Hide the flatbuffers types and headers from the serialize APIs, and stop using the DEPRECATED functions from flatbuffer_loader.h.
This required creating the new `DetachedBuffer` type to replace/hide `flatbuffers::DetachedBuffer`, a class that owns a span of custom-allocated memory.
This is another step towards hiding the flatbuffers types and headers from the load/serialize APIs.
Differential Revision: [D38292798](https://our.internmc.facebook.com/intern/diff/D38292798/)
**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D38292798/)!
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82619
Approved by: https://github.com/qihqi
We define specializations for pybind11 defined templates
(in particular, PYBIND11_DECLARE_HOLDER_TYPE) and consequently
it is important that these specializations *always* be #include'd
when making use of pybind11 templates whose behavior depends on
these specializations, otherwise we can cause an ODR violation.
The easiest way to ensure that all the specializations are always
loaded is to designate a header (in this case, torch/csrc/util/pybind.h)
that ensures the specializations are defined, and then add a lint
to ensure this header is included whenever pybind11 headers are
included.
The existing grep linter didn't have enough knobs to do this
conveniently, so I added some features. I'm open to suggestions
for how to structure the features better. The main changes:
- Added an --allowlist-pattern flag, which turns off the grep lint
if some other line exists. This is used to stop the grep
lint from complaining about pybind11 includes if the util
include already exists.
- Added --match-first-only flag, which lets grep only match against
the first matching line. This is because, even if there are multiple
includes that are problematic, I only need to fix one of them.
We don't /really/ need this, but when I was running lintrunner -a
to fixup the preexisting codebase it was annoying without this,
as the lintrunner overall driver fails if there are multiple edits
on the same file.
I excluded any files that didn't otherwise have a dependency on
torch/ATen, this was mostly caffe2 and the valgrind wrapper compat
bindings.
Note the grep replacement is kind of crappy, but clang-tidy lint
cleaned it up in most cases.
See also https://github.com/pybind/pybind11/issues/4099
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82552
Approved by: https://github.com/albanD
Summary:
Originally reverted this diff D37116110 (c9aa74a37f) because
```
> /usr/local/bin/buck build //caffe2/test/cpp/lite_interpreter_runtime/...
BUILD FAILED
The rule //caffe2:backend_interface_libAndroid could not be found.
Please check the spelling and whether it is one of the 1866 targets in /data/users/batanasov/fbsource/fbcode/caffe2/TARGETS. (52107 bytes)
1 similar targets in /data/users/batanasov/fbsource/fbcode/caffe2/TARGETS are:
//caffe2:backend_interface_lib
This error happened while trying to get dependency '//caffe2:backend_interface_libAndroid' of target '//caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profilerAndroid'
At //caffe2:backend_interface_libAndroid (ovr_config//platform/linux:x86_64-fbcode)
At //caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profilerAndroid (ovr_config//platform/linux:x86_64-fbcode)
```
The add test_mobile_profiler was not meant to be built with Android or other mobile platforms, so we are changing the test to a cpp_unittest
Test Plan:
```
buck test //caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler
Parsing buck files: finished in 0.9 sec
Creating action graph: finished in 26.5 sec
Downloaded 2/2 artifacts, 1.30 Mbytes, 0.0% cache miss (for updated rules)
Building: finished in 16.5 sec (100%) 18451/18451 jobs, 3/18451 updated
Total time: 44.0 sec
More details at https://www.internalfb.com/intern/buck/build/8bee82c1-66a9-4fae-805f-e4ef5505d25d
BUILD SUCCEEDED
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id: 6904f989-5c17-4c5b-9a4f-ffb643dfcc43
Trace available for this run at /tmp/tpx-20220726-114727.001729-6904f989-5c17-4c5b-9a4f-ffb643dfcc43/trace.log
RemoteExecution session id: reSessionID-6904f989-5c17-4c5b-9a4f-ffb643dfcc43-tpx
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/844425183404951
✓ ListingSuccess: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler : 3 tests discovered (17.640)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.Backend (0.206)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.BackendMemoryEvents (0.271)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.ModuleHierarchy (0.268)
Summary
Pass: 3
ListingSuccess: 1
Finished test run: https://www.internalfb.com/intern/testinfra/testrun/844425183404951
```
Differential Revision: D38166171
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82243
Approved by: https://github.com/salilsdesai
- Added backwards compatibility test to ensure that every Op in the old Nondeterministic op list from ir.cpp has the tag nondeterministic_seeded.
