• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1# Copyright 2019 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# ============================================================================
15import numpy as np
16
17import mindspore.context as context
18import mindspore.nn as nn
19from mindspore import Tensor
20from mindspore.common.api import ms_function
21
22context.set_context(device_target="Ascend")
23
24
25class Net(nn.Cell):
26    def __init__(self):
27        super(Net, self).__init__()
28        self.dense = nn.Dense(2048, 1001)
29
30    @ms_function
31    def construct(self, x):
32        return self.dense(x)
33
34class MultiLayerDense(nn.Cell):
35    def __init__(self):
36        super(MultiLayerDense, self).__init__()
37        self.dense1 = nn.Dense(in_channels=256, out_channels=512)
38        self.dense2 = nn.Dense(in_channels=512, out_channels=1024)
39
40    @ms_function
41    def construct(self, x):
42        x = self.dense1(x)
43        x = self.dense2(x)
44        return x
45
46
47def test_net():
48    x = np.random.randn(32, 2048).astype(np.float32)
49    net = Net()
50    output = net(Tensor(x))
51    print(x)
52    print(output.asnumpy())
53
54
55def test_net_ND():
56    x = np.random.randn(2, 332, 2048).astype(np.float32)
57    net = Net()
58    output = net(Tensor(x))
59    print(x)
60    print(output.asnumpy())
61
62
63def test_net_multilayer():
64    x = np.random.randn(16, 32, 256).astype(np.float32)
65    net = MultiLayerDense()
66    output = net(Tensor(x))
67    print(x)
68    print(output.asnumpy())
69