This pr
moved some model generation scripts to a central place (mobile net v2, android test model)
updated scripts so these models can run on Android (Java doesn't support certain scalar types as return value)
updated model generation script to take arguments (generate models for android/ios, checked-in model or on-the-fly model)
add Android instrumentation tests for these new models
After this change, the Android instrumentation test will run 35 models which covered 91% of production ops. The coverage information can be found in this file: https://github.com/pytorch/pytorch/blob/master/test/mobile/model_test/coverage.yaml
Note that these models are checked-in for back compatibility check (to ensure they can run with newer pytorch versions).
The script generates models for mobile test. For each model we have a "checked-in" version
and an "on-the-fly" version. The "on-the-fly" version will be generated during test, and
should not be committed to the repo. The "checked-in" version is used for back compatibility check.
Note that Android only support checked-in model right now. iOS can test both (in another pr).
use 'gen_test_model.py android-test' to generate on the fly models for android
use 'gen_test_model.py ios-test' to generate on the fly models for ios
use 'python gen_test_model.py android' to generate checked-in models for android
use 'python gen_test_model.py ios' to generate on-the-fly models for ios
use 'gen_test_model.py <model_name_no_suffix>' to update the given checked-in model
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74793
Approved by: https://github.com/kit1980
Summary: Android only support a few scalar types as model return value. This diff improved the error message so user can know which type is not supported.
Test Plan: verified unsupported scalar type is printed
Differential Revision: D35104788
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74660
Approved by: https://github.com/kit1980
Added tests for lite interpreter. By default the run_test.sh will use lite interpreter, unless manually set BUILD_LITE_INTERPRETER=0
Also fixed model generation script for android instrumentation test and README.
Verified test can pass for both full jit and lite interpreter. Also tested on emulator and real device using different abis.
Lite interpreter
```
./scripts/build_pytorch_android.sh x86
./android/run_tests.sh
```
Full JIT
```
BUILD_LITE_INTERPRETER=0 ./scripts/build_pytorch_android.sh x86
BUILD_LITE_INTERPRETER=0 ./android/run_tests.sh
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72736
The android build script (./scripts/build_pytorch_android.sh) is broken if user didn't provide the abi list.
./scripts/build_pytorch_android.sh ==> failed due to the so file for armv7 cannot be found
./scripts/build_pytorch_android.sh x86,x86_64 ==> works
This is because by default we will build 4 ABIs:
0ca0e02685/android/gradle.properties (L1)
but only one is provided in this script.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73063
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71508
"==" is the more universal way to test type equalities, and also ::get() doesn't incur any refcount overhead now, so we can swtich to == instead of relying on type kinds.
ghstack-source-id: 147353057
Test Plan:
CI
buck test xplat/caffe2/android:pytorch_jni_common_test
Differential Revision: D33672433
fbshipit-source-id: 5973fd40de48b8017b5c3ebaa55bcf5b4b391aa3
(cherry picked from commit db84a4b566d1f2f17cda8785e11bc11739e6f50c)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69421
I've hit a lot of build issues in D32671972, and I've come to realize that a lot of it boils down to header hygene. `function.h` includes `profiler.h` *solely* to transitively include `record_function.h` which winds up leaking the profiler symbols. Moreover several files are relying on transitive includes to get access to `getTime`. As long as I have to touch all the places that use `getTime`, I may as well also move them to the new namespace.
Test Plan: Unit tests and CI.
Reviewed By: aaronenyeshi, albanD
Differential Revision: D32865907
fbshipit-source-id: f87d6fd5afb784dca2146436e72c69e34623020e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66741
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
Test Plan: Sandcastle
Reviewed By: ngimel
Differential Revision: D31705360
fbshipit-source-id: 7115f76e381ad2d98584eb534961c3cbb957ebaa
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66234
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
bypass_size_limit
allow-large-files
Test Plan: Sandcastle
Reviewed By: ngimel
Differential Revision: D30652629
fbshipit-source-id: 0ae6c4bbbb554bad42e372792a6430e1acf15e3e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64602
print type name in error message for easier debugging.
