1. Add an Emulator named `pixel5`, if you don't already have one

```
$ sdkmanager --install "system-images;android-29;google_apis;x86"
$ echo "no" | avdmanager --verbose create avd --force --name "pixel5" --device "pixel" --package "system-images;android-29;google_apis;x86" --tag "google_apis" --abi "x86"
```

2. Run an Emulator using Android Studio or from command line.

```
$ emulator -no-window -no-snapshot-load @pixel5
```

build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_arm64 --platforms=@org_tensorflow//tensorflow/tools/toolchains/android:arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86 --platforms=@org_tensorflow//tensorflow/tools/toolchains/android:x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64

          script: ./gradlew :android-test:connectedCheck
        env:
          API_LEVEL: ${{ matrix.api-level }}

      - name: Run Release Tests
        uses: reactivecircus/android-emulator-runner@v2
        with:
          api-level: ${{ matrix.api-level }}
          arch: ${{ matrix.api-level == '34' && 'x86_64' || 'x86' }}

  /**
   * Returns a hash function implementing the <a
   * href="https://github.com/aappleby/smhasher/blob/master/src/MurmurHash3.cpp">32-bit murmur3
   * algorithm, x86 variant</a> (little-endian variant), using the given seed value, <b>with a known
   * bug</b> as described in the deprecation text.
   *
   * <p>The C++ equivalent is the MurmurHash3_x86_32 function (Murmur3A), which however does not

	"strconv"
	"strings"
	"text/scanner"

	"cmd/asm/internal/arch"
	"cmd/asm/internal/flags"
	"cmd/asm/internal/lex"
	"cmd/internal/obj"
	"cmd/internal/obj/ppc64"
	"cmd/internal/obj/riscv"
	"cmd/internal/obj/x86"
	"cmd/internal/sys"
)

// TODO: configure the architecture

var testOut *strings.Builder // Gathers output when testing.

// append adds the Prog to the end of the program-thus-far.

    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();

    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();

*   [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md)
    Windows x64 & x86.

    *   **Windows x64 & x86 packages:**
        *   oneDNN optimizations are *enabled by default* on X86 CPUs