuple):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = ()
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net = Net(z)
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assert net(x, y) == y
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def test_if_tuple_is_not_null():
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class Net(nn.Cell):
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def __init__(self, z: tuple):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = (1, 2, 3)
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net = Net(z)
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assert net(x, y) == x
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def test_if_dict_is_null():
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class Net(nn.Cell):
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def __init__(self, z: dict):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = {}
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net = Net(z)
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assert net(x, y) == y
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def test_if_dict_is_not_null():
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class Net(nn.Cell):
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def __init__(self, z: dict):
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""""""
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super(Net, self).__init__()
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self.z = z
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def construct(self, x, y):
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if self.z:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = {"one": 1, "two": 2}
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net = Net(z)
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assert net(x, y) == x
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def test_if_else_assign():
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class Net(nn.Cell):
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def __init__(self, m: list):
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""""""
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super(Net, self).__init__()
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self.m = m
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self.n = [4, 5, 6]
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def construct(self, x, y):
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exp_1 = self.m if self.m else self.n
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exp_2 = self.m if exp_1 == self.n else self.n
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if exp_2 == self.m:
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if self.m:
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ret = x
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else:
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ret = y
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else:
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if self.m:
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ret = x
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else:
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ret = y
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return ret
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x = Tensor(np.ones([6, 8, 10], np.int32))
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y = Tensor(np.zeros([3, 4, 5], np.int32))
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z = [1, 2]
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net = Net(z)
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assert net(x, y) == x
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def test_if_compile_true():
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output = if_compile_test(3, 8)
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print("test_if_compile_true:", output)
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def test_if_compile_false():
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output = if_compile_test(8, 3)
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print("test_if_compile_false:", output)
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