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auto-encoder's Issues

Is there a License for this Repository?

Thank you for this great repository. I am using the Resnet Autoencoder implementation code for my academic work, but I did not see any license or permission regarding academic usage. Could you please clarify this issue for me?

You could choose a license from the GitHub documentation page.
https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/licensing-a-repository

If you want it short and simple, many open-source repositories are using the MIT license (just a suggestion). https://choosealicense.com/licenses/mit/

Why fully connection in Decoder?

Hi, I find that there are three linear and bn at the beginning of Decoder (196-200 in resnet.py). Why adding these layers? Much Thanks.

decoder input shape

When running resnet.py, there is following error:

Traceback (most recent call last):
  File "/home/wentian/.pycharm_helpers/pydev/pydevd.py", line 1741, in <module>
    main()
  File "/home/wentian/.pycharm_helpers/pydev/pydevd.py", line 1735, in main
    globals = debugger.run(setup['file'], None, None, is_module)
  File "/home/wentian/.pycharm_helpers/pydev/pydevd.py", line 1135, in run
    pydev_imports.execfile(file, globals, locals)  # execute the script
  File "/home/wentian/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "/home/wentian/work/caption_t_r_2/src/test.py", line 359, in <module>
    pred = autoencoder(inputs)
  File "/home/wentian/library/miniconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/wentian/work/caption_t_r_2/src/test.py", line 262, in forward
    x = self.decoder(x)
  File "/home/wentian/library/miniconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/wentian/work/caption_t_r_2/src/test.py", line 213, in forward
    x = F.relu(self.bn3(x))
  File "/home/wentian/library/miniconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/wentian/library/miniconda3/lib/python3.6/site-packages/torch/nn/modules/batchnorm.py", line 45, in forward
    self._check_input_dim(input)
  File "/home/wentian/library/miniconda3/lib/python3.6/site-packages/torch/nn/modules/batchnorm.py", line 193, in _check_input_dim
    .format(input.dim()))
ValueError: expected 4D input (got 2D input)

At line 262, the shape of x is (11, 48).

Binary function?

I tried to understand why did you put this Binary layer between encoder and decoder. I mean are you trying to create a map of positive values? If this is the case, I am not sure if restricting them will work better than just freeing them up, also wouldn't using something like x[x > 0] or something be simpler?

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