print("<ERROR TYPE REF>")
            }

            printCollection(namedValues, separator = ", ", prefix = "(", postfix = ")") { argument ->
                append(argument.name.render())
                append(" = ")
                renderConstantValueDebug(argument.expression, printer)
            }
        }
    }

    private fun renderConstantValueDebug(value: KtAnnotationValue, printer: PrettyPrinter) {

            }

            is FirVarargArgumentsExpression -> {
                // Vararg arguments may have multiple independent expressions associated.
                // Choose one to be the representative PSI value for the entire assembled argument.
                val (annotationValues, representativePsi) = arguments.convertVarargsExpression(builder)

internal fun mapAnnotationParameters(annotation: FirAnnotation): Map<Name, FirExpression> {
    if (annotation is FirAnnotationCall && annotation.arguments.isEmpty()) return emptyMap()

    checkWithAttachment(annotation.resolved, { "By now the annotations argument mapping should have been resolved" }) {
        withFirEntry("annotation", annotation)
        withClassEntry("annotationTypeRef", annotation.annotationTypeRef)

f1 := apply[[]int]             // type argument for S explicitly provided, type argument for E inferred
f2 := apply[[]string, string]  // both type arguments explicitly provided

var bytes []byte
r := apply(bytes, func(byte) byte { … })  // both type arguments inferred from the function arguments
</pre>

<p>

            token,
        )
    }
    add(FirErrors.ANNOTATION_ARGUMENT_KCLASS_LITERAL_OF_TYPE_PARAMETER_ERROR) { firDiagnostic ->
        AnnotationArgumentKclassLiteralOfTypeParameterErrorImpl(
            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.ANNOTATION_ARGUMENT_MUST_BE_CONST) { firDiagnostic ->
        AnnotationArgumentMustBeConstImpl(

     * Maps [typeArguments] to the type parameters of [partiallyAppliedSymbol].
     *
     * If too many type arguments are provided, a mapping is still created. Extra type arguments are simply ignored. If this wasn't the
     * case, the resulting [KtCall] would contain no type arguments at all, which can cause problems later. If too few type arguments are

*   Extends `tf.keras.layers.Lambda` layers to support multi-argument lambdas,
    and keyword arguments when calling the layer.
*   Functional models now get constructed if *any* tensor in a layer call's
    arguments/keyword arguments comes from a keras input. Previously the
    functional api would only work if all of the elements in the first argument
    to the layer came from a keras input.

func (e GenericError) Unwrap() error {
	return e.Err
}

// InvalidArgument incorrect input argument
type InvalidArgument GenericError

func (e InvalidArgument) Error() string {
	if e.Err != nil {
		return "Invalid arguments provided for " + e.Bucket + "/" + e.Object + ": (" + e.Err.Error() + ")"
	}
	return "Invalid arguments provided for " + e.Bucket + "/" + e.Object
}

// BucketNotFound bucket does not exist.

   * Returns an ordering that compares objects according to the order in which they are given to
   * this method. Only objects present in the argument list (according to {@link Object#equals}) may
   * be compared. This comparator imposes a "partial ordering" over the type {@code T}. Null values
   * in the argument list are not supported.
   *
   * <p>The returned comparator throws a {@link ClassCastException} when it receives an input

                else -> fe10Type.getValueParameterTypesFromFunctionType()
            }.map { it.type.toKtType(analysisContext) }
        }

    override val returnType: KtType
        get() = withValidityAssertion {
            when {
                descriptor.functionTypeKind.isReflectType -> fe10Type.arguments.last().type