Test Plan:
Example:
java.lang.IllegalStateException: Expected IValue type Tensor, actual type TensorList
Reviewed By: beback4u
Differential Revision: D30782318
fbshipit-source-id: 60d88a659e7b4bb2b574b12c7652a28f0d5ad0d2
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62419
This diff adds support for cpu only kineto profiler on mobile. Thus
enabling chrome trace generation on mobile. This bring cpp API for
mobile profiling on part with Torchscript.
This is done via:
1. Utilizating debug handle annotations in KinetoEvent.
2. Adding post processing capability, via callbacks, to
KinetoThreadLocalState
3. Creating new RAII stype profiler, KinetoEdgeCPUProfiler, which can be
used in surrounding scope of model execution. This will write chrome
trace to the location specified in profiler constructor.
Test Plan:
MobileProfiler.ModuleHierarchy
Imported from OSS
Reviewed By: raziel
Differential Revision: D29993660
fbshipit-source-id: 0b44f52f9e9c5f5aff81ebbd9273c254c3c03299
Summary:
Also fix `TestProducerVersion` by removing assumption that major and minor are single digit
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59345
Reviewed By: robieta
Differential Revision: D28853720
Pulled By: malfet
fbshipit-source-id: 4b6d03c6b0c9d652a5aef792aaa84eaa522d10e8
Summary:
I build using [Bazel](https://bazel.build/).
When I use `pytorch_android` in latest Android app, I get the following error due to dependencies:
```
$ bazel build //app/src/main:app
WARNING: API level 30 specified by android_ndk_repository 'androidndk' is not available. Using latest known API level 29
INFO: Analyzed target //app/src/main:app (0 packages loaded, 0 targets configured).
INFO: Found 1 target...
ERROR: /home/H1Gdev/android-bazel-app/app/src/main/BUILD.bazel:3:15: Merging manifest for //app/src/main:app failed: (Exit 1): ResourceProcessorBusyBox failed: error executing command bazel-out/k8-opt-exec-2B5CBBC6/bin/external/bazel_tools/src/tools/android/java/com/google/devtools/build/android/ResourceProcessorBusyBox --tool MERGE_MANIFEST -- --manifest ... (remaining 11 argument(s) skipped)
Use --sandbox_debug to see verbose messages from the sandbox ResourceProcessorBusyBox failed: error executing command bazel-out/k8-opt-exec-2B5CBBC6/bin/external/bazel_tools/src/tools/android/java/com/google/devtools/build/android/ResourceProcessorBusyBox --tool MERGE_MANIFEST -- --manifest ... (remaining 11 argument(s) skipped)
Use --sandbox_debug to see verbose messages from the sandbox
Error: /home/H1Gdev/.cache/bazel/_bazel_H1Gdev/29e18157a4334967491de4cc9a879dc0/sandbox/linux-sandbox/914/execroot/__main__/app/src/main/AndroidManifest.xml:19:18-86 Error:
Attribute application@appComponentFactory value=(androidx.core.app.CoreComponentFactory) from [maven//:androidx_core_core] AndroidManifest.xml:19:18-86
is also present at [maven//:com_android_support_support_compat] AndroidManifest.xml:19:18-91 value=(android.support.v4.app.CoreComponentFactory).
Suggestion: add 'tools:replace="android:appComponentFactory"' to <application> element at AndroidManifest.xml:5:5-19:19 to override.
May 19, 2021 10:45:03 AM com.google.devtools.build.android.ManifestMergerAction main
SEVERE: Error during merging manifests
com.google.devtools.build.android.AndroidManifestProcessor$ManifestProcessingException: Manifest merger failed : Attribute application@appComponentFactory value=(androidx.core.app.CoreComponentFactory) from [maven//:androidx_core_core] AndroidManifest.xml:19:18-86
is also present at [maven//:com_android_support_support_compat] AndroidManifest.xml:19:18-91 value=(android.support.v4.app.CoreComponentFactory).
