# Description:
# TensorFlow is a computational framework, primarily for use in machine
# learning applications.

load("@rules_cc//cc:cc_import.bzl", "cc_import")

# buildifier: disable=out-of-order-load
# copybara:comment_begin(oss-only)
load("//tensorflow:strict.default.bzl", "py_strict_library")

# copybara:comment_end
# buildifier: enable=out-of-order-load
load("@bazel_skylib//lib:selects.bzl", "selects")

   * @throws IllegalCharsetNameException if a charset value is present, but illegal
   * @throws UnsupportedCharsetException if a charset value is present, but no support is available
   *     in this instance of the Java virtual machine
   */
  public Optional<Charset> charset() {
    // racy single-check idiom, this is safe because Optional is immutable.
    Optional<Charset> local = parsedCharset;
    if (local == null) {

* Fix AWS device allocator to only use valid device names ([#41455](https://github.com/kubernetes/kubernetes/pull/41455), [@gnufied](https://github.com/gnufied))
* Reverts to looking up the current VM in vSphere using the machine's UUID, either obtained via sysfs or via the `vm-uuid` parameter in the cloud configuration file. ([#40892](https://github.com/kubernetes/kubernetes/pull/40892), [@robdaemon](https://github.com/robdaemon))

* Reverts to looking up the current VM in vSphere using the machine's UUID, either obtained via sysfs or via the `vm-uuid` parameter in the cloud configuration file. ([#40892](https://github.com/kubernetes/kubernetes/pull/40892), [@robdaemon](https://github.com/robdaemon))

    if (parent == null) {
      /*
       * The given directory is a filesystem root. All zero of its ancestors exist. This doesn't
       * mean that the root itself exists -- consider x:\ on a Windows machine without such a drive
       * -- or even that the caller can create it, but this method makes no such guarantees even for
       * non-root files.
       */
      return;
    }
    parent.mkdirs();

### Nebenläufigkeit + Parallelität: Web + maschinelles Lernen { #concurrency-parallelism-web-machine-learning }

Mit **FastAPI** können Sie die Vorteile der Nebenläufigkeit nutzen, die in der Webentwicklung weit verbreitet ist (derselbe Hauptvorteil von NodeJS).

/minio/minio/blob/master/LICENSE) MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. For more detailed documentation please visit [here](https://docs.minio.io/) Introduction ---------- This chart bootstraps MinIO Cluster on [Kubernetes](http://kubernetes.io) using the [Helm](https://helm.sh)...

# CL 132000043 debug/elf: support arm64 relocations, Michael Hudson-Doyle <******@****.***>
pkg debug/elf, const EM_AARCH64 = 183
pkg debug/elf, const EM_AARCH64 Machine
pkg debug/elf, const R_AARCH64_ABS16 = 259
pkg debug/elf, const R_AARCH64_ABS16 R_AARCH64
pkg debug/elf, const R_AARCH64_ABS32 = 258
pkg debug/elf, const R_AARCH64_ABS32 R_AARCH64
pkg debug/elf, const R_AARCH64_ABS64 = 257

# LINUX ARM64 PYCPP
# In Linux Arm64 presubmit/continuous build, we cross-compile the binaries on
# Linux x86 so that we can use RBE. Since tests still need to run on the single
# host Arm64 machine, the build becomes too slow (~30 min) to be a presubmit.
# For testing purposes, we want to see the runtime performance of an
# experimental job that is build-only, i.e, we only build the test targets and

/minio/minio/blob/master/LICENSE) MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. For more detailed documentation please visit [here](https://docs.minio.io/) Introduction ---------- This chart bootstraps MinIO Cluster on [Kubernetes](http://kubernetes.io) using the [Helm](https://helm.sh)...