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1# Copyright 2021 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15""" test numpy ops """
16import pytest
17import numpy as np
18
19import mindspore.nn as nn
20from mindspore import Tensor, ms_function, context
21from mindspore.ops import operations as P
22from mindspore.ops import functional as F
23import mindspore.common.dtype as mstype
24import mindspore.common._monad as monad
25
26context.set_context(mode=context.GRAPH_MODE)
27
28# `add_func` is defined in current file.
29def add_func(x, y):
30    return x + y
31
32@ms_function
33def do_increment(i):
34    add_1 = F.partial(add_func, 1)
35    return add_1(i)
36
37def test_increment():
38    a = do_increment(9)
39    assert a == 10
40
41
42@ms_function
43def use_monad(x, y):
44    res = P.Mul()(x, y)
45    res = F.depend(res, monad.U)
46    return res
47
48def test_use_monad():
49    x = Tensor(1.0, mstype.float32)
50    y = Tensor(1.0, mstype.float32)
51    print(use_monad(x, y))
52
53
54class Net(nn.Cell):
55    def __init__(self):
56        super(Net, self).__init__()
57        self.x = Tensor([2, 3, 4])
58
59    def construct(self):
60        x_len = len(self.x)
61        for i in range(x_len):
62            print(i)
63        return x_len
64
65def test_builtins_len():
66    net = Net()
67    net()
68
69
70@ms_function
71def np_fallback_func():
72    array_x = tuple([2, 3, 4, 5])
73    np_x = np.array(array_x).astype(np.float32)
74    me_x = Tensor(np_x)
75    me_x = me_x + me_x
76    return me_x
77
78@pytest.mark.skip(reason='Not support graph fallback feature yet')
79def test_np_fallback_func():
80    print(np_fallback_func())
81
82
83@ms_function
84def div_mod_func(x, y):
85    a = divmod(x, y)
86    return Tensor(a)
87
88@pytest.mark.skip(reason='Not support graph fallback feature yet')
89def test_div_mod_func():
90    print(div_mod_func(8, 3))  # (2, 2)
91
92
93# NameError: name 'Tensor' is not defined.
94@ms_function
95def select_func(cond, x, y):
96    if isinstance(cond, (tuple, list)):
97        output = y
98    elif isinstance(cond, Tensor):
99        output = F.select(cond, x, y)
100    else:
101        output = x
102    return output
103
104def test_select_func():
105    cond = Tensor([True, False])
106    x = Tensor([2, 3], mstype.float32)
107    y = Tensor([1, 2], mstype.float32)
108    print(select_func(cond, x, y))
109
110
111# Not interpret 'Tensor'.
112@ms_function
113def select_func2(cond, x, y):
114    if isinstance(cond, (tuple, list)):
115        output = y
116    if isinstance(cond, Tensor):
117        output = F.select(cond, x, y)
118    else:
119        output = x
120    return output
121
122def test_select_func2():
123    cond = Tensor([True, False])
124    x = Tensor([2, 3], mstype.float32)
125    y = Tensor([1, 2], mstype.float32)
126    print(select_func2(cond, x, y))
127
128
129# NameError: name 'Tensor' is not defined.
130@ms_function
131def slice_func(a, b):
132    a[1:3, ::] = b
133    return a
134
135def test_slice_func():
136    a = Tensor(np.arange(60).reshape(3, 4, 5), dtype=mstype.float32)
137    b = Tensor([1], dtype=mstype.float32)
138    print(slice_func(a, b))
139