Suggestion: add 'tools:replace="android:appComponentFactory"' to <application> element at AndroidManifest.xml:5:5-19:19 to override.
at com.google.devtools.build.android.AndroidManifestProcessor.mergeManifest(AndroidManifestProcessor.java:186)
at com.google.devtools.build.android.ManifestMergerAction.main(ManifestMergerAction.java:217)
at com.google.devtools.build.android.ResourceProcessorBusyBox$Tool$5.call(ResourceProcessorBusyBox.java:93)
at com.google.devtools.build.android.ResourceProcessorBusyBox.processRequest(ResourceProcessorBusyBox.java:233)
at com.google.devtools.build.android.ResourceProcessorBusyBox.main(ResourceProcessorBusyBox.java:177)
Warning:
See http://g.co/androidstudio/manifest-merger for more information about the manifest merger.
Target //app/src/main:app failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 2.221s, Critical Path: 1.79s
INFO: 2 processes: 2 internal.
FAILED: Build did NOT complete successfully
```
This is due to conflict between `AndroidX` and `Support Library` on which `pytorch_android_torch` depends.
(In the case of `Gradle`, it is avoided by `android.useAndroidX`.)
I created [Android application](https://github.com/H1Gdev/android-bazel-app) for comparison.
At first, I updated `AppCompat` from `Support Library` to `AndroidX`, but `pytorch_android` and `pytorch_android_torchvision` didn't seem to need any dependencies, so I removed dependencies.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58527
Reviewed By: xta0
Differential Revision: D28585234
Pulled By: IvanKobzarev
fbshipit-source-id: 78aa6b1525543594ae951a6234dd88a3fdbfc062
Summary:
Build lite interpreter as default for android, should wait until https://github.com/pytorch/pytorch/pull/56002 lands
Mainly two changes:
1. Use lite interpreter as default for Android
2. Switch the lite interpreter build test to full jit build test
Test Plan: Imported from OSS
Differential Revision: D27695530
Reviewed By: IvanKobzarev
Pulled By: cccclai
fbshipit-source-id: e1b2c70fee6590accc22c7404b9dd52c7d7c36e2
Summary:
Switching pytorch android to use fbjni from prefab dependencies
Bumping version of fbjni to 0.2.2
soloader version to 0.10.1
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55066
Reviewed By: dreiss
Differential Revision: D27469727
Pulled By: IvanKobzarev
fbshipit-source-id: 2ab22879e81c9f2acf56807c6a133b0ca20bb40a
Summary:
*Context:* https://github.com/pytorch/pytorch/issues/53406 added a lint for trailing whitespace at the ends of lines. However, in order to pass FB-internal lints, that PR also had to normalize the trailing newlines in four of the files it touched. This PR adds an OSS lint to normalize trailing newlines.
The changes to the following files (made in 54847d0adb9be71be4979cead3d9d4c02160e4cd) are the only manually-written parts of this PR:
- `.github/workflows/lint.yml`
- `mypy-strict.ini`
- `tools/README.md`
- `tools/test/test_trailing_newlines.py`
- `tools/trailing_newlines.py`
I would have liked to make this just a shell one-liner like the other three similar lints, but nothing I could find quite fit the bill. Specifically, all the answers I tried from the following Stack Overflow questions were far too slow (at least a minute and a half to run on this entire repository):
- [How to detect file ends in newline?](https://stackoverflow.com/q/38746)
- [How do I find files that do not end with a newline/linefeed?](https://stackoverflow.com/q/4631068)
- [How to list all files in the Git index without newline at end of file](https://stackoverflow.com/q/27624800)
- [Linux - check if there is an empty line at the end of a file [duplicate]](https://stackoverflow.com/q/34943632)
- [git ensure newline at end of each file](https://stackoverflow.com/q/57770972)
To avoid giving false positives during the few days after this PR is merged, we should probably only merge it after https://github.com/pytorch/pytorch/issues/54967.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54737
Test Plan:
Running the shell script from the "Ensure correct trailing newlines" step in the `quick-checks` job of `.github/workflows/lint.yml` should print no output and exit in a fraction of a second with a status of 0. That was not the case prior to this PR, as shown by this failing GHA workflow run on an earlier draft of this PR:
- https://github.com/pytorch/pytorch/runs/2197446987?check_suite_focus=true
In contrast, this run (after correcting the trailing newlines in this PR) succeeded:
- https://github.com/pytorch/pytorch/pull/54737/checks?check_run_id=2197553241
To unit-test `tools/trailing_newlines.py` itself (this is run as part of our "Test tools" GitHub Actions workflow):
```
python tools/test/test_trailing_newlines.py
```
Reviewed By: malfet
Differential Revision: D27409736
Pulled By: samestep
fbshipit-source-id: 46f565227046b39f68349bbd5633105b2d2e9b19
Summary:
The link in the README was broken
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54434
Reviewed By: ailzhang
Differential Revision: D27328733
Pulled By: nairbv
fbshipit-source-id: 12ebb6f66983f9348a90b9738fbd9f3f2660c2d1
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48990
Introducing TensorImageUtils methods to prepare tensors in channelsLast MemoryFormat.
