Summary:
Since `c10::ArrayRef` now support `c10::ArrayRef<const T>`, let's restore `ComputePostOrder` to accept `const Node*` again, which is more suitable for the context of the given helpers.
Test Plan:
CI.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/88773
Approved by: https://github.com/JackCaoG
Next stage of breaking up https://github.com/pytorch/pytorch/pull/74710
IR builder class introduced to decouple the explicit usage of `TsNode` in core lazy tensors.
Requires https://github.com/pytorch/pytorch/pull/75324 to be merged in first.
**Background**
- there are ~ 5 special ops used in lazy core but defined as :public {Backend}Node. (DeviceData, Expand, Scalar...)
- we currently require all nodes derive from {Backend}Node, so that backends can make this assumption safely
- it is hard to have shared 'IR classes' in core/ because they depend on 'Node'
**Motivation**
1. avoid copy-paste of "special" node classes for each backend
2. in general decouple and remove all dependencies that LTC has on the TS backend
**Summary of changes**
- new 'IRBuilder' interface that knows how to make 5 special ops
- move 'special' node classes to `ts_backend/`
- implement TSIRBuilder that makes the special TS Nodes
- new backend interface API to get the IRBuilder
- update core code to call the builder
CC: @wconstab @JackCaoG @henrytwo
Partially Fixes#74628
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75433
Approved by: https://github.com/wconstab
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75292
- Follow the convention in [this doc](https://docs.google.com/document/d/1Vi96ITGoK7BW01ZEccexs4pvCQKF4_LdV8w7TfIWPvM/edit) to setup config for ltc force fallback ops.
- Pybinds are added to read/set the config.
- Use the added pybinds in the unit test which needs to force fallbacks.
Test Plan:
```
pytest test/lazy/test_extract_compiled_graph.py
```
Reviewed By: malfet
Differential Revision: D35417678
Pulled By: shunting314
fbshipit-source-id: 1e05b8c831174872d70257a0ddd958863d6ca80d
(cherry picked from commit 9366bde7ef20837dcf03b7d8e18f9017a58c80fa)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75237
applies 'OVRSOURCE' logic to one more place missed in D35331263 (8b7e2bf7a6) so that lazy TS backend is not compiled in internal builds
Test Plan: CI
Reviewed By: malfet, shunting314
Differential Revision: D35377758
fbshipit-source-id: 5dcd3d36e50a8917470a917f2120353972dc31ba
(cherry picked from commit 8b8ed7bdaa553eec2ef8b5461d1bd867979049dd)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75046
Merge the code needed for dynamic+ltc integration from the staging branch to the master branch.
Test Plan:
Unit test
```
pytest test_extract_compiled_graph
```
test thru dynamo
```
LTC_TS_CUDA=1 time python torchbench.py --speedup-ltc -dcuda --nvfuser --randomize-input --only <model name>
```
Reviewed By: alanwaketan
Differential Revision: D35300646
Pulled By: shunting314
fbshipit-source-id: 09ed20d3bb8ef80e4b93ba87ea3356a07d2dccdb
(cherry picked from commit 2b56771cdfd2cfa825c65ee9fd42338fb372fb32)
Summary:
This adds a minimal set of python bindings for lazy tensor and the torchscript backend.
It targets the APIs that are used by the `test_ts_opinfo.py` test (which it also lands, from lazy_tensor_staging, where it is [lazy_tensor_core/test/test_lazy.py](https://github.com/pytorch/pytorch/blob/lazy_tensor_staging/lazy_tensor_core/test/test_lazy.py)).
We should land more python bindings obviously. I just wanted to focus on a minimal set that can also be tested, and use it to agree on how we organize the bindings, then others could easily contribute bindings on top of this infrastructure.
cc JackCaoG
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74508
Reviewed By: pbelevich
Differential Revision: D35032152
Pulled By: wconstab
fbshipit-source-id: 526505ab355b7ad27037ece0ff814b2a4b69f1e2
(cherry picked from commit b4f73dd147472cb38003204aff228087c0230fda)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72607
since python isn't available from libtorch, most of lazy tensor
code can't depend on python.
separate python_util into libtorch_python library
make debug_util and IR dump work with or without python by providing
a default function for 'maybe getting python stacktrace' that returns
an empty stacktrace
use a registration mechanism on libtorch_python library load to update
the 'maybe' function to use the real python stacktrace getter
Test Plan:
OSS build tests:
- test_ptltc by itself works
- LTC_SAVE_TENSORS_FILE=log test_ptltc works, and log contains
empty stacktrces
- python examply.py by itself works
- LTC_SAVE_TENSORS_FILE=log test_ptltc works, and log contains
real stacktraces
fbcode build: rely on CI to run test/lazy
Reviewed By: desertfire
Differential Revision: D34115046
fbshipit-source-id: 8d6222963c146da36b3c1b5ff8a638bbc3f1442e
(cherry picked from commit 3717688ade)
