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test_dynamicinput_convert.py 1.4 kB

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  1. # Tencent is pleased to support the open source community by making ncnn available.
  2. #
  3. # Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
  4. #
  5. # Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
  6. # in compliance with the License. You may obtain a copy of the License at
  7. #
  8. # https://opensource.org/licenses/BSD-3-Clause
  9. #
  10. # Unless required by applicable law or agreed to in writing, software distributed
  11. # under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
  12. # CONDITIONS OF ANY KIND, either express or implied. See the License for the
  13. # specific language governing permissions and limitations under the License.
  14. import pytest
  15. import pnnx
  16. import torch
  17. import torch.nn as nn
  18. import torch.nn.functional as F
  19. from packaging import version
  20. class Model(nn.Module):
  21. def __init__(self):
  22. super(Model, self).__init__()
  23. def forward(self, x):
  24. x = F.relu(x)
  25. return x
  26. def test_export():
  27. net = Model()
  28. net.eval()
  29. torch.manual_seed(0)
  30. x = torch.rand(1, 16)
  31. x1 = torch.rand(1, 128)
  32. a0 = net(x)
  33. a1 = net(x1)
  34. mod = torch.jit.trace(net, x)
  35. mod.save("test_F_relu_dconvert.pt")
  36. net2 = pnnx.convert("test_F_relu_dconvert.pt", x, x1)
  37. b0 = net2(x)
  38. b1 = net2(x1)
  39. assert torch.equal(a0, b0) and torch.equal(a1, b1)