**Note that the 3 ops marked "normal" were not actually real op signatures. (ie findOp with dispatcher returned a nullptr). These were changed to normal.Tensor_Tensor, normal.Tensor_float and normal.float_Tensor in the list since that is what matches the rest of their signatures**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82257
Approved by: https://github.com/davidberard98
- Add is_aliasing method in function schema to be able to indicate if an argument has an alias_set attached to it. This is utilized in the integration with autograd (see next PR)
- Tested in test_schema_info
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82255
Approved by: https://github.com/davidberard98
- Modified is_nondeterministic method in SchemaInfo class to utilize tags.
- Modified isNonDeterministic method in ir.cpp to utilize SchemaInfo when a Node is an aten op.
- Added an assert to ensure that if a node is an aten op kind, it has a schema.
- Tested through verifying that all IR.cpp tests run, and through adding 2 custom determinism checks to test for the special dropout edge case and a general bernoulli case.
Differential Revision: [D38179499](https://our.internmc.facebook.com/intern/diff/D38179499)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82253
Approved by: https://github.com/davidberard98
- Added backwards compatibility test to ensure that every Op in the old Nondeterministic op list from ir.cpp has the tag nondeterministic_seeded.
**Note that the 3 ops marked "normal" were not actually real op signatures. (ie findOp with dispatcher returned a nullptr). These were changed to normal.Tensor_Tensor, normal.Tensor_float and normal.float_Tensor in the list since that is what matches the rest of their signatures**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82029
Approved by: https://github.com/davidberard98
- Add is_aliasing method in function schema to be able to indicate if an argument has an alias_set attached to it. This is utilized in the integration with autograd (see next PR)
- Tested in test_schema_info
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81916
Approved by: https://github.com/davidberard98
- Modified is_nondeterministic method in SchemaInfo class to utilize tags.
- Modified isNonDeterministic method in ir.cpp to utilize SchemaInfo when a Node is an aten op.
- Added an assert to ensure that if a node is an aten op kind, it has a schema.
- Tested through verifying that all IR.cpp tests run, and through adding 2 custom determinism checks to test for the special dropout edge case and a general bernoulli case.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81836
Approved by: https://github.com/davidberard98
- Generalized AnalyzeImpl cases for batchNorm and InstanceNorm in alias_analysis.cpp using schema_info.
- Tested by ensuring all aliasDB special case checks for batchNorm and instanceNorm pass as expected.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81785
Approved by: https://github.com/davidberard98
- Modify the is_mutable(size_t index) overload to become is_mutable(const SchemaArgument& argument) due to cases where one might want to check the mutability of either input or output arguments.
- Refactored all calls to the function to use this new overload
- Tested through is_mutable() tests in test_schema_info.cpp
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81784
Approved by: https://github.com/davidberard98
- Created may_contain_alias method in SchemaInfo which is a wrapper around FunctionSchema may_contain_alias that also accounts for argument values. This is done using similar logic to AliasDB using an internal understanding of wildcard sets and container object
- Added a multitude of tests for various graph edge cases (inputs aliasing, outputs aliasing, multiple input wildcards, multiple container objects, etc...).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81444
Approved by: https://github.com/davidberard98
- Create c10::AliasTypeSet type def of vector<TypePtr> to match alias_analysis.cpp formatting and improve readability.
- Move canAliasTypeSetsAlias, mapTypeToAliasTypeSet, getAliasTypeSetContainedTypes, and getCorrectList to public in function_schema.h for use in SchemaInfo class.
