66 lines
1.8 KiB
Python
66 lines
1.8 KiB
Python
# 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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import numpy as np
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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context.set_context(device_target="GPU")
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.dense = nn.Dense(2048, 1001)
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def construct(self, x):
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return self.dense(x)
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class MultiLayerDense(nn.Cell):
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def __init__(self):
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super(MultiLayerDense, self).__init__()
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self.dense1 = nn.Dense(in_channels=256, out_channels=512)
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self.dense2 = nn.Dense(in_channels=512, out_channels=1024)
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def construct(self, x):
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x = self.dense1(x)
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x = self.dense2(x)
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return x
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def test_net():
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x = np.random.randn(32, 2048).astype(np.float32)
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net = Net()
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output = net(Tensor(x))
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print(x)
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print(output.asnumpy())
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def test_net_ND():
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x = np.random.randn(2, 332, 2048).astype(np.float32)
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net = Net()
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output = net(Tensor(x))
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print(x)
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print(output.asnumpy())
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def test_net_multilayer():
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x = np.random.randn(16, 32, 256).astype(np.float32)
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net = MultiLayerDense()
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output = net(Tensor(x))
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print(x)
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print(output.asnumpy())
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