* we don't include the method, then the compiler will complain that an abstract method is
   * unimplemented. So instead we use a dynamic proxy to get an implementation. If the method being
   * called on the {@code TypeVariable} instance has the same name as one of the public methods of
   * {@link TypeVariableImpl}, the proxy calls the same method on its instance of {@code

            It will be closed in 14 days if no further activity occurs.
            If you don't want the stale bot to close it, then set a milestone for it.
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auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a
# For new protobuf, if V.x.y is gencode version, then runtime version U must be
# V <= U <= V+1

}

// parsePAXRecord parses the input PAX record string into a key-value pair.
// If parsing is successful, it will slice off the currently read record and
// return the remainder as r.
func parsePAXRecord(s string) (k, v, r string, err error) {
	// The size field ends at the first space.
	nStr, rest, ok := strings.Cut(s, " ")
	if !ok {
		return "", "", s, ErrHeader
	}

auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a
# For new protobuf, if V.x.y is gencode version, then runtime version U must be
# V <= U <= V+1

   * we don't include the method, then the compiler will complain that an abstract method is
   * unimplemented. So instead we use a dynamic proxy to get an implementation. If the method being
   * called on the {@code TypeVariable} instance has the same name as one of the public methods of
   * {@link TypeVariableImpl}, the proxy calls the same method on its instance of {@code

              echo "Commit $commit wrapper: $WRAPPER_GRADLE_VERSION"
              if ! [[ $WRAPPER_GRADLE_VERSION =~ ^[0-9.]+(-(rc|milestone|m)-[0-9]+)?$ ]]; then
                  RED="\e[31m"
                  ENDCOLOR="\e[0m"

)

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

         *
         * 2a. If the resolved types are identical to the original types, then we can return the
         * original, identical JDK TypeVariable. By doing so, we sidestep the problem entirely.
         *
         * 2b. If the resolved types are different from the original types, things are trickier. The
         * only way to get a TypeVariable instance for the resolved types is to create our own. The

      # Our Maven configuration then specifies different JDKs to use for some of the steps:
      # - 11 (sometimes) to *download* to support anyone who runs JDiff or our Gradle integration tests (including our doc snapshots and our Java 11 CI test run) but not to use directly
      # - 24 for running Javadoc and javac (to help people who build Guava locally and might not use a recent JDK to run Maven)
      - name: 'Set up JDKs'