*/

package org.gradle.execution.plan;

import java.util.HashSet;
import java.util.Set;

class MutationInfo {
    private final Set<Node> nodesYetToConsumeOutput = new HashSet<>();
    final Set<String> outputPaths = new HashSet<>();
    final Set<String> destroyablePaths = new HashSet<>();
    boolean hasFileInputs;
    boolean hasOutputs;
    boolean hasLocalState;
    boolean hasValidationProblem;

                                SrvCopyChunkCopyResponse outputData = response.getOutputData(SrvCopyChunkCopyResponse.class);
                                maxChunks = outputData.getChunksWritten();
                                maxChunkSize = outputData.getChunkBytesWritten();
                                byteLimit = outputData.getTotalBytesWritten();
                                continue;

  def _create_and_save_vocab_table_lookup_model_tf1(
      self,
      output_path: str,
      tags: Collection[str],
      signature_def_key: str,
  ) -> Tuple[Mapping[str, core.Tensor], Mapping[str, core.Tensor]]:
    """Creates and saves a simple model that uses a vocab table.

    Args:
      output_path: Path to the directory to save the created model.

namespace generator {

PathConfig::PathConfig(const string& output_dir, const string& source_dir,
                       const string& api_dir_list,
                       const std::vector<string> op_names)
    : output_path(output_dir), op_names(op_names) {
  api_dirs = str_util::Split(api_dir_list, ",", str_util::SkipEmpty());

  // Decompose the directory components given the output/source directories.
  //

	}

	o = DefaultOptions()
	o.logCallers = "foobar"
	err = Configure(o)
	if err != nil {
		t.Error("Got success, expected failure")
	}

	o = DefaultOptions()
	// using invalid filename
	o.OutputPaths = []string{"//"}
	err = Configure(o)
	if err == nil {
		t.Errorf("Got success, expecting error")
	}

	o = DefaultOptions()
	o.ErrorOutputPaths = []string{"//"}
	err = Configure(o)
	if err == nil {

            mutations.outputPaths.add(outputLocation.getAbsolutePath());
            mutations.hasOutputs = true;
        });
    }

    private void addLocalStateFilesToMutations(FileCollection localStateFiles) {
        final MutationInfo mutations = getMutationInfo();
        localStateFiles.forEach(file -> {
            mutations.outputPaths.add(file.getAbsolutePath());

opt<std::string> input_model(llvm::cl::Positional,
                             llvm::cl::desc("<input model path>"),
                             llvm::cl::Required);

// NOLINTNEXTLINE
opt<std::string> output_path("o", llvm::cl::desc("<output path>"),
                             llvm::cl::Required);

// NOLINTNEXTLINE
opt<std::string> export_type("export-type", llvm::cl::desc("<export type>"),

        node.resolveMutations();
        mutations.hasValidationProblem = nodeValidator.hasValidationProblems(node);
        accessHierarchies.getOutputHierarchy().recordNodeAccessingLocations(node, mutations.outputPaths);
        accessHierarchies.getDestroyableHierarchy().recordNodeAccessingLocations(node, mutations.destroyablePaths);
    }

  /// to feed them with. See `Input::Initializer` for details on what can be
  /// used as feed values.
  typedef std::unordered_map<Output, Input::Initializer, OutputHash> FeedType;

  /// Create a new session to evaluate the graph contained in `scope` by
  /// connecting to the TensorFlow runtime specified by `target`.
  ClientSession(const Scope& scope, const string& target);

	errSink, closeErrorSink, err := zap.Open(options.ErrorOutputPaths...)
	if err != nil {
		return nil, nil, nil, err
	}

	var outputSink zapcore.WriteSyncer
	if len(options.OutputPaths) > 0 {
		outputSink, _, err = zap.Open(options.OutputPaths...)
		if err != nil {
			closeErrorSink()
			return nil, nil, nil, err
		}
	}

	var sink zapcore.WriteSyncer
	if rotaterSink != nil && outputSink != nil {