simple_memory_arena.cc

/* 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.
==============================================================================*/

#include "tensorflow/lite/simple_memory_arena.h"

#include <stddef.h>
#include <stdint.h>

#include <algorithm>
#include <cstring>
#include <iterator>
#include <limits>
#include <memory>
#include <string>
#include <vector>

#include "tensorflow/lite/core/c/common.h"
#include "tensorflow/lite/core/macros.h"
#ifdef TF_LITE_TENSORFLOW_PROFILER
#include "tensorflow/lite/tensorflow_profiler_logger.h"
#endif  // TF_LITE_TENSORFLOW_PROFILER

namespace {

template <typename T>
T AlignTo(size_t alignment, T offset) {
  return offset % alignment == 0 ? offset
                                 : offset + (alignment - offset % alignment);
}

}  // namespace

namespace tflite {

void SimpleMemoryArena::PurgeAfter(int32_t node) {
  for (int i = 0; i < active_allocs_.size(); ++i) {
    if (active_allocs_[i].first_node > node) {
      // alloc is allocated after node, so mark it for deletion.
      active_allocs_[i].tensor = -1;
    }
  }
  active_allocs_.erase(
      std::remove_if(active_allocs_.begin(), active_allocs_.end(),
                     [](ArenaAllocWithUsageInterval& alloc) {
                       return alloc.tensor == -1;
                     }),
      active_allocs_.end());
}

void SimpleMemoryArena::PurgeActiveAllocs(int32_t node) {
  for (int i = 0; i < active_allocs_.size(); ++i) {
    if (active_allocs_[i].last_node < node) {
      // alloc is deallocated before node, so mark it for deletion..
      active_allocs_[i].tensor = -1;
    }
  }
  active_allocs_.erase(
      std::remove_if(active_allocs_.begin(), active_allocs_.end(),
                     [](ArenaAllocWithUsageInterval& alloc) {
                       return alloc.tensor == -1;
                     }),
      active_allocs_.end());
}

void SimpleMemoryArena::CalculateActiveAllocs(
    const std::vector<ArenaAllocWithUsageInterval>& allocs, int32_t node) {
  active_allocs_.clear();
  for (int i = 0; i < allocs.size(); ++i) {
    if (allocs[i].first_node <= node && allocs[i].last_node >= node) {
      active_allocs_.push_back(allocs[i]);
    }
  }
  std::sort(active_allocs_.begin(), active_allocs_.end());
}

void SimpleMemoryArena::ResetAllocs() { active_allocs_.clear(); }

TfLiteStatus SimpleMemoryArena::Allocate(
    TfLiteContext* context, size_t alignment, size_t size, int32_t tensor,
    int32_t first_node, int32_t last_node,
    ArenaAllocWithUsageInterval* new_alloc) {
  TF_LITE_ENSURE(context, alignment <= arena_alignment_);
  new_alloc->tensor = tensor;
  new_alloc->first_node = first_node;
  new_alloc->last_node = last_node;
  new_alloc->size = size;
  if (size == 0) {
    new_alloc->offset = 0;
    return kTfLiteOk;
  }
  // If we don't find a better gap just allocate at the end of the buffer.
  const size_t kOffsetNotAssigned = std::numeric_limits<size_t>::max();
  size_t best_offset = kOffsetNotAssigned;
  size_t best_offset_fit = kOffsetNotAssigned;

  // Go through the sorted allocs and look at the gaps between them.
  size_t current_offset = 0;
  for (const auto& alloc : active_allocs_) {
    if (alloc.last_node < first_node || alloc.first_node > last_node) {
      // Usage interval of alloc doesn't intersect with current tensor's usage
      // interval, so we skip it.
      continue;
    }
    size_t aligned_current_offset = AlignTo(alignment, current_offset);
    // If we found a gap larger than required size, and smaller than previous
    // best fit, take it.
    if (aligned_current_offset + size <= alloc.offset &&
        alloc.offset - aligned_current_offset < best_offset_fit) {
      best_offset = aligned_current_offset;
      best_offset_fit = alloc.offset - current_offset;
    }
    current_offset = std::max(current_offset, alloc.offset + alloc.size);
    // A gap of zero is as good as it gets, no point continuing.
    if (best_offset_fit == 0) {
      break;
    }
  }
  if (best_offset == kOffsetNotAssigned) {
    best_offset = AlignTo(alignment, current_offset);
  }

