This PR replace c10::guts::to_string with std::to_string. The major part of changes is using void* as optimizer state key since string is used only for serialization and using pointers as hashing keys is more efficient than a string.
Some other guts functions in the affected source files are also replaced.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108480
Approved by: https://github.com/Skylion007
Number of OSS PR were reverted, because new signed-unsigned comparison warnings, which are treated as errors in some internal builds.
Not sure how those selective rules are applied, but this PR removes `-Wno-sign-compare` from PyTorch codebase.
The only tricky part in this PR, as making sure that non-ASCII character detection works for both signed and unsigned chars here:
6e3d51b08a/torch/csrc/jit/serialization/python_print.cpp (L926)
Exclude several files from sign-compare if flash attention is used, due to the violation in cutlass, to be fixed by https://github.com/NVIDIA/cutlass/pull/869
Do not try to fix sign compare violations in caffe2 codebase
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96723
Approved by: https://github.com/albanD
We want to make TorchRec sharded models TorchScriptable.
TorchRec sharded models uses generic types Awaitable[W] and LazyAwaitable[W] (https://github.com/pytorch/torchrec/blob/main/torchrec/distributed/types.py#L212).
In sharded model those types are used instead of contained type W, having the initialization function that produces object of type W.
At the moment when the first attribute of W is requested - `LazyAwaitable[W]` will call its initialization function (on the same stack), cache the result inside and work transparently as an object of W. So we can think about it as a delayed object initialization.
To support this behavior in TorchScript - we propose a new type to TorchScript - `Await`.
In eager mode it works the same as `LazyAwaitable[W]` in TorchRec, being dynamically typed - acting as a type `W` while it is `Await[W]`.
Within torchscript it is `Await[W]` and can be only explicitly converted to W, using special function `torch.jit.awaitable_wait(aw)`.
Creation of this `Await[W]` is done via another special function `torch.jit.awaitable(func, *args)`.
The semantic is close to `torch.jit.Future`, fork, wait and uses the same jit mechanics (inline fork Closures) with the difference that it does not start this function in parallel on fork. It only stores as a lambda inside IValue that will be called on the same thread when `torch.jit.awaitable_wait` is called.
For example (more examples in this PR `test/jit/test_await.py`)
```
def delayed(z: Tensor) -> Tensor:
return Tensor * 3
@torch.jit.script
def fn(x: Tensor):
aw: Await[int] = torch.jit._awaitable(delayed, 99)
a = torch.eye(2)
b = torch.jit._awaitable_wait(aw)
return a + b + x
```
Functions semantics:
`_awaitable(func -> Callable[Tuple[...], W], *args, **kwargs) -> Await[W]`
Creates Await object, owns args and kwargs. Once _awaitable_wait calls, executes function func and owns the result of the function. Following _awaitable_wait calls will return this result from the first function call.
`_awaitable_wait(Await[W]) -> W`
Returns either cached result of W if it is not the first _awaitable_wait call to this Await object or calls specified function if the first.
`_awaitable_nowait(W) -> Await[W]`
Creates trivial Await[W] wrapper on specified object To be type complaint for the corner cases.
Differential Revision: [D42502706](https://our.internmc.facebook.com/intern/diff/D42502706)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90863
Approved by: https://github.com/davidberard98
Not only is this change usually shorter and more readable, it also can yield better performance. size() is not always a constant time operation (such as on LinkedLists), but empty() always is.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/93236
Approved by: https://github.com/malfet
As we live in C++17 world
This is a functional no-op, just
- `s/namespace at { namespace native {/namespace at::native {/`
- `s/namespace torch { namespace jit {/namespace torch::jit {/`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92100
Approved by: https://github.com/izaitsevfb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74119
implemented function to generate source as ExtraFilesMap and constants
wrote function to construct jit module given (ivalue, source,
constant) tripple.
Test Plan: unittest
Reviewed By: pavithranrao
Differential Revision: D34803945
fbshipit-source-id: 2edc798407fe68294cb4c3c7516f5bd143df88c3
(cherry picked from commit 35e54e166b8f0f5cfe8f08c07866b59ae61ee79d)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71968
Right now when we output type to python files under `code/`, we directly write the dynamic type representation `Dynamic<>`, which causes server side to load an unsupported type. Instead we should do the fallback in export_module.cpp.
ghstack-source-id: 147856473
Test Plan:
CI
buck test //xplat/pytorch/mobile/test:test_read_all_mobile_model_configs
```
...
