std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding
  // session has been run (this is detected in RecordMutation function). If the
  // string is empty, no mutation has occurred. Otherwise the string is a

// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

// Records the inputs in the `ForwardOperation`.
Status AddInput(AbstractOperation*, AbstractTensorHandle*, ForwardOperation*);

  absl::MutexLock l(&block->mu);
  if (block->state != FetchState::FINISHED) {
    return true;  // No need to check for staleness.
  }
  if (max_staleness_ == 0) return true;  // Not enforcing staleness.
  return timer_seconds_() - block->timestamp <= max_staleness_;
}

std::shared_ptr<RamFileBlockCache::Block> RamFileBlockCache::Lookup(
    const Key& key) {
  absl::MutexLock lock(&mu_);
  auto entry = block_map_.find(key);

#include <memory>

#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/cloud/now_seconds_env.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

TEST(ExpiringLRUCacheTest, MaxAge) {
  const string key = "a";
  std::unique_ptr<NowSecondsEnv> env(new NowSecondsEnv);

  // or 10 seconds have elapsed (at which point it will respond with an error).
  const int callers = 4;
  BlockingCounter counter(callers);
  auto fetcher = [&counter](const string& filename, size_t offset, size_t n,
                            char* buffer, TF_Status* status) -> int64_t {
    counter.DecrementCount();
    if (!counter.WaitFor(std::chrono::seconds(10))) {

  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(const AbstractTensorHandle*);
  // Records an operation with given inputs and outputs
  // on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has a trainable dtype.
  // op_name is optional and is used for debugging only.

Copyright (c) 2014, the respective contributors
All rights reserved.

Caffe uses a shared copyright model: each contributor holds copyright over
their contributions to Caffe. The project versioning records all such
contribution and copyright details. If a contributor wants to further mark
their specific copyright on a particular contribution, they should indicate
their copyright solely in the commit message of the change when it is

  //
  // Arguments provide enough information to reconstruct the original `TFE_Op`,
  // or construct a transformed version, by inspecting the passed `op`.
  //
  // TFE_OpGetDevice(op) records the original placement of the operation. It may
  // be an empty string if no device was explicitly requested, but will
  // otherwise be the name of this custom device. Ops are placed onto a custom

  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(int64_t tensor_id);

  // Records an operation with inputs `input_tensor_id` and outputs
  // `output_tensors` on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has trainable dtype.
  //

  /// `max_age` is also 0, the cache will not be populated).
  ExpiringLRUCache(uint64_t max_age, size_t max_entries,
                   std::function<uint64_t()> timer_seconds = TF_NowSeconds)
      : max_age_(max_age),
        max_entries_(max_entries),
        timer_seconds_(timer_seconds) {}

  /// Insert `value` with key `key`. This will replace any previous entry with
  /// the same key.
  void Insert(const std::string& key, const T& value) {