  // Update the required buffer size.
  high_water_mark_ = std::max(high_water_mark_, best_offset + size);
  new_alloc->offset = best_offset;

  auto insertion_it = std::upper_bound(active_allocs_.begin(),
                                       active_allocs_.end(), *new_alloc);
  active_allocs_.insert(insertion_it, *new_alloc);
  return kTfLiteOk;
}

TfLiteStatus SimpleMemoryArena::Commit(TfLiteContext* context,
                                       bool* arena_reallocated) {
  size_t required_size = RequiredBufferSize();
  if (required_size > underlying_buffer_size_) {
    *arena_reallocated = true;
#ifdef TF_LITE_TENSORFLOW_PROFILER
    PauseHeapMonitoring(/*pause=*/true);
    OnTfLiteArenaAlloc(subgraph_index_, reinterpret_cast<std::uintptr_t>(this),
                       required_size);
#endif
    char* new_alloc = new char[required_size];
    char* new_underlying_buffer_aligned_ptr = reinterpret_cast<char*>(
        AlignTo(arena_alignment_, reinterpret_cast<intptr_t>(new_alloc)));

    // If the arena had been previously allocated, copy over the old memory.
    // Since Alloc pointers are offset based, they will remain valid in the new
    // memory block.
    if (high_water_mark_ > 0 && underlying_buffer_size_ > 0) {
      size_t copy_amount = std::min(
          underlying_buffer_.get() + underlying_buffer_size_ -
              underlying_buffer_aligned_ptr_,
          new_alloc + required_size - new_underlying_buffer_aligned_ptr);
      memcpy(new_underlying_buffer_aligned_ptr, underlying_buffer_aligned_ptr_,
             copy_amount);
    }

#ifdef TF_LITE_TENSORFLOW_PROFILER
    if (underlying_buffer_size_ > 0) {
      OnTfLiteArenaDealloc(subgraph_index_,
                           reinterpret_cast<std::uintptr_t>(this),
                           underlying_buffer_size_);
    }
#endif
    underlying_buffer_.reset(new_alloc);
    underlying_buffer_size_ = required_size;
    underlying_buffer_aligned_ptr_ = new_underlying_buffer_aligned_ptr;
#ifdef TF_LITE_TENSORFLOW_PROFILER
    PauseHeapMonitoring(/*pause=*/false);
#endif
  } else {
    *arena_reallocated = false;
  }
  committed_ = true;
  return underlying_buffer_ != nullptr ? kTfLiteOk : kTfLiteError;
}

TfLiteStatus SimpleMemoryArena::ResolveAlloc(
    TfLiteContext* context, const ArenaAllocWithUsageInterval& alloc,
    char** output_ptr) {
  TF_LITE_ENSURE(context, committed_);
  TF_LITE_ENSURE(context, output_ptr != nullptr);
  TF_LITE_ENSURE(context,
                 underlying_buffer_size_ >= (alloc.offset + alloc.size));
  if (alloc.size == 0) {
    *output_ptr = nullptr;
  } else {
    *output_ptr = underlying_buffer_aligned_ptr_ + alloc.offset;
  }
  return kTfLiteOk;
}

TfLiteStatus SimpleMemoryArena::ClearPlan() {
  committed_ = false;
  high_water_mark_ = 0;
  active_allocs_.clear();
  return kTfLiteOk;
}

TfLiteStatus SimpleMemoryArena::ReleaseBuffer() {
  committed_ = false;
#ifdef TF_LITE_TENSORFLOW_PROFILER
  OnTfLiteArenaDealloc(subgraph_index_, reinterpret_cast<std::uintptr_t>(this),
                       underlying_buffer_size_);
#endif
  underlying_buffer_size_ = 0;
  underlying_buffer_aligned_ptr_ = nullptr;
  underlying_buffer_.reset();
  return kTfLiteOk;
}

// Using weak symbols to create a pluggable debugging module.
TFLITE_ATTRIBUTE_WEAK void DumpArenaInfo(
    const std::string& name, const std::vector<int>& execution_plan,
    size_t arena_size, const std::vector<ArenaAllocWithUsageInterval>& allocs) {
}

void SimpleMemoryArena::DumpDebugInfo(
    const std::string& name, const std::vector<int>& execution_plan) const {
  tflite::DumpArenaInfo(name, execution_plan, underlying_buffer_size_,
                        active_allocs_);
}

}  // namespace tflite