Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53402
Add an `options` field to the `Save` operator which accepts options for how to
serialize different blobs. At the moment this simply allows controlling the
existing `chunk_size` behavior, but in the future we can add other options,
such as the ability to control compression settings or other serialization
formats.
ghstack-source-id: 123567034
Test Plan:
Added a new test to `load_save_test.py` that passes in options and verifies
that blobs were serialized with the expected number of chunks.
buck test caffe2/caffe2:caffe2_test_cpu \
caffe2/caffe2/core:serialization_test \
caffe2/caffe2/python/operator_test:load_save_test
Reviewed By: mraway
Differential Revision: D26502577
fbshipit-source-id: 6e302e530bb96990517c2e35c505db7f14a56284
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53401
This is a reland of D26641599 (cd9ac54ea7) after rebasing onto D26802576 (f595ba1bae).
Add some small utility functions to read the blob names back from the minidb
file so that we can verify how many chunks were written for each blob.
ghstack-source-id: 123567033
Test Plan: buck test caffe2/caffe2/python/operator_test:load_save_test
Reviewed By: mraway
Differential Revision: D26853942
fbshipit-source-id: 0b45078fdd279f547752c8fdb771e296374a00da
Summary:
Context: https://github.com/pytorch/pytorch/pull/53299#discussion_r587882857
These are the only hand-written parts of this diff:
- the addition to `.github/workflows/lint.yml`
- the file endings changed in these four files (to appease FB-internal land-blocking lints):
- `GLOSSARY.md`
- `aten/src/ATen/core/op_registration/README.md`
- `scripts/README.md`
- `torch/csrc/jit/codegen/fuser/README.md`
The rest was generated by running this command (on macOS):
```
git grep -I -l ' $' -- . ':(exclude)**/contrib/**' ':(exclude)third_party' | xargs gsed -i 's/ *$//'
```
I looked over the auto-generated changes and didn't see anything that looked problematic.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53406
Test Plan:
This run (after adding the lint but before removing existing trailing spaces) failed:
- https://github.com/pytorch/pytorch/runs/2043032377
This run (on the tip of this PR) succeeded:
- https://github.com/pytorch/pytorch/runs/2043296348
Reviewed By: walterddr, seemethere
Differential Revision: D26856620
Pulled By: samestep
fbshipit-source-id: 3f0de7f7c2e4b0f1c089eac9b5085a58dd7e0d97
Summary:
Add some small utility functions to read the blob names back from the minidb
file so that we can verify how many chunks were written for each blob.
Test Plan: buck test caffe2/caffe2/python/operator_test:load_save_test
Reviewed By: mraway
Differential Revision: D26641599
fbshipit-source-id: bccb0af157d85e585e95bc7be61c4584fba3cb04
Summary:
Add a test in `load_save_test.py` that passes in a chunk_size parameter,
to ensure that we exercise the logic that passes the chunk size to the C++
serialization code.
Test Plan:
Ran the tests with the vlog level set to 3 and manually verified the log
messages showed that we were serializing in the expected chunks.
There are existing C++ tests that confirm chunking behavior works as expected
in the pure C++ code.
Reviewed By: mraway
Differential Revision: D26502578
fbshipit-source-id: cd0074f2358da81c68b0fed2c2a94818d83a957d
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52388
Pull Request resolved: https://github.com/pytorch/glow/pull/5364
This allows us to change global variables through onnxifi calls. And add python bindings along with it. Note that we supply a dummy backend_id as it's not needed by glow due to setting being global.
#codemod
Test Plan:
```
buck test mode/dev //glow/fb/test:test_onnxifi_optionnnpi
```
Reviewed By: jfix71, khabinov
Differential Revision: D26481652
fbshipit-source-id: 19b8201c77f653cf7d93ad68760aa7fb5ec45ff4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51768
This updates python/core.py to explicitly define all of the `DataType`
values rather than dynamically defining them at runtime from the
`caffe2_pb2` values.
This allows type checkers like Pyre and Mypy to see the members of the
`DataType` class. Otherwise the type checkers report errors such as
`"core.DataType" has no attribute "INT64"`.
This code does keep a run-time check that all of the data types defined
by `caffe2_pb2.proto` are defined correctly in this file. This way if
someone does add a new type to `caffe2_pb2.proto` it should be very
quickly apparent that this file needs to be updated and kept in sync.
ghstack-source-id: 121936201
Test Plan:
Confirmed that various caffe2/python tests still pass.
Verified that this allows many `pyre-fixme` comments to be removed in
downstream projects, and that Pyre is still clean for these projects.
Reviewed By: jeffdunn
Differential Revision: D26271725
Pulled By: simpkins
fbshipit-source-id: f9e95795de60aba67d7d3872d0c141ed82ba8e39
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51767
The `_import_c_extension.py` finds the right C extension library to use,
and then simply re-exports all of the symbols that it defines.
