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braceal / molecules

Machine learning for molecular dynamics.
MIT License
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ConvTranspose2d in PyTorch #13

Open braceal opened 4 years ago

braceal commented 4 years ago

TODO: revist output_padding. This code may not generalize to other examples. Needs testing. See https://github.com/pytorch/pytorch/pull/904/files could fix by storing list of output_sizes from the encoder conv layers and removing the decoder conv layers from the sequential and instead store a list of them. However, this approach has problems because output_sizes must be passed in the forward function, meaning that we can't use the nn.Sequential of conv layers i.e. the conv layers are stored as a list, not as member variables as is needed by nn.Module.

TODO referenced in molecules/ml/unsupervised/conv_vae/pytorch_cvae/cvae.py

braceal commented 4 years ago

Could use nn.ModuleList to make conv layers member vars. Then use the output_size api