**In the future it might be better to find a different home for most of these functions since they don't depend on functionSchema. **
- Created hash function for SchemaArgument
- Add assert to ensure that there is only 1 input and 1 output with each alias set (excluding wildcard)
- Fixed double wildcard input edge case for may_alias. (This is the case where if there is a schema with the form (Tensor(a) a, Tensor(*) b, Tensor(*) c) -> Tensor, and the argument values for 'a' and 'b' cause them to alias, then 'a' may also alias 'c'.
- Added tests for double wildcard case in may_alias, mismatching types in may_alias, and the uniqueness internal assert.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81439
Approved by: https://github.com/davidberard98
- Created may_contain_alias method in FunctionSchema to publicize more detailed aliasing information about inputs and outputs of a schema. This method returns whether the first argument may contain an alias to the second argument (ie if the first argument is a list[Tensor], it can contain an alias to the second argument of the second argument is Tensor(*)) and vice versa if bidirectional = true.
- Created helper methods are explained more thoroughly in detail in function_schema.h
-Tested may_contain_alias methods for basic functionality, bidirectional functionality, wildcard functionality and dual container functionality in test_schema_info.cpp.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81352
Approved by: https://github.com/davidberard98, https://github.com/Gamrix
- Added special cases for detach in is_non_deterministic() check and batch_norm and instance_norm in is_mutable() check in SchemaInfo().
- Added tests for the above special cases for detach, batch_norm and instance_norm.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81007
Approved by: https://github.com/davidberard98
- Added has_side_effects method which returns whether a given op has side effects. Currently this is implemented with a hard-coded list of functions copied from ir.cpp in AliasDB, but this will eventually be implemented by returning with a given schema has the has_side_effects tag.
- Tested in test_schema_info.cpp with both an op with side effects and an op without side effects.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81002
Approved by: https://github.com/davidberard98
- Added is_non_deterministic which returns whether a given op is non-deterministic. Currently this is implemented with a hard-coded list of non-deterministic functions copied from ir.cpp in AliasDB, but this will eventually be implemented by returning with a given schema has the non_deterministic tag.
- Tested is_non_deterministic method with a deterministic op and a non deterministic op in test_schema_info.cpp
**Note that the case for op "aten::dropout(Tensor input, float p, bool train) -> Tensor" which is deterministic whenever "train=false" is not accounted for in this pr and will be fixed in a later pr. Currently "aten::dropout(Tensor input, float p, bool train) -> Tensor" is always considered nondeterministic.**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81000
Approved by: https://github.com/davidberard98
- Created may_alias method in SchemaInfo to update the implementation of FunctionSchema::may_alias for aliasing cases due to inputs aliasing.
- Created output_alias_map_ internal variable to check cases where outputs might alias due to inputs aliasing. This variable is updated in generateAliasMap().
- Added tests for various may_alias special cases (input - input, input - output, output - output) due to inputs aliasing causing other arguments to also alias.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80984
Approved by: https://github.com/davidberard98
- Created addArgumentValue/s methods in SchemaInfo to pass argument values into the subclass. These are used for more accurate mutation, aliasing and determinism checks which include special cases.
- Added input_alias_map_ to keep track of which inputs alias each other. This is updated with the method generateAliasMap.
- Implemented is_mutable methods in SchemaInfo which also give information based on argument values. For instance, if two inputs alias and one is mutable by the schema, then the other will also be mutable.
- Tested Schema Info is_mutable implementation where inputs alias as mentioned above.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80972
Approved by: https://github.com/davidberard98
- Created may_alias method in FunctionSchema to publicize aliasing information about inputs and outputs of a schema.
- Tested may_alias methods for basic functionality, exceptions, and wildcard functionality.
**Cases where elements of a container alias another argument will be handled with a new may_contain_alias method which will be created in a later pr**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80918
Approved by: https://github.com/davidberard98
- Added overloads to is_mutable method in FunctionSchema to tell whether an argument at index is mutable or an argument with name is mutable.
- Created SchemaInfo subclass of FunctionSchema with constructors from FunctionSchema and from const char* signature.
