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
* [mpscnn] MPSCNNChannelShuffle
att
* [Easy] Adding tags as an argument to the functional layer
Without it "tags" would be added as an argument to the operator.
The change here is based on the assumption that there is no operator that takes "tags" as an argument.
* Fix locally_connected_op schema check.
Fix locally_connected_op schema check.
* [C2] Add TypeAndShape inference for few more operators
As desc
* [c2] Shape inference should support 0 as dimension
Tensors can have 0 in their dimension.
* Make MockHiveReader loop over and support max_examples
Replace DatasetReader with RandomDatasetReader.
So that Mock Hive Reader can simulate a large data input using a small sample file as source.
* Utility function to wipe cache between benchmark runs
Caffe2 benchmark does not wipe out cache between runs, and this potentially creates an unrealistically optimistic picture of performance. This diff adds utility function to wipe out the cache.
* Allow caffe2 GlobalInit to be invoked multiple times
Allow caffe2 GlobalInit to be invoked multiple times. Will re-parse gflags and update logging levels on successive invocations, but will not re-run init functions or perform other one-time initialization.
* Add Caffe2 GlobalInitIsCalledGuard to base net and operator classes
Warn if caffe2's GlobalInit function has not been invoked before creating an operator or net object. This is based on discussion here: https://fb.quip.com/kqGIAbmK7vNG
* Rethrow current exception on failure
Rethrow current exception instead of copy constructing a new one on op failure.
* Make `clone()` return subclass of List/Struct
`clone()` is not working correctly when we subclass those classes
* Wipe the cache before the net run
the util function is copied from D7409424
will rebase once D7409424 is landed.
* [Caffe2] [Mobile] Support utils/cast.h::GetCastDataType with LITE_PROTO builds
* Correct includes
async_polling include -> async_base include
* Prepare execution flags for executor migration
Making async_scheduling aware of underlying net type to prepare for executor
migration
* Add operator level observers into async executor
Adding operator level observers into RunAsync operators' calls
* Cleanup TEST_Benchmark
Remove duplicate code and provide default implementation in NetBase
* [C2] Fix type and shape inference for binary comparison ops
As desc.
* Add GlobalInit to predictor to ensure initialization is always done before prediction
FACEBOOK:
Redo D7651453 the correct way.
Now use a static variable for the arguments passed to GLog
* Remove spammy log message
This method is currently used in various places inside Caffe itself.
* Disable events for operators inside a chain
We don't need to use events in operators within a chain because the chain is
always scheduled on a single stream, keeping only first and last event for
scheduling purposes
* Ensure correct finish run order
In rare cases we might call finishRun and trigger net's destruction while
another worker is still holding shared_ptr to a thread pool, that can cause
thread pool destruction from within a worker thread in case no other nets are
using the pool. This diff fixes the order of calling finishRun and also changes
pool() to return raw pointer to keep pool's ownership within the net
* Reduce unnecessary polling
Make sure we don't waste CPU by polling operators that we can set an efficient
callbacks on
* Squash commit of syncing 9506eeb from github to fbcode
Patch xplat buck fix
add virtual destructor to OptimizationPass
add virtual destructor to OptimizationPass
build fixes for sync
build fixes for sync
* Fix net tracing
Fix net tracing from async_scheduling
* Fix logging
Summary:
Before this fix, a functional layer name can appear several time in a
blob and causes confusion. This diff fix this issue.
Reviewed By: kittipatv
Differential Revision: D5641354
fbshipit-source-id: d19349b313aab927e6cb82c5504f89dbab60c2f2
Summary: This diff makes functional layer return scalar if only one output. This diff also corrects all other corresponding implementations.
Reviewed By: kittipatv
Differential Revision: D5386853
fbshipit-source-id: 1f00582f6ec23384b2a6db94e19952836755ef42
Summary:
Currently, the functional layer infers the output types and shapes by running the operator once.
But in cases where special input data are needed to run the operator, the inferrence may fail.
This diff allows the caller to manually specify the output types and shapes if the auto infererence may fail.
Reviewed By: kennyhorror
Differential Revision: D4864003
fbshipit-source-id: ba242586ea384f76d745b29a450497135717bdcc
Summary: Having to pack the input to schema doesn't make much sense since the structure is not recognized by operators anyway.
Differential Revision: D4895686
fbshipit-source-id: df78884ed331f7bd0c69db4f86c682c52829ec76
Summary:
Adding support for multilabel in multiclass workflow. `input_feature_schema` and `trainer_extra_schema` are now a function taking in the preprocessor option and output the schema. This allows dynamic schema definition based on the option.
Changing default value will be in the next diff.
Reviewed By: xianjiec
Differential Revision: D4750064
fbshipit-source-id: 896143f432e963bc1723c0153749efeb39a83bec
Summary:
currently the output schema and blobs are names as "field_i" which is
bad for debugging. This diff allows us to specify output names.
Reviewed By: kennyhorror
Differential Revision: D4744949
fbshipit-source-id: 8ac4d3c75cacbb4c9b5f55793ac969fe1cf20467
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
Summary:
This diff is trying to address one of the concerns that Xianjie have had - requirements create a layer for all operators and attach pass shapes and other info around.
The basic idea of the diff:
1. Try to create a layer with a given name, but if it's not available try to fallback on operator with that name (that is expected to have no parameters).
2. For all operators that we're adding through this functional style of creation - try to use C2 Shape/Type inference logic to get output type. If we fail to get - it just return untyped record and expect user to annotate it when it's really needed.
Reviewed By: xianjiec
Differential Revision: D4408771
fbshipit-source-id: aced7487571940d726424269970df0eb62670c39
