Update on "fix embedding_backward_dense decomp with broadcasting"

Fixes #95182

cc soumith voznesenskym yanboliang penguinwu anijain2305 EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng Xia-Weiwen wenzhe-nrv jiayisunx desertfire ngimel for another decomp fix. For this one, I tried auditing the CPU and CUDA kernels for `embedding_backward_dense` and just could not figure out where the `unsqueeze(1)` was supposed to be coming from. In the failing example, our tensor shapes are `(2, 4, 3)` and `(2, 4)`, and so I just assumed that the existing decomp had a typo - we should be unsqueezing the last dim, instead of dim index 1. That fixes the repro, and the existing decomp + meta tests appear to be passing.




cc soumith voznesenskym yanboliang penguinwu anijain2305 EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng Xia-Weiwen wenzhe-nrv jiayisunx desertfire

[ghstack-poisoned]

.ci/docker/android/build.gradle

@@ -53,7 +53,7 @@ dependencies {
     implementation 'androidx.appcompat:appcompat:1.0.0'
     implementation 'com.facebook.fbjni:fbjni-java-only:0.2.2'
     implementation 'com.google.code.findbugs:jsr305:3.0.1'
-    implementation 'com.facebook.soloader:nativeloader:0.10.4'
+    implementation 'com.facebook.soloader:nativeloader:0.10.5'
 
     implementation 'junit:junit:' + rootProject.junitVersion
     implementation 'androidx.test:core:' + rootProject.coreVersion

.github/scripts/trymerge.py

@@ -1195,7 +1195,17 @@ def find_matching_merge_rule(
         reject_reason = f"Rejecting the merge as no rules are defined for the repository in {MERGE_RULE_PATH}"
         raise RuntimeError(reject_reason)
     checks = get_combined_checks_from_pr_and_land_validation(pr, land_check_commit)
-    checks = get_classifications(pr.last_commit()['oid'], pr.get_merge_base(), checks, flaky_rules)
+    base_rev = None
+    try:
+        # is allowed to fail if git is not available
+        base_rev = pr.get_merge_base()
+    except Exception as e:
+        print(
+            f"Failed fetching base git revision for {pr.pr_num}. Skipping additional classifications.\n"
+            f"{type(e)}\n{e}"
+        )
+    if base_rev is not None:
+        checks = get_classifications(pr.last_commit()['oid'], base_rev, checks, flaky_rules)
 
     # PRs can fail multiple merge rules, but it only needs to pass one rule to be approved.
     # If it fails all rules, we need to find the rule that it came closest to passing and report

.github/workflows/mac-mps.yml

@@ -31,6 +31,7 @@ jobs:
       MACOS_SCCACHE_S3_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
 
   macos-12-py3-arm64-mps-test:
+    if: false
     name: macos-12-py3-arm64-mps
     uses: ./.github/workflows/_mac-test-mps.yml
     needs: macos-12-py3-arm64-build

.github/workflows/trunk.yml

@@ -223,12 +223,13 @@ jobs:
     name: macos-12-py3-arm64-mps
     uses: ./.github/workflows/_mac-test-mps.yml
     needs: macos-12-py3-arm64-build
-    if: needs.macos-12-py3-arm64-build.outputs.build-outcome == 'success'
+    if: false && needs.macos-12-py3-arm64-build.outputs.build-outcome == 'success'
     with:
       sync-tag: macos-12-py3-arm64-mps-test
       build-environment: macos-12-py3-arm64
 
   macos-12-py3-arm64-test:
+    if: false
     name: macos-12-py3-arm64
     uses: ./.github/workflows/_mac-test.yml
     needs: macos-12-py3-arm64-build

android/README.md

@@ -111,12 +111,12 @@ dependencies {
     implementation(name:'pytorch_android', ext:'aar')
     implementation(name:'pytorch_android_torchvision', ext:'aar')
     ...
-    implementation 'com.facebook.soloader:nativeloader:0.10.4'
+    implementation 'com.facebook.soloader:nativeloader:0.10.5'
     implementation 'com.facebook.fbjni:fbjni-java-only:0.2.2'
 }
 ```
 We also have to add all transitive dependencies of our aars.
-As `pytorch_android` [depends](https://github.com/pytorch/pytorch/blob/master/android/pytorch_android/build.gradle#L76-L77) on `'com.facebook.soloader:nativeloader:0.10.4'` and `'com.facebook.fbjni:fbjni-java-only:0.2.2'`, we need to add them.
+As `pytorch_android` [depends](https://github.com/pytorch/pytorch/blob/master/android/pytorch_android/build.gradle#L76-L77) on `'com.facebook.soloader:nativeloader:0.10.5'` and `'com.facebook.fbjni:fbjni-java-only:0.2.2'`, we need to add them.
 (In case of using maven dependencies they are added automatically from `pom.xml`).
 
 You can check out [test app example](https://github.com/pytorch/pytorch/blob/master/android/test_app/app/build.gradle) that uses aars directly.

android/build.gradle

@@ -13,7 +13,7 @@ allprojects {
             junitVersion = "4.12"
 
             fbjniJavaOnlyVersion = "0.2.2"
-            soLoaderNativeLoaderVersion = "0.10.4"
+            soLoaderNativeLoaderVersion = "0.10.5"
         }
 
         repositories {

android/test_app/app/build.gradle

@@ -139,7 +139,7 @@ tasks.all { task ->
 
 dependencies {
     implementation 'com.android.support:appcompat-v7:28.0.0'
-    implementation 'com.facebook.soloader:nativeloader:0.10.4'
+    implementation 'com.facebook.soloader:nativeloader:0.10.5'
 
     localImplementation project(':pytorch_android')
     localImplementation project(':pytorch_android_torchvision')
@@ -154,7 +154,7 @@ dependencies {
 
     aarImplementation(name:'pytorch_android', ext:'aar')
     aarImplementation(name:'pytorch_android_torchvision', ext:'aar')
-    aarImplementation 'com.facebook.soloader:nativeloader:0.10.4'
+    aarImplementation 'com.facebook.soloader:nativeloader:0.10.5'
     aarImplementation 'com.facebook.fbjni:fbjni-java-only:0.2.2'
 
     def camerax_version = "1.0.0-alpha05"

aten/src/ATen/FunctionalizeFallbackKernel.cpp

@@ -30,10 +30,7 @@
 namespace {
   void functionalizeFallback(const c10::OperatorHandle& op, c10::DispatchKeySet dispatchKeySet, torch::jit::Stack* stack) {
     const auto& schema = op.schema();
-    TORCH_INTERNAL_ASSERT(
-      !schema.hasAnyAliasInfo(),
-      "mutating and aliasing ops should all have codegen'd kernels. op name: ",
-      op.operator_name().name, ".", op.operator_name().overload_name);
+    TORCH_INTERNAL_ASSERT(!schema.hasAnyAliasInfo(), "mutating and aliasing ops should all have codegen'd kernels");
     const auto num_arguments = schema.arguments().size();
     const auto arguments_begin = stack->size() - num_arguments;
     auto arguments = torch::jit::last(stack, num_arguments);