{Name: "fastmul", Feature: &ARM.HasFASTMUL},
		{Name: "fpa", Feature: &ARM.HasFPA},
		{Name: "edsp", Feature: &ARM.HasEDSP},
		{Name: "java", Feature: &ARM.HasJAVA},
		{Name: "iwmmxt", Feature: &ARM.HasIWMMXT},
		{Name: "crunch", Feature: &ARM.HasCRUNCH},
		{Name: "neon", Feature: &ARM.HasNEON},
		{Name: "idivt", Feature: &ARM.HasIDIVT},
		{Name: "idiva", Feature: &ARM.HasIDIVA},
		{Name: "lpae", Feature: &ARM.HasLPAE},

at 2022-02-02T14:15:21-05:00
git add pkg go.mod
git commit -a -m 'pkg: add empty package'
git branch -m main
git tag 'v0.1.0'

at 2022-02-02T14:19:44-05:00
git branch 'v1.0.0'
git branch 'v2.0.0'
git checkout 'v1.0.0'
cp v1/pkg/pkg.go pkg/pkg.go
git commit -a -m 'pkg: start developing toward v1.0.0'

at 2022-02-03T10:53:13-05:00
git branch 'v3.0.0-devel'
git checkout 'v3.0.0-devel'
git checkout v0.1.0 pkg/pkg.go

# https://github.com/tensorflow/tensorflow/actions/workflows/release-branch-cherrypick.yml
# and click "Run Workflow." Leave "Use Workflow From" set to "master", then
# input the branch name and paste the cherry-pick commit and click Run. A PR
# will be created.

name: Release Branch Cherrypick
on:
  workflow_dispatch:
    inputs:
      # We use this instead of the "run on branch" argument because GitHub looks

name: Upload SIG Build docker containers modified for release branches

on:
  workflow_dispatch:
  push:
    paths:
      - '.github/workflows/sigbuild-docker-branch.yml'
      - 'tensorflow/tools/tf_sig_build_dockerfiles/**'
      - '!tensorflow/tools/tf_sig_build_dockerfiles/README.md'
    branches:
      - "r[1-9].[0-9]+"

permissions:
  contents: read

jobs:

scala.Option, scala.collection.immutable.List); } xsbt/boot/Launch$$anonfun$xsbt$boot$Launch$$getScalaProvider0$2.class package xsbt.boot; public final synchronized class Launch$$anonfun$xsbt$boot$Launch$$getScalaProvider0$2 extends scala.runtime.AbstractFunction1 implements scala.Serializable { private final String scalaVersion$2; private final java.io.File lib$1; private scala.Option apply(RetrievedModule); public void Launch$$anonfun$xsbt$boot$Launch$$getScalaProvider0$2(Launch, String, java.io.File);...

	}
	return
}

func fpack64(sign, mant uint64, exp int, trunc uint64) uint64 {
	mant0, exp0, trunc0 := mant, exp, trunc
	if mant == 0 {
		return sign
	}
	for mant < 1<<mantbits64 {
		mant <<= 1
		exp--
	}
	for mant >= 4<<mantbits64 {
		trunc |= mant & 1
		mant >>= 1
		exp++
	}
	if mant >= 2<<mantbits64 {
		if mant&1 != 0 && (trunc != 0 || mant&2 != 0) {
			mant++
			if mant >= 4<<mantbits64 {

invalid-trunc.png...

          return 0x80;
        } else if (userFriendly.matches("(?i)(?:French|Latin|Western.*European)")) {
          // Mostly 1-byte UTF-8 sequences, mixed with occasional 2-byte
          // sequences - "Western European" text
          return 0x90;
        } else if (userFriendly.matches("(?i)(?:Branch.*Prediction.*Hostile)")) {
          // Defeat branch predictor for: c < 0x80 ; branch taken 50% of the time.
          return 0x100;

import org.gradle.internal.service.scopes.Scope;
import org.gradle.internal.service.scopes.ServiceScope;

/**
 * A bunch of information about the request that launched the current build.
 */
@ServiceScope(Scope.BuildSession.class)
public interface BuildRequestMetaData {

    /**
     * Returns the meta-data about the client used to launch this build.
     */
    BuildClientMetaData getClient();

    /**

def LaunchToDeviceAttributePass : Pass<"tf-launch-to-device-attribute", "mlir::func::FuncOp"> {
  let summary = "Hoists and annotates device launch inner ops with associated device attribute.";

  let description = [{
    This pass hoists a `tf_device.launch` body and assigns a `device` attribute
    to each TensorFlow dialect op in the body based on the `device` attribute on
    the `tf_device.launch`. If a TensorFlow dialect op already has a device