This adds a `_import_c_extension.pyi` file with type hints to let type
checkers like Pyre and Mypy know the names of the symbols that will be
re-exported from the C extension.
This does not define all of the symbols provided by the C extension,
but does define all of the symbols necessary to make type checkers happy
about other code in the `caffe2/python` directory.
ghstack-source-id: 121916324
Test Plan:
Was able to have Pyre successfully type check the `caffe2/python`
directory with this stub file plus a few other changes.
Confirmed that all of the dependent projects affected by this report no new
pyre issues in sandcastle.
Ran `python test/test_type_hints.py` in the PyTorch github repository and
confirmed it also passes.
Differential Revision: D26271726
Pulled By: simpkins
fbshipit-source-id: 6dbadcf02e0b2cc44a9e3cdabe9291c1250959b4
Summary: Previously there was no regularizer implemented for fp16 sparse features. Add regularizer support here using the Float16SparseNormalize implemented in this stack.
Test Plan:
buck test //caffe2/caffe2/python:regularizer_test
In f248648705, we can see there is the operator `Float16SparseNormalize`.
{F356635445}
Reviewed By: bigrabithong
Differential Revision: D24042567
fbshipit-source-id: 5e0065f8c10b8748daffa8a54a6bf8f461460b18
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51762
Update test_util.py to add a `make_tempdir()` function to the `TestCase`
class. The main advantage of this function is that the temporary
directory will be automatically cleaned up when the test case finishes,
so that test case does not need to worry about manually cleaning up this
directory.
This also prefixes the directory name with `caffe2_test.` so that it is
more obvious where the temporary directories came from if they are ever
left behind after a crashed or killed test process.
This updates the tests in `operator_test/load_save_test.py` to use this
new function, so they no longer have to perform their own manual cleanup
in each test.
Test Plan: python caffe2/python/operator_test/load_save_test.py
Reviewed By: mraway
Differential Revision: D26271178
Pulled By: simpkins
fbshipit-source-id: 51175eefed39d65c03484482e84923e5f39a4768
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51766
Check if we are on Windows using `sys.platform` rather than
`platform.system()`. Even though `platform.system()` is more modern, it
has a few downsides: this performs a runtime check of the platform type,
which has non-zero overhead. On Linux it actually executes the separate
`/bin/uname` process. On the other hand `sys.platform` is determined
when the Python interpreter is compiled, so this is a simple hard-coded
string.
Because it is a runtime check, `platform.system()` checks also cannot be
analyzed by static type checkers like Pyre and Mypy. These type
checkers do understand `sys.platform` checks, and can correctly avoid
complaining about code paths that use platform-specific modules and
functions. e.g., they can avoid complaining about `ctypes.WinDLL` not
existing on Linux if its use is guarded by a `sys.platform` check.
ghstack-source-id: 121107705
Test Plan: Ran tests on Linux, and will check CI test results.
Reviewed By: mraway
Differential Revision: D26271724
Pulled By: simpkins
fbshipit-source-id: b86e427e4ceec0324464ba4bc88b95d5813172d0
Summary:
Increasing the deadline as to avoid
flakiness of the test on ROCM.
Signed-off-by: Roy, Arindam <rarindam@gmail.com>
Fixes #{issue number}
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52013
Reviewed By: albanD
Differential Revision: D26360209
Pulled By: mrshenli
fbshipit-source-id: 1ddc7062c5ff7c980233d22844073de9fb7dcbb3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52083
This makes minor fixes in `caffe2/python` to address all errors currently
reported by Pyre.
I update the code to fix errors when doing so looked simple and safe,
and added `pyre-fixme` comments in other places.
ghstack-source-id: 121109695
Test Plan: Confirmed that Pyre no longer reports errors under `caffe2/python`
Differential Revision: D26272279
fbshipit-source-id: b1eb19d323b613f23280ce9c71e800e874ca1162
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51769
Remove some Python 2 compatibility code that otherwise causes errors to
be reported from static type checkers.
Static type checkers complain that the old Python 2 modules and
functions referenced by this code do not exist. Given that Python 2
support is entirely deprecated now we can simply remove the
compatibility code.
ghstack-source-id: 121313191
Test Plan:
Was able to get Pyre to successfully type check the `caffe2/python`
directory with this and some other changes.
Reviewed By: Tianshu-Bao
Differential Revision: D26271723
Pulled By: simpkins
fbshipit-source-id: fec8a09466be6867388832380480aafd36616aa1
Summary: Moving caffe2_core_gpu_python contbuild to use GPU/RE
Test Plan: CI
Reviewed By: malfet
Differential Revision: D26261826
fbshipit-source-id: a6f8c7bd8368c1cb69499ea0ea7d5add0956a7ad
Summary:
The test is flaky on ROCM when deadline is set to 1 second. This is affecting builds as it is failing randomly.