ChannlesLast is preferred for performance.
Not to introduce api breaking changes, adding additional parameter MemoryFormat which is CONTIGUOUS by default.
Testing by checking test_app that uses this call
```
gradle -p android installMnetLocalBaseDebug -PABI_FILTERS=arm64-v8a
```
Test Plan: Imported from OSS
Reviewed By: jeffxtang
Differential Revision: D27173940
Pulled By: IvanKobzarev
fbshipit-source-id: 27788082d2c8b190323eadcf18de25d2c3b5e1f1
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53567
Updating gradle to version 6.8.3
Proper zip was uploaded to aws.
Successful CI check: https://github.com/pytorch/pytorch/pull/53619
Test Plan: Imported from OSS
Reviewed By: dreiss
Differential Revision: D26928885
Pulled By: IvanKobzarev
fbshipit-source-id: b1081052967d9080cd6934fd48c4dbe933630e49
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51419
## Summary
1. Add an option `BUILD_LITE_INTERPRETER` in `caffe2/CMakeLists.txt` and set `OFF` as default.
2. Update 'build_android.sh' with an argument to swtich `BUILD_LITE_INTERPRETER`, 'OFF' as default.
3. Add a mini demo app `lite_interpreter_demo` linked with `libtorch` library, which can be used for quick test.
## Test Plan
Built lite interpreter version of libtorch and test with Image Segmentation demo app ([android version](https://github.com/pytorch/android-demo-app/tree/master/ImageSegmentation)/[ios version](https://github.com/pytorch/ios-demo-app/tree/master/ImageSegmentation))
### Android
1. **Prepare model**: Prepare the lite interpreter version of model by run the script below to generate the scripted model `deeplabv3_scripted.pt` and `deeplabv3_scripted.ptl`
```
import torch
model = torch.hub.load('pytorch/vision:v0.7.0', 'deeplabv3_resnet50', pretrained=True)
model.eval()
scripted_module = torch.jit.script(model)
# Export full jit version model (not compatible lite interpreter), leave it here for comparison
scripted_module.save("deeplabv3_scripted.pt")
# Export lite interpreter version model (compatible with lite interpreter)
scripted_module._save_for_lite_interpreter("deeplabv3_scripted.ptl")
```
2. **Build libtorch lite for android**: Build libtorch for android for all 4 android abis (armeabi-v7a, arm64-v8a, x86, x86_64) `BUILD_LITE_INTERPRETER=1 ./scripts/build_pytorch_android.sh`. This pr is tested on Pixel 4 emulator with x86, so use cmd `BUILD_LITE_INTERPRETER=1 ./scripts/build_pytorch_android.sh x86` to specify abi to save built time. After the build finish, it will show the library path:
```
...
