applies to it, you have the option of following the terms and
conditions either of that published version or of any later version
published by the Free Software Foundation. If the Library as you
received it does not specify a version number of the GNU Lesser
General Public License, you may choose any version of the GNU Lesser
General Public License ever published by the Free Software Foundation.

        `tensorflow[and-cuda]==2.15.0` will not install this fixed version.
        Please use `==2.15.0.post1` to specify this exact version on Linux
        platforms, or a fuzzy version specification, such as `==2.15.*`, to
        specify the most recent compatible version of TensorFlow 2.15 on all
        platforms.

# Release 2.15.0

## TensorFlow

### Breaking Changes

Some tests require multiple JDKs to be installed on your computer, be aware of this if you make changes related to anything toolchains related.

If you want to explicitly run tests with a different Java version, you need to specify `-PtestJavaVersion=#` with the major version of the JDK you want the tests to run with (e.g. `-PtestJavaVersion=14`).

### Configuration cache enabled by default

            classInNestedClass = classInNestedClass.findClassOrObjectParent()
        }
        return null
    }


    /**
     * An enum class to specify the distance of scopes from an element as a partial order
     *
     * Example:
     *   import ... // scope1  FirExplicitSimpleImportingScope - enum entry: ExplicitSimpleImporting

Following is an example YAML configuration structure.
```yaml
version: v2
address: ":9000"
rootUser: "minioadmin"
rootPassword: "minioadmin"
console-address: ":9001"
certs-dir: "/home/user/.minio/certs/"
pools: # Specify the nodes and drives with pools
  - args:
      - "https://server-example-pool1:9000/mnt/disk{1...4}/"
      - "https://server{1...2}-pool1:9000/mnt/disk{1...4}/"
      - "https://server3-pool1:9000/mnt/disk{1...4}/"

**available machines** taking into account the amount of memory needed by them, and the amount available in the machines in the cluster.

If your application is **simple**, this will probably **not be a problem**, and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more...

# END TF TEST SUITE OPTIONS

# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction
# between host and execution platform.
build:cross_compile_base --host_cpu=k8

            // the dispatch receiver and always pass null for extension receiver (because in Java there is no way to specify an extension
            // receiver)
            return KtPartiallyAppliedSymbol(
                signature,
                extensionReceiver?.toKtReceiverValue(context, this),
                null
            )