Disabling for now.
Signed-off-by: Arindam Roy <rarindam@gmail.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50964
Reviewed By: houseroad
Differential Revision: D26049370
Pulled By: BIT-silence
fbshipit-source-id: 22337590a8896ad75f1281e56fbbeae897f5c3b2
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50393
Exponential Moving Average
Usage:
add ema_options in adagrad optimizer. For details, plz refer to the test workflow setting.
if ema_end == -1, it means ema will never end.
Test Plan:
buck test caffe2/caffe2/fb/optimizers:ema_op_optimizer_test
buck test caffe2/caffe2/fb/optimizers:ema_op_test
f240459719
Differential Revision: D25416056
fbshipit-source-id: a25e676a364969e3be2bc47750011c812fc3a62f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49486
Remove code for Python 3.5 and lower.
There's more that can be removed/modernised, but sticking mainly to redundant version checks here, to keep the diff/PR smaller.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46579
Reviewed By: zou3519
Differential Revision: D24453571
Pulled By: ezyang
fbshipit-source-id: c2cfcf05d6c5f65df64d89c331692c9aec09248e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49591
A bunch of these tests are marked flaky, and have been since time immemorial. (Read: as far back as Buck will build.) However closer inspection reveals that they fail if and only if run on a GPU worker. What seems to be going on is that there are more jobs than GPUs, so the contention causes waits which registers as timeouts on the test.
This diff is kind of hacky, but it basically just drops deadlines if a GPU is present. Because Caffe2 is going away I'm not too terribly concerned about a beautiful solution, but we may as well keep some test coverage if it's easy.
CC Sebastian, Ilia, Min, and Hongzheng who also have tasks for what seems to be the same flakiness.
Test Plan: Turn the tests back on and see if they fall over. (The failure repros reliably on an OnDemand GPU and is fixed by this change, so it's not really just a hail Mary.)
Reviewed By: ngimel
Differential Revision: D25632981
fbshipit-source-id: 43dcce416fea916ba91f891e9e5b59b2c11cca1a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49402
In cases of NCCLAllReduce operations there could be non-trivial overhead for
launching cooperative kernels (especially in case of async execution of
different parts of the model). This diff is reviving this operator to make it
possible to fuse multiple operations into a single kernel.
Test Plan:
Unit-test.
Used in a later diff.
Reviewed By: xianjiec
Differential Revision: D25531206
fbshipit-source-id: 64b1c161233a726f9e2868f1059316e42a8ea1fc
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49322
In some cases async execution might loose dependencies (Alias like ops) or produce suboptimal scheduling when there is an option which parts to schedule first. Example of the later behavior can happen in ModelParallel training where copy can get lower priority compared to the rest of the execution on the given GPU, which will caused other GPUs to starve.
This operator allows to address these issues by introducing extra explicit dependencies between ops.
Test Plan:
Unit-test/
E2E testing in the future diffs.
Reviewed By: xianjiec
Differential Revision: D24933471
fbshipit-source-id: 1668994c7856d73926cde022378a99e1e8db3567
Summary:
+ Add ArgMin support to Caffe2 to PyTorch converter
+ Using hypothesis to parameterize different conditions for test
Test Plan: buck test //caffe2/torch/fb/model_transform/c2_convert:c2_pt_converter_test
Reviewed By: houseroad
Differential Revision: D25016203
fbshipit-source-id: 94489fcf1ed3183ec96f9796a5b4fb348fbde5bc
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48240
Adds the support for converting the SparseLengthsSum4BitRowwiseSparse operator from caffe2 to pytorch as a part of c2_pt_converter
Test Plan:
Added a unit tested
buck test //caffe2/torch/fb/model_transform/c2_convert:c2_pt_converter_test
Tests Passed :
https://our.intern.facebook.com/intern/testinfra/testrun/2251799856412296
Reviewed By: houseroad
Differential Revision: D25067833
fbshipit-source-id: 45cbc331ca35bee27e083714e65a1e87a2a2d2e0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48340
This changes the context managed classes from using a decorator to define them to using inheritance. Inheritance allows the python static type checking to work correctly.
```
context.define_context()
class Bar(object): ...
context.define_context(allow_default=True)
class Foo(object): ...
```
becomes
```
class Foo(context.Managed): ...
class Bar(context.DefaultManaged): ...
```
Behavior differences:
* arg_name has been removed since it's not used anywhere
* classes need to call `super()` in `__enter__/__exit__` methods if they override (none do)
This also defines a context.pyi file to add types for python3. python2 support should not be affected
Test Plan:
ci
buck test //caffe2/caffe2/python:context_test //caffe2/caffe2/python:checkpoint_test
Reviewed By: dongyuzheng
Differential Revision: D25133469
fbshipit-source-id: 16368bf723eeb6ce3308d6827f5ac5e955b4e29a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48407
T79817692: Fused8BitRowwiseQuantizedToFloat operator support for c2_pt_converter.
