// Create a copy of `metagraph` which will be used and mutated for fingerprint
  // computation.
  FingerprintDef fingerprint_def;
  MetaGraphDef* metagraph = saved_model.mutable_meta_graphs(0);
  // Set fingerprint field #1.
  fingerprint_def.set_saved_model_checksum(HashSavedModel(saved_model));
  // Set fingerprint field #2.
  graph_regularization::SimpleDelete(*metagraph->mutable_graph_def());

                                const MetaGraphDef& meta_graph,
                                std::unique_ptr<Session>* session) {
  Session* session_p = nullptr;
  TF_RETURN_IF_ERROR(NewSession(session_options, &session_p));
  session->reset(session_p);
  TF_RETURN_IF_ERROR(ValidateSavedTensors(meta_graph.graph_def()));
  return (*session)->Create(meta_graph.graph_def());
}

  // "Value" attribute.
  NodeAttrMap node_attr_map = NodeToAttrMap(metagraph.graph_def());

  // These are needed for creating "Assets", by looking up their filenames.
  std::vector<AssetFileDef> assets;
  TF_RETURN_IF_ERROR(GetAssetFileDefs(metagraph, &assets));

  // Signatures are needed for determining whether a function is a
  // SignatureDefFunction or not.

        dependsOn(task3, [task4])
        dependsOn(transform1, [task4])

        when:
        collector.collectNodes([task1, task2, task3, task4, transform1])
        def graph = collector.getGraph()
        def nodes = graph.getNodes(PlannedNodeGraph.DetailLevel.LEVEL1_TASKS) as List<TestPlannedNode>
        then:
        nodes.size() == 4
        nodes*.nodeIdentity*.nodeType =~ [NodeType.TASK]
        verifyAll {

  saved_model_proto = saved_model_loader.parse_saved_model(saved_model_path)
  for meta_graph in saved_model_proto.meta_graphs:
    if any(
        node.op.startswith('FakeQuant') for node in meta_graph.graph_def.node
    ):
      return True
    for function in meta_graph.graph_def.library.function:
      if any(node.op.startswith('FakeQuant') for node in function.node_def):
        return True

#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace py = pybind11;

namespace {

using ::tensorflow::SignatureDef;
using ::tensorflow::quantization::ExportedModel;
using ::tensorflow::quantization::PyFunctionLibrary;

#include "absl/status/statusor.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"
#include "tensorflow/tools/proto_splitter/cc/util.h"
#include "tensorflow/tools/proto_splitter/chunk.pb.h"

#include "tensorflow/core/framework/versions.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace tensorflow {

namespace {

// Gets tensor names from tensor_info and inserts them into the set of tensor
// names.
void GetTensorNamesFromTensorInfo(const TensorInfo& tensor_info,

#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/platform/stringpiece.h"
#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_model.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"
#include "tensorflow/core/protobuf/trackable_object_graph.pb.h"

namespace tensorflow {

                renderExecutions();
            }

            private void renderExecutions() {
                h3().text("Executions for commit " + Git.current().getCommitId()).end();
                getGraphs(testHistory).forEach(graph -> graph.render(this));
            }
        };
    }
    // @formatter:on

    private static class Chart {
        private String field;
        private String label;