Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21763
Custom __getattr__ functions can only raise AttributeError. This code throwed NotImplementedError which caused upstream troubles when hasattr() was called.
Differential Revision: D15815176
fbshipit-source-id: 0982e2382de4578d3fc05c5d2a63f624d6b4765e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21742
Add error message to NotImplementedError so we know which function it is about.
Reviewed By: bddppq
Differential Revision: D15806379
fbshipit-source-id: 14eab9d03aa5b44ab95c5caeadc0e01d51f22188
Summary:
This is the first of two changes that are supposed to improve how we handle RNNs in the JIT. They still get traced as `PythonOp`s, but now it will be much easier to actually expose them to the JIT as e.g. `aten::lstm`, and ignore the Python interpreter entirely. This needs some symbolic adjustments that will be part of a second PR.
Even when we fix symbolics, there will still be a bit of a problem with statefulness of the cuDNN API (we need a mutable cache for the dropout state, but our IR has no way of representing that).
zdevito ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10481
Reviewed By: ezyang
Differential Revision: D9341113
Pulled By: apaszke
fbshipit-source-id: 0ae30ead72a1b12044b7c12369d11e5ca8ec30b5
* add reduce=True arg to MarginRankingLoss
* make default margin arg match for legacy
* remove accidentally added test
* fix test
* fix native_functions.yaml alphabetical order
* implement CosineEmbeddingLoss as a native function and add reduce=True arg to it
* fix flake8
* address comments
* add reference function to tests
* fix flake8
This takes advantage of the broadcasting behavior of torch.matmul to
support inputs with more than two dimensions. The extra dimensions are
treated like part of the batch dimension, much like nn.Bottle in Lua
Torch.
There are a few related small performance changes:
* Addmm computes the gradient in column-major for inputs in
column-major format
* Variable.mm calls Addmm in-place with the desired output buffer
Here's the command I used to invoke autopep8 (in parallel!):
git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i
Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.
Also configures flake8 to match pep8's behavior.
Also configures TravisCI to check the whole project for lint.