[ OK ] GeneralAndSpecial/BackPortTest.BackPortForChunkIdx/37 (39142 ms)
[ RUN ] GeneralAndSpecial/BackPortTest.BackPortForChunkIdx/38
total: 6 success: 6 failure: 0
[ OK ] GeneralAndSpecial/BackPortTest.BackPortForChunkIdx/38 (9651 ms)
[ RUN ] GeneralAndSpecial/BackPortTest.BackPortForChunkIdx/39
total: 4 success: 4 failure: 0
[ OK ] GeneralAndSpecial/BackPortTest.BackPortForChunkIdx/39 (5509 ms)
[----------] 40 tests from GeneralAndSpecial/BackPortTest (806244 ms total)
[----------] Global test environment tear-down
[==========] 41 tests from 2 test cases ran. (810453 ms total)
[ PASSED ] 41 tests.
```
Reviewed By: pavithranrao
Differential Revision: D33830355
fbshipit-source-id: 0be608fadf14daa2b703f31118ab648cb7b75f9b
(cherry picked from commit 6d65049ae5)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65967
Graph is an implementation detail. If user wants to get access to the
underlying graph, they should be able to explicitly dynamic cast instead.
ghstack-source-id: 141659819
Test Plan: no behavior change.
Reviewed By: gmagogsfm
Differential Revision: D31326153
fbshipit-source-id: a0e984f57c6013494b92a7095bf5bb660035eb84
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65345
FooType::get() can return a const reference. Inconveniently, converting shared_ptr<FooType> to shared_ptr<Type> requires a copy & refcount bump, so to properly take advantage of this in unshapedType() we need to take a const Type& in isSubtypeOf(), which is good practice anyway -- don't require a shared_ptr if you don't need to take ownership.
ghstack-source-id: 140044165
Test Plan:
CI
perf says c10::unshapedType time decreased from 2.8% to 2.2% during static runtime startup, though I expect this to be generally beneficial.
Reviewed By: hlu1
Differential Revision: D31027361
fbshipit-source-id: 676feb81db9f74ad7b8651d8774f4ecb4cfa6ab8
Summary:
This PR is created to replace https://github.com/pytorch/pytorch/pull/53180 PR stack, which has all the review discussions. Reason for needing a replacement is due to a messy Sandcastle issue.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64234
Reviewed By: gmagogsfm
Differential Revision: D30656444
Pulled By: ansley
fbshipit-source-id: 77536c8bcc88162e2c72636026ca3c16891d669a
Summary:
Add `-Wno-writable-strings`(which is clang's flavor of `-Wwrite-strings`) to list of warnings ignored while compiling torch_python.
Avoid unnecessary copies in range loop
Fix number of signed-unsigned comparisons
Found while building locally on M1
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62930
Reviewed By: albanD
Differential Revision: D30171981
Pulled By: malfet
fbshipit-source-id: 25bd43dab5675f927ca707e32737ed178b04651e
Summary:
Make an assert message in Pytorch's JIT provide better information by
printing the debug name of a value in `PythonPrintImpl::useOf` if it's not
found in any tables.
Test Plan:
Tested printing a `module.code` where the module had an invalid value used
as an operand. Before it asserted without any more details, afterwards it
printed the debug name which made it easy to track down the offending value.
Reviewed By: SplitInfinity
Differential Revision: D28856026
fbshipit-source-id: 479f66c458a0a2d9a161ade09f20382e7b19d60e
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os
def get_compiled_files_list():
import json
with open("build/compile_commands.json") as f:
data = json.load(f)
files = [os.path.relpath(node['file']) for node in data]
for idx, fname in enumerate(files):
if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
return files
def run_clang_tidy(fname):
check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
changes = check_output(["git", "ls-files", "-m"])
if len(changes) == 0:
return
check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])
def main():
git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
compiled_files = get_compiled_files_list()
for idx, fname in enumerate(git_files):
if fname not in compiled_files:
continue
if fname.startswith("caffe2/contrib/aten/"):
continue
print(f"[{idx}/{len(git_files)}] Processing {fname}")
run_clang_tidy(fname)
if __name__ == "__main__":
main()
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892
Reviewed By: H-Huang
Differential Revision: D27991944
Pulled By: malfet
fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53410
**Summary**
This commit enables indexing into `ModuleList` using a non-literal
index if the LHS of the assignment statement of which the indexing is
the RHS is annotated with an interface type.
