const OutputList& tensors, std::vector<Tensor>* out);

/// Computes the output 'tensor', returning the resulting tensor in 'out'.
void GetTensor(const Scope& scope, Output tensor, Tensor* out);

// Computes the output 'tensor', returning the resulting tensor in 'out'.
// assign_vars are extra outputs that should be run
// e.g. to assign values to variables.

        [_AsClassName(x) for x in ctx.attr.srcs],
    )
    ctx.actions.write(output = ctx.outputs.out, content = _OUTPUT % (
        classes,
        ctx.attr.outname,
    ))

_GenSuite = rule(
    attrs = {
        "srcs": attr.label_list(allow_files = True),
        "outname": attr.string(),
    },
    outputs = {"out": "%{name}.java"},
    implementation = _impl,
)

                outputs.file("output.txt")
                    .withPropertyName("$NON_ASCII_NAME")
                outputs.cacheIf { true }
                doLast {
                    file("output.txt").text = "output"
                }
            }
        """

        when:
        withBuildCache().run("createFile", "-Dfile.encoding=$fileEncoding")
        then:

// Fatal outputs a message at fatal level.
func Fatal(fields any) {
	defaultScope.Fatal(fields)
}

// Fatalf uses fmt.Sprintf to construct and log a message at fatal level.
func Fatalf(format string, args ...any) {
	defaultScope.Fatalf(format, args...)
}

// FatalEnabled returns whether output of messages using this scope is currently enabled for fatal-level output.
func FatalEnabled() bool {

                // See https://github.com/gradle/gradle/issues/18460.
                LOGGER.debug("More outputs are being registered even though the build output cleanup registry has already been finalized. New outputs: {}", files);
            } else {
                this.outputs.add(fileCollectionFactory.resolving(files));
            }
        }
    }

    @Override

  /// `Tensor` objects in `outputs`. The number and order of `outputs` will
  /// match `fetch_outputs`.
  Status Run(const std::vector<Output>& fetch_outputs,
             std::vector<Tensor>* outputs) const;

  /// Same as above, but use the mapping in `inputs` as feeds.
  Status Run(const FeedType& inputs, const std::vector<Output>& fetch_outputs,
             std::vector<Tensor>* outputs) const;

        outputs.add(output);
    }

    /**
     * Returns concatenated non-empty output entries.
     */
    public String getOutput() {
        List<String> nonEmptyOutputs = filter(outputs, string -> !string.equals(""));
        return join("\n", nonEmptyOutputs);
    }

    /**
     * Returns all output entries.
     */
    public List<String> getOutputs() {
        return outputs;
    }

    /**

     */
    DISABLE_CONDITION_SATISFIED,

    /**
     * The work has no outputs declared.
     */
    NO_OUTPUTS_DECLARED,

    /**
     * Work has declared output that is not cacheable.
     *
     * Reasons for non-cacheable outputs:
     * <ul>
     *     <li>an output contains a file tree,</li>
     *     <li>an output is not tracked.</li>
     * </ul>
     */
    NON_CACHEABLE_OUTPUT,

    /**

    // Note: when replication is supported, this op will have N outputs.
    .Output("outputs: T")
    .Attr("T: type")
    .SetShapeFn([](InferenceContext* c) {
      for (int i = 0; i < c->num_outputs(); ++i) {
        c->set_output(i, c->input(0));
      }
      return absl::OkStatus();
    })
    .Doc(
        "Operator that connects the output of an XLA computation to other "
        "consumer graph nodes.");

        val output = outputDirectory.resolve(entry.name)
        if (!output.canonicalPath.startsWith(outputDirectoryCanonicalPath)) {
            throw ZipException("Zip entry '${entry.name}' is outside of the output directory")
        }
        if (entry.isDirectory) {
            output.mkdirs()
        } else {
            output.parentFile.mkdirs()