- Tested is_mutable method overloads in new test_schema_info.cpp file.
**Note that this pr is used to set up SchemaInfo. Implementation for SchemaInfo will be addressed in later commits**
Differential Revision: [D37651384](https://our.internmc.facebook.com/intern/diff/D37651384)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80734
Approved by: https://github.com/davidberard98
Summary:
Testing for successful recording of backend events. Testing checks that the trace file successfully adds the memory recording from the backend at execute. The record in the trace file looks like:
```
{
"ph": "i", "cat": "cpu_instant_event", "s": "t", "name": "[memory]",
"pid": 847267, "tid": 847267,
"ts": 1655333276408215,
"args": {
"Device Type": 0, "Device Id": -1, "Addr": 108370615407104, "Bytes": 16384, "Total Allocated": 16384, "Total Reserved": 49152
}
}
```
Test Plan:
```
buck test //caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler
Parsing buck files: finished in 1.6 sec
Creating action graph: finished in 30.9 sec
Downloaded 0/5 artifacts, 0.00 bytes, 100.0% cache miss (for updated rules)
Building: finished in 37.9 sec (100%) 25314/25314 jobs, 5/25314 updated
Total time: 01:10.5 min
More details at https://www.internalfb.com/intern/buck/build/ef1c4324-13d3-494e-bce7-8004047d5f89
BUILD SUCCEEDED
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id: 17f300d4-9a78-4302-9e9e-d7ab79ba1ff0
Trace available for this run at /tmp/tpx-20220615-165413.567757-17f300d4-9a78-4302-9e9e-d7ab79ba1ff0/trace.log
RemoteExecution session id: reSessionID-17f300d4-9a78-4302-9e9e-d7ab79ba1ff0-tpx
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/7881299443250383
✓ ListingSuccess: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler : 3 tests discovered (37.049)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.Backend (0.402)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.ModuleHierarchy (0.487)
✓ Pass: caffe2/test/cpp/lite_interpreter_runtime:test_mobile_profiler - MobileProfiler.BackendMemoryEvents (0.280)
Summary
Pass: 3
ListingSuccess: 1
Finished test run: https://www.internalfb.com/intern/testinfra/testrun/7881299443250383
If you need help understanding your runs, please follow the wiki: https://fburl.com/posting_in_tpx_users
```
Differential Revision: D37116110
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80351
Approved by: https://github.com/kimishpatel
Summary:
Remove code dup in import.cpp / export_modules.cpp such that
1. Only one copy of switching logic (detect flatbuffer / is_flatbuffer);
2. Move detection of includeness of flatbuffer to runtime (so no more macros)
This also reverts the dependency of import.cpp -> flatbuffer_loader.cpp to flatbuffer_loader.cpp -> import.cpp.
Differential Revision: D36926217
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79184
Approved by: https://github.com/zhxchen17
Due to implicit conversion shenanigans, having both IntArrayRef
and SymIntArrayRef overloads makes {} ambiguous. While we could
fix this by making a single unified type that accepts all the overloads
we want, an easier fix was to just push the SymIntArrayRef overload
to its own name.
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79281
Approved by: https://github.com/suo
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77926
There is a discrepency between the string representation of C++ FunctionSchema and torchgen.model.FunctionSchema.
The latter will not add parenthesis around the returned types if that a single item,
but the C++ FunctionSchema always add the parenthesis.
Make them consistent so we can convert one type to the other via its string representation and parse method.
Differential Revision: [D36535924](https://our.internmc.facebook.com/intern/diff/D36535924/)
Approved by: https://github.com/bdhirsh
Summary:
Includes following refactor:
1. common loading on operator validation that is dup'd in pickle and
flatbuffer loader moved to function.h/cpp
2. Allow loading of a function without wiring operator.
This function will be used to implement get_bundled_input and friends
for flatbuffer.
Test Plan: contbuild & OSS CI, see 69fa49f123
Reviewed By: cccclai
Differential Revision: D36348549
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77624
Approved by: https://github.com/cccclai
