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:
Get higher order interaction of embeddings, similar to cross net but applied in the embedding level.
Formula:
e_(l+1,i) = element_wise_mul[e_(0,i), \sum_i(e_(l,i) * w_(l,i))] + e_(l,i) + b
where l means the l-th layer of this higher order net, i means the i-th embedding in the list.
Finally, concat all the embeddings in the last layer, or concat the sum of each embedding, and attach to the output blob of dot processor.
Differential Revision: D6244001
fbshipit-source-id: 96292914158347b79fc1299694d65605999b55e8
Summary:
The output shape info is incorrect, e.g. if we have 4 embeddings with dim size 32, the actual shape is (4, 32),
but the previous implementation in concat layer will give us (128, 1). This bug doesn't affect the dot products
calculation because the actual shape of the blob is still (4, 32) in concat_split_op
Differential Revision: D6264793
fbshipit-source-id: 82995e83a8c859cbd15617ff7850a35b30b453b6
Summary:
To achive this, I modified the blob name scheme defined in a layer.
Before it was scope/fc_w and scope/fc_w_auto_0 (if there is another fc
within the same scope).
Now I change it to scope/fc/w and scope/fc_auto_0/w.
That is, we rely on the uniqueness of the scoped layer name to define
names for blobs.
I also overwrote the create_param method in LayerModelHelper to let it
use the resolved name for blobs given the sharingparameter context.
There are some details such as making the initializer more structured
that I need to finalize.
Reviewed By: kennyhorror
Differential Revision: D5435132
fbshipit-source-id: a0525f5ea0977e255dd5ea765b38913f5951d455
Summary: Previously, the code below would go out of bound.
Reviewed By: xianjiec
Differential Revision: D4968037
fbshipit-source-id: 3760e2cddc919c45d85ac644ac3fabf72dbaf666
Summary:
otherwise the blob will be in different namescope, e.g., `_nested`: https://fburl.com/ntlsaezv.
this make tensorboard ugly.
Reviewed By: dzhulgakov
Differential Revision: D4696946
fbshipit-source-id: 73627feccd7c4896964e6c549b7241bcce4f49a7
Summary:
Remove the use of `NextName` in layer model helper, so that the same function return `model_helper` that should construct identical `Net`, when under the same NameScope.
The `NextScopedBlob` should only take effect when there is real name conflicting, otherwise it returns ScopedBlobReference.
This is critical for parameter blobs. In long run, we need to be able to specify parameter blobs more explicitly. (kennyhorror is working on this). This solution works in short term for e.g., two tower sparse nn models.
Reviewed By: kennyhorror
Differential Revision: D4555423
fbshipit-source-id: 2c4b99a61392e5d51aa878f7346466a8f14be187
