* Scope MultiRNN blobs with name as well as layers
Also don't double scope MultiRNN in case of multiple layers.
* Scope input projection of first layer with name
We don't scope it with layers because the projection is done
outside of the layer.
* Avoid scoping input blob in MemongerTest.test_rnn
* Rectify input_blob in prepare_input
Revert change in memonger_test because rectifying input will solve the problem.
* First attempt on sqrt op
* Adding the Sqrt op along with the test cases
* Made changes per @Yangqing's questions re: tensor format and used hypothesis to generate input tensor
In pytorch, after pad_packed_sequence, the "extra" elements (after the
ends of the sequences) are reset. In the equivalent Caffe2 graph
exported via ONNX, they contained some leftover values, which caused
tests to fail. Probably no one depends on these values, but just in
case, set them to zero to mimic pytorch semantics.
* Handle legacy pad in Caffe2==>ONNX converter, also remove fake initializer
* Address the comments, 1) have filtering fake initializer before ssa rewrite, 2) polish the legacy padding handling logic
* Add test cases to cover the code just added
* Nit
Added functionality to GatherRangesToDenseOp such that it supports an optional input KEY, and will sort DATA according to KEY for each example per feature.
* [C2] Implement Layer-wise Adaptive Rate Scaling (LARS)
* [C2] Implement Layer-wise Adaptive Rate Scaling (LARS)
* add unit test for Lars
* set default value for lars to be None
* remove lars for subclasses of SgdOptimizer
The old pow operator has been deleted in math_ops.cc, math_ops.cu and math_ops.h, while the new operator supporting scalar and tensor exponent has been added in pow_op.cc, pow_op.h an elementwise_op.cu.
Summary: as title. This is similar with python pprint utility for nested json data structure. It can be useful for checking schema during debugging.
Reviewed By: kittipatv
Differential Revision: D6710767
fbshipit-source-id: e450aa5477fa1ad4f93c4573f8108a2f49956da8
Summary: The original implementation averaged the momentum across the embedding dimensions, which doesn't make any sense. This meant all the embedding dimensions received the same update, becoming a very memory-expensive one-dimensional embedding.
Differential Revision: D7003135
fbshipit-source-id: ed54e3427bc13895a4e949e96b4b17f6ebfb6d53
Summary:
In some cases we were doing quantization even we we should not. This diff is
preventing this from happening.
Reviewed By: rayleichen
Differential Revision: D6953547
fbshipit-source-id: 7c65baaf969e5e1bddb68ca8182f4f3b43f2431d
Summary:
Without this enforce it's too easy to export model overriding it's params in
predictor.
Reviewed By: rayleichen
Differential Revision: D6984506
fbshipit-source-id: 9bbf375758686c6ad12ad071723f255363e98ae6
Summary:
This reverts commit 30f614beea6f859fee25ce4f85573142885dde45
bypass-lint
An infra SEV is better than not reverting this diff.
If you copy this password, see you in SEV Review!
cause_a_sev_many_files
Differential Revision:
D6893040
Original commit changeset: 30f614beea6f
fbshipit-source-id: 5e98a24699088283f864efe31234874bdacbe3c3
Summary: The old pow operator has been deleted in math_ops.cc, math_ops.cu and math_ops.h, while the new operator supporting scalar and tensor exponent has been added in pow_op.cc, pow_op.h an elementwise_op.cu.
Reviewed By: houseroad
Differential Revision: D6893040
fbshipit-source-id: 30f614beea6f859fee25ce4f85573142885dde45
Summary:
Add a function to return true if the model contains loss and retuen
false if the model doesn't include a loss.
Reviewed By: kittipatv
Differential Revision: D6982444
fbshipit-source-id: 1f63b7a1eaa3077841a0ad5d8d854b471d0aa84c
Summary: Sometimes we need to add some extra schema later
Reviewed By: sunnieshang
Differential Revision: D6951849
fbshipit-source-id: 564eb88f9250eae24869fd10ba3426e00a18af33
Summary:
Modify detect_components to take a list of valid node_name prefixes instead of values. Users can set node_name to e.g. `'sparse_component:0'`, `'sparse_component:1'`, etc.
and pass `'sparse_component:'` as a valid prefix. Also add `Tags.SPARSE_COMPONENT` in addition to `Tags.SPARSE_SHARDED` and `Tags.SPARSE_DONT_SHARD` and update all calls to
`detect_device_components`.
Reviewed By: azzolini
Differential Revision: D6952599
fbshipit-source-id: e1b1e6b146a6bd053b295690016044fd5990c893
Summary:
Change log
- Support rectangle cropping, where height and width of clip cropping can be set separately. This is useful when most video resolution is non-square, such as 240p, 360p and 480p where width is significantly larger than height.
- Comparisons of training on ucf101 between using 112x112 croppings and using 112x144 cropping.
- https://fburl.com/i0rw6y1k
- Support 14 multi-cropping per video clip at testing stage to improve classification accuracy. Take left-top, central-top, right-top, left-bottom, central-bottom, right-bottom and central-central croppings as well as their mirrorings. In total, 14 croppings.
- Comparisons on the same model trained on UCF-101. Use 1 clip per video
- RGB. f41014306, w/o Vs f41014868, w/ multi-cropping: `0.64099 Vs 0.65796`
- OF. f41014889, w/o Vs f41014913, w/ multi-cropping: `0.65796 Vs 0.67624`
- Support color jittering and color lighting on RGB data for training data augmentation.
- Comparisons of training on ucf101 from scratch with and without color jittering and lighting:
- https://fburl.com/k69zatul
Reviewed By: HengCV
Differential Revision: D6962620
fbshipit-source-id: 9b43478945874142727fea351ee04417218e6606
Summary: Copying model_id from metaNetDef_->modelInfo in PredictorContainer for dper models. Since these model_id's are strings of <model_id>_<snapshot_id>, changed them to strings in net_observer
Reviewed By: salexspb
Differential Revision: D6752448
fbshipit-source-id: 93c91950b44c012e57240aaf909bc961449cfd7c
Summary: Step 1 of 3 in adding support for multidevice batch normalization on GPUs. Implements ChannelStatsOp for the GPU. Next steps are to port the backprop stats op and tie things together in DPM.
Reviewed By: rbgirshick
Differential Revision: D6953411
fbshipit-source-id: cd50e53d66ea84fe66021c08b978b28290d9f347
Summary: The interface is not used anywhere AFAICT; cleaning up to make it less confusing.
Reviewed By: kuttas
Differential Revision: D6867040
fbshipit-source-id: 3e8a77df76ef09c6864c308561825777b326f76c
Summary: CompleteInTimeOrDie was added to detect deadlocks and proactively exit. In addition, call os.abort() to generate a core dump so that the error is actionable.
Reviewed By: bmaurer
Differential Revision: D6938343
fbshipit-source-id: 8bd36da4f4bb1195bd3398f25d133a6ebf1c66ad
