Update base for Update on "[ET-VK] Add support for binary symint ops"

## Changes

* Add an implementation for binary operators which add symbolic integers.

## Motivation

Support executing llama models with dynamic shapes. This operator shows up when exporting with dynamic shapes.

Differential Revision: [D75238029](https://our.internmc.facebook.com/intern/diff/D75238029/)

[ghstack-poisoned]

Author: SS-JIA

.github/scripts/label_utils.py

@@ -22,9 +22,7 @@
 
 LABEL_ERR_MSG_TITLE = "This PR needs a `release notes:` label"
 LABEL_ERR_MSG = f"""# {LABEL_ERR_MSG_TITLE}
-If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with `release notes:`.
-
-If not, please add the `release notes: none` label.
+If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with `release notes:`. This helps us keep track and include your important work in the next release notes.
 
 To add a label, you can comment to pytorchbot, for example
 `@pytorchbot label "release notes: none"`

.github/scripts/trymerge.py

@@ -59,12 +59,7 @@
     patterns_to_regex,
     retries_decorator,
 )
-from label_utils import (
-    gh_add_labels,
-    gh_remove_label,
-    has_required_labels,
-    LABEL_ERR_MSG,
-)
+from label_utils import gh_add_labels, gh_remove_label
 from trymerge_explainer import get_revert_message, TryMergeExplainer
 
 # labels
@@ -2116,9 +2111,6 @@ def merge(
     # Check for approvals
     find_matching_merge_rule(pr, repo, skip_mandatory_checks=True)
 
-    if not has_required_labels(pr):
-        raise RuntimeError(LABEL_ERR_MSG.lstrip(" #"))
-
     if ignore_current:
         checks = pr.get_checkrun_conclusions()
         _, failing, _ = categorize_checks(

.github/workflows/check-labels.yml

@@ -51,4 +51,4 @@ jobs:
           PR_NUM: ${{ github.event.number || github.event.inputs.pr_number }}
         run: |
           set -ex
-          python3 .github/scripts/check_labels.py --exit-non-zero "${PR_NUM}"
+          python3 .github/scripts/check_labels.py "${PR_NUM}"

.github/workflows/trunk.yml

@@ -305,7 +305,7 @@ jobs:
         # Install requirements
         ${CONDA_RUN} sh install_requirements.sh
         ${CONDA_RUN} sh backends/apple/coreml/scripts/install_requirements.sh
-        ${CONDA_RUN} python install_executorch.py --pybind coreml
+        ${CONDA_RUN} python install_executorch.py
         ${CONDA_RUN} sh examples/models/llama/install_requirements.sh
 
         # Test ANE llama

CMakePresets.json

@@ -15,7 +15,7 @@
         "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/third-party/ios-cmake/ios.toolchain.cmake",
         "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/macos.cmake",
         "PLATFORM": "MAC_ARM64",
-        "DEPLOYMENT_TARGET": "10.15"
+        "DEPLOYMENT_TARGET": "12.0"
       },
       "condition": {
         "lhs": "${hostSystemName}",
@@ -77,7 +77,7 @@
       "inherits": ["common"],
       "cacheVariables": {
         "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/pybind.cmake",
-        "CMAKE_OSX_DEPLOYMENT_TARGET": "10.15"
+        "CMAKE_OSX_DEPLOYMENT_TARGET": "12.0"
       },
       "condition": {
         "type": "inList",
@@ -93,7 +93,7 @@
         ],
         "cacheVariables": {
             "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/llm.cmake",
-            "CMAKE_OSX_DEPLOYMENT_TARGET": "10.15"
+            "CMAKE_OSX_DEPLOYMENT_TARGET": "12.0"
         },
         "condition": {
             "type": "inList",

Package.swift

@@ -120,7 +120,7 @@ let package = Package(
   name: "executorch",
   platforms: [
     .iOS(.v17),
-    .macOS(.v10_15),
+    .macOS(.v12),
   ],
   products: packageProducts,
   targets: packageTargets + [

backends/apple/coreml/runtime/delegate/ETCoreMLDefaultModelExecutor.mm

@@ -27,7 +27,7 @@ - (instancetype)initWithModel:(ETCoreMLModel *)model {
                                                  eventLogger:(const executorchcoreml::ModelEventLogger* _Nullable __unused)eventLogger
                                                        error:(NSError * __autoreleasing *)error {
     if (self.ignoreOutputBackings) {
-        if (@available(macOS 11.0, iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
+        if (@available(iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
             predictionOptions.outputBackings = @{};
         }
     }

backends/apple/coreml/runtime/delegate/ETCoreMLModelManager.mm

@@ -92,7 +92,7 @@ BOOL is_backed_by_same_buffer(MLMultiArray *array1, MLMultiArray *array2) {
                                             NSOrderedSet<NSString *> *output_names,
                                             NSError * __autoreleasing *error) {
     MLPredictionOptions *options = [MLPredictionOptions new];
-    if (@available(macOS 11.0, iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
+    if (@available(iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
         NSMutableDictionary<NSString *, id> *output_backings = [NSMutableDictionary dictionary];
         NSEnumerator<NSString *> *enumerator = [output_names objectEnumerator];
         for (MLMultiArray *output in outputs) {
@@ -687,7 +687,7 @@ - (void)addPrewarmedAsset:(ETCoreMLAsset *)asset {
                                                                  eventLogger:eventLogger
                                                                        error:&localError];
     // Try without output backings.
-    if (@available(macOS 11.0, iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
+    if (@available(iOS 16.0, tvOS 16.0, watchOS 9.0, *)) {
         if (!modelOutputs && predictionOptions.outputBackings.count > 0) {
             executor.ignoreOutputBackings = YES;
             localError = nil;

backends/apple/mps/setup.md

@@ -91,7 +91,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_executorch.sh --pybind mps
+CMAKE_ARGS="-DEXECUTORCH_BUILD_MPS=ON" ./install_executorch.sh
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/arm/_passes/__init__.py

@@ -23,6 +23,7 @@
 from .decompose_cosine_similarity_pass import DecomposeCosineSimilarityPass  # noqa
 from .decompose_div_pass import DecomposeDivPass  # noqa
 from .decompose_gelu_pass import DecomposeGeluPass  # noqa
+from .decompose_groupnorm_pass import DecomposeGroupNormPass  # noqa
 from .decompose_layernorm_pass import DecomposeLayerNormPass  # noqa
 from .decompose_leaky_relu_pass import DecomposeLeakyReLUPass  # noqa
 from .decompose_linalg_vector_norm_pass import DecomposeLinearVectorNormPass  # noqa