1 /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #ifndef TENSORFLOW_LITE_DELEGATES_GPU_COMMON_MEMORY_MANAGEMENT_MIN_COST_FLOW_ASSIGNMENT_H_ 17 #define TENSORFLOW_LITE_DELEGATES_GPU_COMMON_MEMORY_MANAGEMENT_MIN_COST_FLOW_ASSIGNMENT_H_ 18 19 #include <stddef.h> 20 21 #include <vector> 22 23 #include "tensorflow/lite/delegates/gpu/common/memory_management/types.h" 24 #include "tensorflow/lite/delegates/gpu/common/status.h" 25 26 namespace tflite { 27 namespace gpu { 28 29 // Implements memory management with a Minimum-cost flow matching algorithm. 30 // 31 // The problem of memory management is NP-complete. This function creates 32 // auxiliary flow graph, find minimum-cost flow in it and calculates the 33 // assignment of shared objects to tensors, using the result of the flow 34 // algorithm. 35 absl::Status MinCostFlowAssignment( 36 const std::vector<TensorUsageRecord<size_t>>& usage_records, 37 ObjectsAssignment<size_t>* assignment); 38 39 } // namespace gpu 40 } // namespace tflite 41 42 #endif // TENSORFLOW_LITE_DELEGATES_GPU_COMMON_MEMORY_MANAGEMENT_MIN_COST_FLOW_ASSIGNMENT_H_ 43