Changes by apply order:
1. Replace all `".."` and `os.pardir` usage with `os.path.dirname(...)`.
2. Replace nested `os.path.dirname(os.path.dirname(...))` call with `str(Path(...).parent.parent)`.
3. Reorder `.absolute()` ~/ `.resolve()`~ and `.parent`: always resolve the path first.
`.parent{...}.absolute()` -> `.absolute().parent{...}`
4. Replace chained `.parent x N` with `.parents[${N - 1}]`: the code is easier to read (see 5.)
`.parent.parent.parent.parent` -> `.parents[3]`
5. ~Replace `.parents[${N - 1}]` with `.parents[${N} - 1]`: the code is easier to read and does not introduce any runtime overhead.~
~`.parents[3]` -> `.parents[4 - 1]`~
6. ~Replace `.parents[2 - 1]` with `.parent.parent`: because the code is shorter and easier to read.~
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129374
Approved by: https://github.com/justinchuby, https://github.com/malfet
Changes by apply order:
1. Replace all `".."` and `os.pardir` usage with `os.path.dirname(...)`.
2. Replace nested `os.path.dirname(os.path.dirname(...))` call with `str(Path(...).parent.parent)`.
3. Reorder `.absolute()` ~/ `.resolve()`~ and `.parent`: always resolve the path first.
`.parent{...}.absolute()` -> `.absolute().parent{...}`
4. Replace chained `.parent x N` with `.parents[${N - 1}]`: the code is easier to read (see 5.)
`.parent.parent.parent.parent` -> `.parents[3]`
5. ~Replace `.parents[${N - 1}]` with `.parents[${N} - 1]`: the code is easier to read and does not introduce any runtime overhead.~
~`.parents[3]` -> `.parents[4 - 1]`~
6. ~Replace `.parents[2 - 1]` with `.parent.parent`: because the code is shorter and easier to read.~
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129374
Approved by: https://github.com/justinchuby, https://github.com/malfet
Summary:
NNAPI: Internal test infra can't find test_nnapi.py. Easiest solution is to just skip these tests if test_nnapi.py can't be found
test_ivalue: fails due to qscheme op not implemented for CPU backend. In OSS, it doesn't run because it's not included in test_jit.py.
CPU NNC tests: test_working_byte_cpu_float32 is failing, but hard to repro; we don't use CPU NNC internally, so let's just skip CPU NNC tests internally.
Differential Revision: D48041615
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108937
Approved by: https://github.com/eellison
Enabling more tests on ASAN, meanwhile we disable float-divide-by-zero and float-cast-overflow, both are disabled because they are also disabled by default in latest clang.
The following cited doc explains the reasons.
```
-fsanitize=float-cast-overflow: Conversion to, from, or between floating-point types
which would overflow the destination. Because the range of representable values
for all floating-point types supported by Clang is [-inf, +inf], the only cases detected are
conversions from floating point to integer types.
-fsanitize=float-divide-by-zero: Floating point division by zero.
This is undefined per the C and C++ standards,
but is defined by Clang (and by ISO/IEC/IEEE 60559 / IEEE 754) as producing
either an infinity or NaN value,
so is not included in -fsanitize=undefined.
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/103647
Approved by: https://github.com/kit1980
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62272
Added Android NNAPI delegate implementation of runtime initialization (compilation) and execution.
The delegate's preprocess step was [previously implemented](https://github.com/pytorch/pytorch/pull/62225). Now, the reset of the delegate, which implements client-side execution, is added.
**nnapi_backend_lib.cpp**:
Implementation of delegate's compile and execute.
`execute()` is essentially a C++ implementation of [`NnapiModule`](https://github.com/pytorch/pytorch/blob/master/torch/backends/_nnapi/prepare.py), which wraps an NNAPI Compilation and handles preparation of weights, inputs, and outputs.
- Any steps that can be done before execution are moved to `compile()`.
- `init()` cannot be moved to `compile()` because it requires real inputs for dynamic shaping.
- `shape_compute_module` cannot currently be deserialized in `compile()`, since mobile::Module has no IValue conversion.
- Processed arguments that are modified by `init()` must be kept as member variables. Any other processed arguments are passed through a dictionary, `handles`.
**nnapi_bind.cpp & nnapi_bind.h**:
Created a header file for `nnapi_bind.cpp`, so that it's NnapiCompilation class can be used by `nnapi_backend_lib.cpp`.
**test_backend_nnapi.py**:
Enabled execution testing.
ghstack-source-id: 135432844
Test Plan:
Imported from OSS
Tested on devserver.
1. Load and unpack a special devserver build of NNAPI: `jf download GICWmAAzUR0eo20TAPasVts8ObhobsIXAAAz --file "nnapi-host-linux.tar.xz"`
2. `export LIBNEURALNETWORKS_PATH=/path/to/libneuralnetworks.so`
3. Run unittests: `python test/test_jit.py TestNnapiBackend` and `python test/test_nnapi.py`
TODO: test with lite interpreter runtime
Reviewed By: raziel, iseeyuan
Differential Revision: D29944873
fbshipit-source-id: 48967d873e79ef2cce9bcba2aeea3c52f7a18c07
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62213
Added sanity checks in preprocess function for Android NNAPI delegate.
