_DEFAULT_PROMPT_ASK_ATTEMPTS = 10

_TF_BAZELRC_FILENAME = '.tf_configure.bazelrc'
_TF_WORKSPACE_ROOT = ''
_TF_BAZELRC = ''
_TF_CURRENT_BAZEL_VERSION = None

NCCL_LIB_PATHS = [
    'lib64/', 'lib/powerpc64le-linux-gnu/', 'lib/x86_64-linux-gnu/', ''
]

# List of files to configure when building Bazel on Apple platforms.
APPLE_BAZEL_FILES = [
    'tensorflow/lite/ios/BUILD', 'tensorflow/lite/objc/BUILD',
    'tensorflow/lite/swift/BUILD',

}

// gccMachine returns the gcc -m flag to use, either "-m32", "-m64" or "-marm".
func gccMachine() []string {
	switch goarch {
	case "amd64":
		if goos == "darwin" {
			return []string{"-arch", "x86_64", "-m64"}
		}
		return []string{"-m64"}
	case "arm64":
		if goos == "darwin" {
			return []string{"-arch", "arm64"}
		}
	case "386":
		return []string{"-m32"}
	case "arm":

* Do not daemonize `salt-minion` for the openstack-heat provider. ([#40722](https://github.com/kubernetes/kubernetes/pull/40722), [@micmro](https://github.com/micmro))
* OpenStack-Heat will now look for an image named "CentOS-7-x86_64-GenericCloud-1604". To restore the previous behavior set OPENSTACK_IMAGE_NAME="CentOS7" ([#40368](https://github.com/kubernetes/kubernetes/pull/40368), [@sc68cal](https://github.com/sc68cal))

    X850,
    X851,
    X852,
    X853,
    X854,
    X855,
    X856,
    X857,
    X858,
    X859,
    X860,
    X861,
    X862,
    X863,
    X864,
    X865,
    X866,
    X867,
    X868,
    X869,
    X870,
    X871,
    X872,
    X873,
    X874,
    X875,
    X876,
    X877,
    X878,
    X879,
    X880,

pkg debug/elf, const R_X86_64_GOTPCREL64 = 28
pkg debug/elf, const R_X86_64_GOTPCREL64 R_X86_64
pkg debug/elf, const R_X86_64_GOTPCRELX = 41
pkg debug/elf, const R_X86_64_GOTPCRELX R_X86_64
pkg debug/elf, const R_X86_64_GOTPLT64 = 30
pkg debug/elf, const R_X86_64_GOTPLT64 R_X86_64
pkg debug/elf, const R_X86_64_IRELATIVE = 37
pkg debug/elf, const R_X86_64_IRELATIVE R_X86_64
pkg debug/elf, const R_X86_64_PC32_BND = 39

    X850,
    X851,
    X852,
    X853,
    X854,
    X855,
    X856,
    X857,
    X858,
    X859,
    X860,
    X861,
    X862,
    X863,
    X864,
    X865,
    X866,
    X867,
    X868,
    X869,
    X870,
    X871,
    X872,
    X873,
    X874,
    X875,
    X876,
    X877,
    X878,
    X879,
    X880,

}

@test "Wheel is manylinux2014 (manylinux_2_17) compliant" {
    python3 -m auditwheel show "$TF_WHEEL" > audit.txt
    grep --quiet -zoP 'is consistent with the following platform tag:\n"manylinux_2_17_(aarch|x86_)64"\.' audit.txt
}

@test "Wheel conforms to upstream size limitations" {
    WHEEL_MEGABYTES=$(stat --format %s "$TF_WHEEL" | awk '{print int($1/(1024*1024))}')
    # Googlers: search for "test_tf_whl_size"

        instead of 2.15, or users could receive an installation error due to
        those missing dependencies.
*   TensorFlow 2.15.0.post1 is being released for Linux x86_64 to resolve this
    issue as quickly as possible.
    *   This version removes the `tensorrt` Python package dependencies from the
        tensorflow[and-cuda] installation method to ensure `pip install

pkg debug/elf, const R_X86_64_GOT32 R_X86_64
pkg debug/elf, const R_X86_64_GOTPCREL R_X86_64
pkg debug/elf, const R_X86_64_GOTTPOFF R_X86_64
pkg debug/elf, const R_X86_64_JMP_SLOT R_X86_64
pkg debug/elf, const R_X86_64_NONE R_X86_64
pkg debug/elf, const R_X86_64_PC16 R_X86_64
pkg debug/elf, const R_X86_64_PC32 R_X86_64
pkg debug/elf, const R_X86_64_PC8 R_X86_64
pkg debug/elf, const R_X86_64_PLT32 R_X86_64

    <magic priority="60">
      <match value="PE\000\000" type="string" offset="128">
         <match value="0x8664" type="little16" offset="132"/>
      </match>
      <match value="PE\000\000" type="string" offset="240">
         <match value="0x8664" type="little16" offset="244"/>
      </match>
    </magic>
  </mime-type>
  <mime-type type="application/x-msdownload;format=pe-itanium">