chromium/third_party/tflite/src/tensorflow/lite/graph_info.h

/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_LITE_GRAPH_INFO_H_
#define TENSORFLOW_LITE_GRAPH_INFO_H_

#include <stddef.h>

#include <cstdint>
#include <utility>
#include <vector>

#include "tensorflow/lite/core/c/common.h"

namespace tflite {

// Basic information about an inference graph, where execution nodes
// are connected via tensors.
class GraphInfo { … };

// Represents a subset of nodes in a TensorFlow Lite graph.
struct NodeSubset { … };

// LINT.IfChange
// Node edge.second depends on node edge.first.
ControlEdge;
ControlEdges;
// LINT.ThenChange(//tensorflow/compiler/mlir/lite/utils/control_edges.h)

// Partitions a list of node indices `nodes_to_partition` into node subsets.
// Each node subset is in dependency order internally (i.e. all members of the
// node subsets can be executed in the order they occur) and externally (i.e.,
// node subsets are executable in the order they occur.) The function assumes
// that the nodes of the graph represented in *info are in dependency order.
//
// Depending on the value of `greedily`, the function behaves
//
// - greedily: while a node_set is generated whose members are (aren't) members
// of
//   `*nodes_to_partition`, it will add nodes to this subset, as long as they
//   are (aren't) members of *nodes_to_partition and they are schedulable (i.e.,
//   all nodes they depend have already be added to `*node_subsets`.)
//
// - non-greedily: this preserves the original execution order, i.e. the node
//   subsets generated will be of the form [ [0..i_1), [i1..i2), ... ].
//
// `control_edges` specifies a control dependency DAG on the nodes contained in
// `info`. The resulting partitioning will respect these control
// dependencies. This way, restrictions (in addition to the nodes' data
// dependencies) can be imposed on the ultimate execution order of the graph
// (naturally, this is relevant only if ordering greedily.)
//
// (Example: with `greedily`, `control_edges.empty()`, and `nodes_to_partition
// == {2, 3}`, the graph
//
//                    /------------\
//                    |            v
// 0 --> 1 --> 2* --> 3*     4 --> 5
//       |                   ^
//       \-------------------/
//
// will be partitioned as {{0, 1, 4}, {2, 3}, {5}}, since data dependencies
// (notated '-->') allow for execution of 4 immediately after 1.
//
// With an additional control dependency `control_edges == {{3, 4}}` (notated
// '==>'), execution of node 4 requires prior execution of node 3:
//
//                    /------------\
//                    |            v
// 0 --> 1 --> 2* --> 3* ==> 4 --> 5
//       |                   ^
//       \-------------------/
//
// and the partitioning will be {{0, 1}, {2, 3}, {4, 5}}.)
//
// If control_edges == nullptr, the algorithm preserves the relative ordering of
// nodes that have their `might_have_side_effects` attribute set, i.e., it
// behaves as if `*control_dependencies` of the form `{ {n_1, n_2}, {n_2, n_3},
// ... }` had been handed in, where the n_i are the (sorted) indices of nodes
// with `might_have_side_effects` attribute set.
//
// The function assumes that `*node_subsets` is initially empty.
TfLiteStatus PartitionGraphIntoIndependentNodeSubsets(
    const GraphInfo* info, const TfLiteIntArray* nodes_to_partition,
    std::vector<NodeSubset>* node_subsets, bool greedily,
    const ControlEdges* control_edges = nullptr);

}  // namespace tflite

#endif  // TENSORFLOW_LITE_GRAPH_INFO_H_