`preprocess()` requires some input metadata passed through its `method_compile_spec` function argument.
`preprocess()` now throws specific error messages, if it cannot find the correct input arguments.
Example error message:
```
RuntimeError: method_compile_spec does not contain the "forward" key.
method_compile_spec should contain a Tensor or Tensor List which bundles input parameters: shape, dtype, quantization, and dimorder.
For input shapes, use 0 for run/load time flexible input.
method_compile_spec must use the following format: {"forward": {"inputs": at::Tensor}} OR {"forward": {"inputs": c10::List<at::Tensor>}}
```
nnapi_backend_preprocess.cpp: contains sanity check implementation
test_backend_nnapi.py: sanity check unit tests
Test: Ran `python test/test_jit.py TestNnapiBackend` in OSS successfully.
TODO: Using Tensors to pass input parameters is a temporary hack. When a dedicated object is implemented, update the sanity check error message.
ghstack-source-id: 134339282
Test Plan: Ran `python test/test_jit.py TestNnapiBackend` in OSS successfully.
Reviewed By: raziel, iseeyuan
Differential Revision: D29917004
fbshipit-source-id: 0d5c6b35889c556cda905ffc29c25c5422ae9ee4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61782
This PR depends on https://github.com/pytorch/pytorch/pull/61787
### Summary:
Added more comprehensive tests for Android NNAPI delegate.
Previously, there was only one basic test for lowering a PReLU module with the NNAPI delegate. Now, more tests are inherited from `test_nnapi.py`, the file for testing NNAPI conversion and execution without the delegate.
**test_backend_nnapi.py**
Test file for Android NNAPI delegate.
- `TestNnapiBackend` class inherits tests from `test_nnapi.py` and overrides the model conversion to use the delegate API.
- Includes an extra test for passing input arguments as Tensors and Tensor Lists.
- Has extra set up for loading the NNAPI delegate library and changing the default dtype from float64 to float32 (dtype is typically float32 by default, but not in delegate backend unit tests)
**test_nnapi.py**
Test file for Android NNAPI without the delegate.
- Some code was refactored to allow override of only the NNAPI conversion call.
- An extra function was added to allow the NNAPI delegate unit test to turn off the model execution step. Once the NNAPI delegate's execution implementation is complete, this may no longer be necessary.
### Test Plan:
I ran `python test/test_jit.py TestNnapiBackend` and `python test/test_nnapi.py` to run both test files.
Test Plan: Imported from OSS
Reviewed By: raziel, iseeyuan
Differential Revision: D29772005
fbshipit-source-id: 5d14067a4f6081835699b87a2ece5bd6bed00c6b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61878
CMakeLists.txt
Android NNAPI delegate library was moved from test/cpp/jit/CMakeLists.txt to torch/CMakeLists.txt. This resolves the issue the original PR had, where the NNAPI delegate library was added to builds without Python (when it depends on Python).
Original PR: https://github.com/pytorch/pytorch/pull/61594
There's an error where the library cannot be built on MacOS. This problem existed in the original PR as well, but now an issue has been created: https://github.com/pytorch/pytorch/issues/61930
test_backend_nnapi.py
Also changed the skip unit test headers so that it's a little cleaner. Now the unit tests are skipped if the Nnapi delegate library file is not found. Previously, the skip was based on the platform (only allowing Linux).
Test Plan:
To run NNAPI delegate unit tests: `python test/test_jit.py TestNnapiBackend`
Imported from OSS
Reviewed By: iseeyuan
Differential Revision: D29799895
fbshipit-source-id: b69a767b5cde3814b0853cfbc84d61ab4155f619
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61594
### Summary:
Added a unit test for the Nnapi delegate's preprocess() function. The
function was previously tested locally, but now a basic test is
added for OSS.
See https://github.com/pytorch/pytorch/pull/61499 for preprocess
implementation. See D29647123 for local testing.
**TODO:**
Add more comprehensive tests.
Add tests for model execution, after the Nnapi delegate's initialization
and execution is implemented T91991928.
**CMakeLists.txt:**
Added a library for the Nnapi delegate
- Explicit linking of torch_python is necessary for the Nnapi delegate's use of pybind
**test_backends.py:**
Added a test for lowering to Nnapi
- Based off https://github.com/pytorch/pytorch/blob/master/test/test_nnapi.py
- Only differences are the loading of the nnapi backend library and the need to change dtype from float64 to float32
### Test Plan:
Running `python test/test_jit.py TestBackendsWithCompiler -v` succeeds. Also saved and examined the model file locally.
Test Plan: Imported from OSS
Reviewed By: iseeyuan
Differential Revision: D29687143
fbshipit-source-id: 9ba9e57f7f856e5ac15e13527f6178d613b32802
