static const char* const kArgOp = "_Arg";
static const char* const kRetValOp = "_Retval";

class Encapsulator {
 public:
  Encapsulator(string group_attribute, Graph const* graph_in)
      : group_attribute_(std::move(group_attribute)), graph_in_(graph_in) {}

  // Find subgraphs marked with 'group_attribute', and build a new
  // subgraph, one for each value of 'group_attribute'.

// dep from B. Originally D must run after C, post-transformation this
// dependency is lost.
Status EncapsulateSubgraphsInFunctions(
    string group_attribute, const Graph& graph_in,
    const RewriteSubgraphFn& rewrite_subgraph_fn, bool reuse_existing_functions,
    std::unique_ptr<Graph>* graph_out, FunctionLibraryDefinition* library);

// so redudant ones may be grouped and removed.
std::unique_ptr<OperationPass<ModuleOp>> CreatePushTransposeThroughEwisePass();

// Creates a pass that brings operations into the same order as graph_info.cc.
std::unique_ptr<OperationPass<func::FuncOp>>
CreatePartitionedTopologicalSortPass();

#define GEN_PASS_DECL_DEFAULTQUANTPARAMSPASS
#define GEN_PASS_DECL_DENSETOSPARSEPASS
#define GEN_PASS_DECL_LEGALIZETFPASS

```

##### Node (optional)

Optionally you can also collect per node metrics. This needs to be done on a per server instance.
The scrape configurations should use all the servers under `targets` so that graphing systems like
grafana can visualize them for all the nodes

```yaml
scrape_configs:
- job_name: minio-job
  metrics_path: /minio/v2/metrics/node
  scheme: http
  static_configs:

// Copyright 2023 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Minimum mutator utilization (MMU) graphing.

// TODO:
//
// In worst window list, show break-down of GC utilization sources
// (STW, assist, etc). Probably requires a different MutatorUtil
// representation.
//
// When a window size is selected, show a second plot of the mutator

      executed by the Flex delegate will be followed by another Flex delegated
      operator, if possible. The reordering uses the same greedy procedure that
      is executed at runtime (in tensorflow/lite/graph_info.cc.)
      This allows us to have an IR of the model that is in the same execution order
      as it will have at runtime (provided Flex is the only delegate present); this

#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/lite/experimental/remat/metadata_util.h"
#include "tensorflow/lite/graph_info.h"
#include "tensorflow/lite/model_builder.h"
#include "tsl/platform/status.h"
#include "tsl/platform/statusor.h"

using absl::Status;
using absl::StatusOr;
using llvm::ArrayRef;
using mlir::Builder;

#include "tensorflow/lite/core/macros.h"
#include "tensorflow/lite/delegates/flex/allowlisted_flex_ops.h"
#include "tensorflow/lite/experimental/remat/metadata_util.h"
#include "tensorflow/lite/graph_info.h"
#include "tensorflow/lite/python/metrics/converter_error_data.pb.h"
#include "tensorflow/lite/schema/schema_conversion_utils.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

const TestExports={};const...