Kittipat Virochsiri 25b1221579 Allow scalar output in functional layer ... Summary: Some operators, e.g., SoftmaxWithLoss, returns scalar-typed tensor. This would allow us to use those ops without having to write layer manually. Reviewed By: xianjiec, kennyhorror Differential Revision: D4703982 fbshipit-source-id: f33969971c57fc037c9b44adb37af1caba4084b6		2017-03-14 15:32:47 -07:00
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__init__.py	fbsync. TODO: check if build files need update.	2016-11-15 00:00:46 -08:00
batch_lr_loss.py	NextScopedBlob with well-defined behavior and respect namescope	2017-02-16 17:16:36 -08:00
concat.py	small change to concat layer to make tensor board vis nicer	2017-03-12 23:01:18 -07:00
dot_product.py	NextScopedBlob with well-defined behavior and respect namescope	2017-02-16 17:16:36 -08:00
expand_dims.py	NextScopedBlob with well-defined behavior and respect namescope	2017-02-16 17:16:36 -08:00
fc.py	model and preprocessor can handle empty dense inputs	2017-02-22 11:19:15 -08:00
functional.py	Allow scalar output in functional layer	2017-03-14 15:32:47 -07:00
layers.py	Add SparseNN workflow for feed.	2017-03-01 11:02:38 -08:00
simple_operator_layers.py	Fix random issues with some of the layers getting missing from registry.	2017-01-10 15:14:31 -08:00
sparse_lookup.py	clean old unit test, add sum processor and sqrt pooling	2017-03-08 23:04:19 -08:00
sparse_to_dense.py	NextScopedBlob with well-defined behavior and respect namescope	2017-02-16 17:16:36 -08:00
split.py	NextScopedBlob with well-defined behavior and respect namescope	2017-02-16 17:16:36 -08:00
tags.py	fbsync. TODO: check if build files need update.	2016-11-15 00:00:46 -08:00