return {ToOperation(edge->src()), edge->src_output()};
}

void TF_OperationAllInputs(TF_Operation* oper, TF_Output* inputs,
                           int max_inputs) {
  for (auto* edge : oper->node.in_edges()) {
    if (edge->dst_input() >= 0 && edge->dst_input() < max_inputs) {
      inputs[edge->dst_input()] = {ToOperation(edge->src()),
                                   edge->src_output()};
    }
  }
}

                          /*expected_max_outputs=*/1, status.get());
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);
  TF_SetStatus(status.get(), TF_OK, "");

  // Check that ops still run successfully on the device.
  parallel_device.Execute(context.get(), std::vector<ParallelTensor*>(),
                          "VarHandleOp", TFE_OpGetAttrs(handle_op.get()),
                          /*expected_max_outputs=*/1, status.get());

  while (n > 0) {
    // Some platforms, notably macs, throw `EINVAL` if `pread` is asked to read
    // more than fits in a 32-bit integer.
    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

    // `pread` returns a `ssize_t` on POSIX, but due to interface being
    // cross-platform, return type of `Read` is `int64_t`.

                        const TFE_OpAttrs* attributes, int expected_max_outputs,
                        TF_Status* status) const {
  std::vector<PartialTensorShape> expected_output_shapes(expected_max_outputs);
  StartExecute(context, inputs, operation_name, attributes,
               expected_max_outputs, *default_cancellation_manager_);
  auto result = Join(expected_output_shapes, status);

  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_);

  env->SetNowSeconds(6);
  EXPECT_FALSE(cache.Lookup(key, &value));
}

TEST(ExpiringLRUCacheTest, MaxEntries) {
  // max_age of 0 means nothing will be cached.
  tf_gcs_filesystem::ExpiringLRUCache<int> cache1(0, 4);
  cache1.Insert("a", 1);
  int value = 0;
  EXPECT_FALSE(cache1.Lookup("a", &value));
  // Now set max_age = 1 and verify the LRU eviction logic.
  tf_gcs_filesystem::ExpiringLRUCache<int> cache2(1, 4);
  cache2.Insert("a", 1);

    EXPECT_EQ(got_n, want_n);
    calls++;
    memset(buffer, 'x', got_n);
    TF_SetStatus(status, TF_OK, "");
    return got_n;
  };
  // If block_size, max_bytes, or both are zero, or want_n is larger than
  // max_bytes the cache is a pass-through.
  tf_gcs_filesystem::RamFileBlockCache cache1(1, 0, 0, fetcher);
  tf_gcs_filesystem::RamFileBlockCache cache2(0, 1, 0, fetcher);

  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,
                         TF_Status* status) {
  tensorflow::FunctionDefLibrary lib;
  {
    tensorflow::mutex_lock l(g->mu);
    lib = g->graph.flib_def().ToProto();
  }
  const auto len = std::min(max_func, static_cast<int>(lib.function_size()));
  for (int i = 0; i < len; ++i) {

    const std::string& parallel_device_name, TFE_Context* context,
    std::vector<MaybeParallelTensorUnowned> inputs, const char* operation_name,
    const TFE_OpAttrs* attributes, int expected_max_outputs,
    TF_Status* status) {
  absl::optional<std::vector<MaybeParallelTensorOwned>> result;
  // TODO(allenl): We should remove "TPU" from these op names at the very least,

    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_Execute(matmul, &retvals[0], &num_retvals, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    if (state.iterations() >= state.max_iterations && async) {
      TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
      TFE_ExecutorWaitForAllPendingNodes(executor, status);
      ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);