This feature already exists for `ModuleDict`, and this commit builds on
top of that implementation. A `prim::ModuleContainerIndex` operator is
emitted for any statement of the form `lhs: InterfaceType =
module_container[idx]`. The same operator has to be used for both
`ModuleDict` and `ModuleList` because serialization does not preserve
the metadata that indicates whether a `Module` is a `ModuleDict` or
`ModuleList`.
**Testing**
This commit extends the existing unit tests for non-literal `ModuleDict`
indexing to test non-literal `ModuleList` indexing.
**Fixes**
This commit fixes#47496.
Test Plan: Imported from OSS
Reviewed By: gmagogsfm
Differential Revision: D26857597
Pulled By: SplitInfinity
fbshipit-source-id: d56678700a264d79aae3de37ad6b08b080175f7c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50228
`fastmod -m 'expect(<((at|c10)::)?\w+Type>\(\)\s*)->'
'expectRef${1}.'`
Presuming it builds, this is a safe change: the result of `expect()`
wasn't being saved anywhere, so we didn't need it, so we can take a
reference instead of a new `shared_ptr`.
ghstack-source-id: 119782961
Test Plan: CI
Reviewed By: SplitInfinity
Differential Revision: D25837374
fbshipit-source-id: 86757b70b1520e3dbaa141001e7976400cdd3b08
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48868
Building on the previous diff, we can make `toTensor()` return a
`const Tensor&`, which should make it easier to avoid reference
counting.
ghstack-source-id: 119327372
Test Plan: internal benchmarks.
Reviewed By: bwasti
Differential Revision: D25325379
fbshipit-source-id: ca699632901691bcee432f595f75b0a4416d55dd
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49990
**Summary**
This commit removes the forward-compatibility gate for buffer metadata
serialization. It was introduced to allow versions of fbcode
binaries statically linked against older versions of PyTorch (without
buffer metadata in JIT) to deserialize archives produced by new versions
of PyTorch. Enough time has probably passed that these old binaries
don't exist anymore, so it should be safe to remove the gate.
**Test Plan**
Internal tests.
Test Plan: Imported from OSS
Reviewed By: xw285cornell
Differential Revision: D25743199
Pulled By: SplitInfinity
fbshipit-source-id: 58d82ab4362270b309956826e36c8bf9d620f081
Summary:
Pull Request resolved: https://github.com/pytorch/glow/pull/5062
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45556
User defined classes can be used as constants. This is useful when freezing and removing the module from the graph.
Test Plan: waitforsadcastle
Reviewed By: eellison
Differential Revision: D23994974
fbshipit-source-id: 5b4a5c91158aa7f22df39d71f2658afce1d29317
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47775
When serializing graphs, we check every node for named types referenced,
so that we can register them as dependencies. We were skipping this
check for the graph inputs themselves. Since types used at input are
almost always used somewhere in the graph, we never noticed this gap
until a user reported an issue with NamedTuples.
Test Plan: Imported from OSS
Reviewed By: jamesr66a
Differential Revision: D24896289
Pulled By: suo
fbshipit-source-id: 4ce76816cb7997a7b65e7cea152ea52ed8f27276
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45716
**Summary**
This commit enables indexing into `ModuleDict` using a non-literal
index if the `ModuleDict` is annotated with `Dict[str, X]`, where `X` is
a module interface type. These annotations must be expressed using a
class attribute named `__annotations__`, which is a `Dict[str, Type]`
where the keys are the names of module attributes and the values are
their types.
The approach taken by this commit is that these annotations are stored
as "hints" along with the corresponding module attributes in the
`ConcreteSubmoduleTypeBuilder` instance for each module (which might be
a `ModuleDict`). These hints are passed into the `ModuleValue` that is
created for desugaring operations on submodules so that indexing into a
`ModuleDict` can be emitted as a getitem op into a dict emitted into the
graph that represents the `ModuleDict`.
**Test Plan**
This commit adds unit tests to `TestModuleContainers` to test this
feature (`test_typed_module_dict`).
Differential Revision: D24070606
Test Plan: Imported from OSS
Reviewed By: ansley
Pulled By: SplitInfinity
fbshipit-source-id: 6019a7242d53d68fbfc1aa5a49df6cfc0507b992
