}
  }
  return absl::OkStatus();
}

}  // namespace

Status InferShapes(Graph* graph, const std::map<int, InferredShape>& arg_shapes,
                   const tensorflow::FunctionLibraryDefinition* fnlib_def,
                   GraphShapeInfo* shape_info) {
  ShapeRefiner shape_refiner(graph->versions(), graph->op_registry());
  shape_refiner.set_require_shape_inference_fns(false);

           "knows how to fuse.  "
           "If set to single-gpu(<N>) then this resolves to <N> for single-GPU "
           "graphs (graphs that have at least one node placed on a GPU and no "
           "more than one GPU is in use through the entire graph) and 0 "
           "otherwise.  Experimental."),
      Flag("tf_xla_min_cluster_size",
           &mark_for_compilation_flags->tf_xla_min_cluster_size,

  std::unique_ptr<Graph> graph;
  TF_RETURN_IF_ERROR(ConvertMlirToGraph(module, configs, &graph, &flib_def));

  // If the entry function is exported to flib, then no graph is constructed.
  // Construct one in that case.
  if (configs.export_entry_func_to_flib) {
    graph = std::make_unique<Graph>(OpRegistry::Global());
    TF_RETURN_IF_ERROR(
        graph->mutable_flib_def()->AddLibrary(std::move(flib_def)));

  std::unique_ptr<Graph> graph;
  TF_RETURN_IF_ERROR(ConvertMlirToGraph(module, configs, &graph, &flib_def));

  // If the entry function is exported to flib, then no graph is constructed.
  // Construct one in that case.
  if (configs.export_entry_func_to_flib) {
    graph = std::make_unique<Graph>(OpRegistry::Global());
    TF_RETURN_IF_ERROR(
        graph->mutable_flib_def()->AddLibrary(std::move(flib_def)));

A. Unique TensorFlower <******@****.***> 1591817060 -0700

  auto graph_op = cast<GraphOp>(func.front().front());

  // For each op in the graph, get the resources it uses and update the access
  // information for them.
  graph_op.walk([&](IslandOp island) {
    // This pass assumes that all functions are suitable for export i.e., each
    // function has a single tf_executor.graph op and all islands wrap the

swift-application-task-graph.png...

visual-studio-task-graph.png...

#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/statusor.h"

// Tool which lowers TensorFlow Graphs to StableHLO graphs.
//
// This tool is used by the ODML Programmability effort to consume input TF
// graphs, and lower them to StableHLO graphs for use by downstream tools.
//
// Input: TF Saved Model or TF MLIR files.
// Output: StableHLO MLIR or TFLite Flatbuffer.
//
// Usage:

function viewer(baseUrl, nodes, options) {
  'use strict';

  // Elements
  const search = document.getElementById('search');
  const graph0 = document.getElementById('graph0');
  const svg = (graph0 == null ? null : graph0.parentElement);
  const toptable = document.getElementById('toptable');

  let regexpActive = false;
  let selected = new Map();
  let origFill = new Map();