BUILD SUCCESSFUL in 55s
134 actionable tasks: 22 executed, 112 up-to-date
+ find /Users/chenlai/pytorch/android -type f -name '*aar'
+ xargs ls -lah
-rw-r--r-- 1 chenlai staff 13M Feb 11 11:48 /Users/chenlai/pytorch/android/pytorch_android/build/outputs/aar/pytorch_android-release.aar
-rw-r--r-- 1 chenlai staff 36K Feb 9 16:45 /Users/chenlai/pytorch/android/pytorch_android_torchvision/build/outputs/aar/pytorch_android_torchvision-release.aar
```
3. **Use the PyTorch Android libraries built from source in the ImageSegmentation app**: Create a folder 'libs' in the path, the path from repository root will be `ImageSegmentation/app/libs`. Copy `pytorch_android-release` to the path `ImageSegmentation/app/libs/pytorch_android-release.aar`. Copy 'pytorch_android_torchvision` (downloaded from [here](https://oss.sonatype.org/#nexus-search;quick~torchvision_android)) to the path `ImageSegmentation/app/libs/pytorch_android_torchvision.aar` Update the `dependencies` part of `ImageSegmentation/app/build.gradle` to
```
dependencies {
implementation 'androidx.appcompat:appcompat:1.2.0'
implementation 'androidx.constraintlayout:constraintlayout:2.0.2'
testImplementation 'junit:junit:4.12'
androidTestImplementation 'androidx.test.ext:junit:1.1.2'
androidTestImplementation 'androidx.test.espresso:espresso-core:3.3.0'
implementation(name:'pytorch_android-release', ext:'aar')
implementation(name:'pytorch_android_torchvision', ext:'aar')
implementation 'com.android.support:appcompat-v7:28.0.0'
implementation 'com.facebook.fbjni:fbjni-java-only:0.0.3'
}
```
Update `allprojects` part in `ImageSegmentation/build.gradle` to
```
allprojects {
repositories {
google()
jcenter()
flatDir {
dirs 'libs'
}
}
}
```
4. **Update model loader api**: Update `ImageSegmentation/app/src/main/java/org/pytorch/imagesegmentation/MainActivity.java` by
4.1 Add new import: `import org.pytorch.LiteModuleLoader;`
4.2 Replace the way to load pytorch lite model
```
// mModule = Module.load(MainActivity.assetFilePath(getApplicationContext(), "deeplabv3_scripted.pt"));
mModule = LiteModuleLoader.load(MainActivity.assetFilePath(getApplicationContext(), "deeplabv3_scripted.ptl"));
```
5. **Test app**: Build and run the ImageSegmentation app in Android Studio,
### iOS
1. **Prepare model**: Same as Android.
2. **Build libtorch lite for ios** `BUILD_PYTORCH_MOBILE=1 IOS_PLATFORM=SIMULATOR BUILD_LITE_INTERPRETER=1 ./scripts/build_ios.sh`
3. **Remove Cocoapods from the project**: run `pod deintegrate`
4. **Link ImageSegmentation demo app with the custom built library**:
Open your project in XCode, go to your project Target’s **Build Phases - Link Binaries With Libraries**, click the **+** sign and add all the library files located in `build_ios/install/lib`. Navigate to the project **Build Settings**, set the value **Header Search Paths** to `build_ios/install/include` and **Library Search Paths** to `build_ios/install/lib`.
In the build settings, search for **other linker flags**. Add a custom linker flag below
```
-all_load
```
Finally, disable bitcode for your target by selecting the Build Settings, searching for Enable Bitcode, and set the value to No.
**
5. Update library and api**
5.1 Update `TorchModule.mm``
To use the custom built libraries the project, replace `#import <LibTorch/LibTorch.h>` (in `TorchModule.mm`) which is needed when using LibTorch via Cocoapods with the code below:
```
//#import <LibTorch/LibTorch.h>
#include "ATen/ATen.h"
#include "caffe2/core/timer.h"
#include "caffe2/utils/string_utils.h"
#include "torch/csrc/autograd/grad_mode.h"
#include "torch/script.h"
#include <torch/csrc/jit/mobile/function.h>
#include <torch/csrc/jit/mobile/import.h>
#include <torch/csrc/jit/mobile/interpreter.h>
#include <torch/csrc/jit/mobile/module.h>
#include <torch/csrc/jit/mobile/observer.h>
```
5.2 Update `ViewController.swift`
```
// if let filePath = Bundle.main.path(forResource:
// "deeplabv3_scripted", ofType: "pt"),
// let module = TorchModule(fileAtPath: filePath) {
// return module
// } else {
// fatalError("Can't find the model file!")