Also refactored some repeated code from the existing test functions. (Initial commit only has refactoring.)
Test Plan: buck test //caffe2/torch/fb/model_transform/c2_convert:c2_pt_converter_test
Reviewed By: bugra
Differential Revision: D25069936
fbshipit-source-id: 72f6a845a1b4639b9542c6b230c8cd74b06bc5a0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48404
On bento this is printing a lot of msgs like (see N408483 if you're an internal user)
```
W1123 120952.322 schema.py:811] Scalar should be considered immutable. Only call Scalar.set() on newly created Scalar with unsafe=True. This will become an error soon.
```
And it's ignoring the log level I set at global level. Removing this line unless this is super important.
Test Plan: build a local dper package and verify
Differential Revision: D25163808
fbshipit-source-id: 338d01c82b4e67269328bbeafc088987c4cbac75
Summary: is_external_input doesn't check if the lookup tables are valid. Calling .Proto() should invalidate all lookup tables and have them rebuilt on call to any methods depending on them. This adds this check to is_external_input.
Test Plan: internal unit tests
Reviewed By: dzhulgakov, esqu1
Differential Revision: D25100464
fbshipit-source-id: d792dec7e5aa9ffeafda88350e05cb757f4c4831
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47023
DeviceType pretty clearly only needs 1 byte. DeviceIndex only needs 1 byte given that machines don't have anywhere near 255 GPUs in them as far as I know.
ghstack-source-id: 116901430
Test Plan: Existing tests, added assertion to catch if my assumption about DeviceIndex is incorrect
Reviewed By: dzhulgakov
Differential Revision: D24605460
fbshipit-source-id: 7c9a89027fcf8eebd623b7cdbf6302162c981cd2
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47768
This stores the next ID for a given NextName(prefix, output_id) so repeated calls to NextName are significantly faster. This accounts for ~65% of time spent for large models.
Test Plan:
buck test //caffe2/caffe2/python/...
will launch canary job before landing to ensure no regressions + confirm speedup
Reviewed By: dzhulgakov
Differential Revision: D24876961
fbshipit-source-id: 668d73060d800513bc72d7cd405a47d15c4acc34
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48021
Extending operator schema check for simple memonger to dag memonger as well. As part of this a fix is being made to handle inplace ops (having at least one output name same as input blob). Earlier all the output blobs from ops were being treated as shareable but it failed assertion of external input blobs with the same name not allowed to share.
Test Plan: Added corresponding unit tests
Reviewed By: hlu1
Differential Revision: D24968862
fbshipit-source-id: b6679a388a82b0d68f65ade64b85560354aaa3ef
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47718
Distributed Inference splits a predict net into multiple parts, part0 being the main part which contains ops to make remote calls to other parts. part0 predict net may contain AsyncIf ops to optimize rpc call usage. AsyncIf ops have internal nets which may refer to memongered blobs. This change handles AsyncIf ops to update internal nets to refer to memongered blobs.
As part of this change, I am also updating dag memonger traversal to always start from root op, i.e. ops with 0 in degree. Earlier logic will start traversing ops based on input head blobs and if one of the head inputs is getting used in a non-root op which gets visited before its parent, the traversal will throwing assertion error here: https://fburl.com/diffusion/ob110s9z . Almost for all the distributed inference part0 nets, it was throwing this assertion error.
Test Plan: Added corresponding tests in memonger_test.py . Could not find unit tests in c++ version of memonger.
Reviewed By: hlu1
Differential Revision: D24872010
fbshipit-source-id: 1dc99b2fb52b2bc692fa4fc0aff6b7e4c5e4f5b0
Summary: Added the MatMul operator for caffe2
Test Plan: buck test //caffe2/torch/fb/model_transform/c2_convert:c2_pt_converter_test
Reviewed By: bugra
Differential Revision: D24920937
fbshipit-source-id: 7ba09ba0439cb9bd15d6a41fd8ff1a86d8d11437
Summary: To support min/max/mean/std, SummarizeOp need to skip size checking (similar to the LpNorm error mentioned above) and accept multiple types
Test Plan:
unit test:
`buck test //caffe2/caffe2/fb/tensorboard/tests:tensorboard_accumulate_histogram_op_test`
https://our.intern.facebook.com/intern/testinfra/testrun/1407375057859572
`buck test //caffe2/caffe2/fb/tensorboard/tests:tensorboard_accumulate_histogram_op_test --stress-runs 1000`
https://our.intern.facebook.com/intern/testinfra/testrun/2533274832166362
Reviewed By: cryptopic
Differential Revision: D24605507
fbshipit-source-id: fa08372d7c9970083c38abd432d4c86e84fb10e0
