checkValidState(cache);
    }
  }

  /* ---------------- Local utilities -------------- */

  /** Most of the tests in this class run against every one of these caches. */
  private Iterable<LoadingCache<Object, Object>> caches() {
    // lots of different ways to configure a LoadingCache
    CacheBuilderFactory factory = cacheFactory();
    return Iterables.transform(

                (v1, v2) -> {
                  throw new IllegalArgumentException("Multiple values for key: " + v1 + ", " + v2);
                }),
        (accum, t) -> {
          /*
           * We assign these to variables before calling checkNotNull to work around a bug in our
           * nullness checker.
           */
          K key = keyFunction.apply(t);
          V newValue = valueFunction.apply(t);
          accum.put(

                (v1, v2) -> {
                  throw new IllegalArgumentException("Multiple values for key: " + v1 + ", " + v2);
                }),
        (accum, t) -> {
          /*
           * We assign these to variables before calling checkNotNull to work around a bug in our
           * nullness checker.
           */
          K key = keyFunction.apply(t);
          V newValue = valueFunction.apply(t);
          accum.put(

    //     we find them, regardless of what the address policies need.
    //
    //  2. EVICTABLE: Connections not required by any address policy. This matches connections that
    //     don't participate in any policy, plus connections whose policies won't be violated if the
    //     connection is closed. We only close these if the idle connection limit is exceeded.
    //

  private final transient @Nullable Object hashTable;
  @VisibleForTesting final transient @Nullable Object[] alternatingKeysAndValues;
  private final transient int size;

  /*
   * We have some considerable complexity in these create methods because of
   * Builder.buildKeepingLast(). The same Builder might be called with buildKeepingLast() and then
   * buildOrThrow(), or vice versa. So in particular, if we modify alternatingKeysAndValues to

See the [security policy](https://golang.org/security) for details.

The recommended way to file an issue is by running `go bug`.
Otherwise, when filing an issue, make sure to answer these five questions:

1. What version of Go are you using (`go version`)?
2. What operating system and processor architecture are you using?
3. What did you do?
4. What did you expect to see?
5. What did you see instead?

# OSX leaves these everywhere on SMB shares
._*

# OSX trash
.DS_Store

# Developers can store local stuff in dirs named __something
__*

# Eclipse files
.classpath
.project
.settings/**

# Files generated by JetBrains IDEs, e.g. IntelliJ IDEA
.idea/
*.iml

# Vscode files
.vscode

# This is where the result of the go build goes
/output*/
/_output*/
/_output

# Emacs save files
*~
\#*\#

    protected Object source;

    protected String longMessage;

    /**
     * Constructs a new {@code MojoException} providing the source and a short and long message.
     * These messages are used to improve the message written at the end of Maven build.
     */
    public MojoException(Object source, String shortMessage, String longMessage) {
        super(shortMessage);
        this.source = source;

	if err == nil {
		t.Fatalf("should returns error but got nil")
	}
}

func TestReturningWithNullToZeroValues(t *testing.T) {
	dialect := DB.Dialector.Name()
	switch dialect {
	case "mysql", "sqlserver":
		// these dialects do not support the "returning" clause
		return
	default:
		// This user struct will leverage the existing users table, but override
		// the Name field to default to null.
		type user struct {
			gorm.Model

   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below: