Summary:
There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports:
```2to3 -f future -w caffe2```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033
Reviewed By: seemethere
Differential Revision: D23808648
Pulled By: bugra
fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
Summary:
Goal of this PR is to unify cuda and hip device types in caffe2 python front end.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14221
Differential Revision: D13148564
Pulled By: bddppq
fbshipit-source-id: ef9bd2c7d238200165f217097ac5727e686d887b
Summary: Still WIP, but works for the universal encoder. The other ones are currently broken.
Differential Revision: D6492786
fbshipit-source-id: 232e0058eb3a0c036de3adf0295db5efd624cca7
Summary:
Fix multilayer inference in Caffe2 example seq2seq code. (Rely on LSTMWithAttentionDecoder.apply rather than fixed state indices to determine stepwise decoder output.)
Also assorted updates to bring code in line with changes elsewhere in the codebase, and added unit tests which ensure that training and inference networks generate the same loss, which should make these problems much easier to identify in future.
Reviewed By: jamesr66a
Differential Revision: D5579803
fbshipit-source-id: 6e0f27340d981990ab8d0da58e63793222e7be87
Summary:
Implement dot attention as described in https://arxiv.org/abs/1508.04025
This saves the computation of weighted encoder outputs in `rnn_cell.py`
When the encoder and decoder dimensions are different, we apply an FC, which corresponds to the general case below Figure 2.
Refactored unit tests.
Reviewed By: jhcross
Differential Revision: D5486976
fbshipit-source-id: f9e9aea675b3b072fbe631bc004199b90a9d95cb
Summary: Several refinements to seq2seq example code, including support for multilayer LSTM.
Reviewed By: jamesr66a
Differential Revision: D5460372
fbshipit-source-id: d2eabf6aa9a5b5df7bbc341fd99c4e7d8322e717
Summary: These return views in Python 3 which would not do anything in a lot of usages currently present in Caffe2. This diff simply removes (almost) all usages of these two in Caffe2 and sub projects in favor of comprehensions which are also easier to read/understand
Reviewed By: akyrola
Differential Revision: D5142049
fbshipit-source-id: e800631d2df7d0823fed698cae46c486038007dc
