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https://github.com/Tencent/ncnn.git
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41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
# Tencent is pleased to support the open source community by making ncnn available.
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#
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# Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
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#
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# Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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# in compliance with the License. You may obtain a copy of the License at
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#
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# https://opensource.org/licenses/BSD-3-Clause
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#
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# Unless required by applicable law or agreed to in writing, software distributed
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# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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# CONDITIONS OF ANY KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations under the License.
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import pnnx
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import torch
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import torch.nn as nn
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import torch.nn.functional as F
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class Model(nn.Module):
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def __init__(self):
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super(Model, self).__init__()
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def forward(self, x, y, z, w):
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x = F.relu(x)
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y = F.relu(y)
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z = F.relu(z)
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w = F.relu(w)
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return x, y, z, w
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if __name__ == "__main__":
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net = Model()
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torch.manual_seed(0)
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x = torch.rand(1, 16)
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y = torch.rand(12, 2, 16)
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z = torch.rand(1, 3, 12, 16)
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w = torch.rand(1, 5, 7, 9, 11)
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pnnx.export(net, "test_F_relu", (x, y, z, w)) |