// }
if let filePath = Bundle.main.path(forResource:
"deeplabv3_scripted", ofType: "ptl"),
let module = TorchModule(fileAtPath: filePath) {
return module
} else {
fatalError("Can't find the model file!")
}
```
### Unit test
Add `test/cpp/lite_interpreter`, with one unit test `test_cores.cpp` and a light model `sequence.ptl` to test `_load_for_mobile()`, `bc.find_method()` and `bc.forward()` functions.
### Size:
**With the change:**
Android:
x86: `pytorch_android-release.aar` (**13.8 MB**)
IOS:
`pytorch/build_ios/install/lib` (lib: **66 MB**):
```
(base) chenlai@chenlai-mp lib % ls -lh
total 135016
-rw-r--r-- 1 chenlai staff 3.3M Feb 15 20:45 libXNNPACK.a
-rw-r--r-- 1 chenlai staff 965K Feb 15 20:45 libc10.a
-rw-r--r-- 1 chenlai staff 4.6K Feb 15 20:45 libclog.a
-rw-r--r-- 1 chenlai staff 42K Feb 15 20:45 libcpuinfo.a
-rw-r--r-- 1 chenlai staff 39K Feb 15 20:45 libcpuinfo_internals.a
-rw-r--r-- 1 chenlai staff 1.5M Feb 15 20:45 libeigen_blas.a
-rw-r--r-- 1 chenlai staff 148K Feb 15 20:45 libfmt.a
-rw-r--r-- 1 chenlai staff 44K Feb 15 20:45 libpthreadpool.a
-rw-r--r-- 1 chenlai staff 166K Feb 15 20:45 libpytorch_qnnpack.a
-rw-r--r-- 1 chenlai staff 384B Feb 15 21:19 libtorch.a
-rw-r--r-- 1 chenlai staff **60M** Feb 15 20:47 libtorch_cpu.a
```
`pytorch/build_ios/install`:
```
(base) chenlai@chenlai-mp install % du -sh *
14M include
66M lib
2.8M share
```
**Master (baseline):**
Android:
x86: `pytorch_android-release.aar` (**16.2 MB**)
IOS:
`pytorch/build_ios/install/lib` (lib: **84 MB**):
```
(base) chenlai@chenlai-mp lib % ls -lh
total 172032
-rw-r--r-- 1 chenlai staff 3.3M Feb 17 22:18 libXNNPACK.a
-rw-r--r-- 1 chenlai staff 969K Feb 17 22:18 libc10.a
-rw-r--r-- 1 chenlai staff 4.6K Feb 17 22:18 libclog.a
-rw-r--r-- 1 chenlai staff 42K Feb 17 22:18 libcpuinfo.a
-rw-r--r-- 1 chenlai staff 1.5M Feb 17 22:18 libeigen_blas.a
-rw-r--r-- 1 chenlai staff 44K Feb 17 22:18 libpthreadpool.a
-rw-r--r-- 1 chenlai staff 166K Feb 17 22:18 libpytorch_qnnpack.a
-rw-r--r-- 1 chenlai staff 384B Feb 17 22:19 libtorch.a
-rw-r--r-- 1 chenlai staff 78M Feb 17 22:19 libtorch_cpu.a
```
`pytorch/build_ios/install`:
```
(base) chenlai@chenlai-mp install % du -sh *
14M include
84M lib
2.8M share
```
Test Plan: Imported from OSS
Reviewed By: iseeyuan
Differential Revision: D26518778
Pulled By: cccclai
fbshipit-source-id: 4503ffa1f150ecc309ed39fb0549e8bd046a3f9c
