EXPECT_EQ(calls.find(offset), calls.end()) << "at offset " << offset;
    calls.insert(offset);
    memset(buffer, 'x', n);
    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  const uint32 block_count = 256;
  tf_gcs_filesystem::RamFileBlockCache cache(
      block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  out.resize(block_count, 0);

      break;
    case TF_DataType::TF_INT8:
    case TF_DataType::TF_INT16:
    case TF_DataType::TF_INT32:
    case TF_DataType::TF_INT64:
      dtype.code = DLDataTypeCode::kDLInt;
      break;
    case TF_DataType::TF_UINT8:
    case TF_DataType::TF_UINT16:
    case TF_DataType::TF_UINT32:
    case TF_DataType::TF_UINT64:
      dtype.code = DLDataTypeCode::kDLUInt;
      break;
    case TF_DataType::TF_BFLOAT16:

-     __extension__ __STRING2_SMALL_GET32 (src, 4)
-#  endif
-__STRING_INLINE char *__strcpy_small (char *, __uint16_t, __uint16_t,
-				      __uint32_t, __uint32_t, size_t);
 __STRING_INLINE char *
 __strcpy_small (char *__dest,
 		__uint16_t __src0_2, __uint16_t __src4_2,
@@ -482,42 +257,6 @@ __strcpy_small (char *__dest,
   return __dest;
 }
 # else
-#  ifndef _FORCE_INLINES

  TF_Tensor* a =
      TF_AllocateTensor(TF_UINT64, dims, 2, 6 * TF_DataTypeSize(TF_UINT64));
  TF_Tensor* b =
      TF_AllocateTensor(TF_UINT64, nullptr, 0, TF_DataTypeSize(TF_UINT64));
  EXPECT_NE(a, nullptr);
  EXPECT_NE(b, nullptr);

  EXPECT_EQ(6, TF_TensorElementCount(a));
  EXPECT_EQ(1, TF_TensorElementCount(b));
  EXPECT_EQ(6 * TF_DataTypeSize(TF_UINT64), TF_TensorByteSize(a));

    ASSERT_EQ(errors::OK, status_.code()) << status_.message();
    X.reset(X_raw);
  }
  // Label
  int32_t Y_vals[] = {1, 0, 1};
  int64_t Y_dims[] = {3};
  AbstractTensorHandlePtr Y;
  {
    AbstractTensorHandle* Y_raw;
    status_ = TestTensorHandleWithDims<int32_t, TF_INT32>(
        immediate_execution_ctx_.get(), Y_vals, Y_dims, 1, &Y_raw);
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    TFE_ContextSetExecutorForThread(ctx, executor);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

    TF_Tensor* t =
        TF_AllocateTensor(TF_INT32, nullptr, 0, 1 * sizeof(tensorflow::int32));
    *reinterpret_cast<tensorflow::int32*>(TF_TensorData(t)) = 42;
    TFE_TensorHandle* h = TFE_NewTensorHandle(t, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TF_DeleteTensor(t);

                                         undeleted_dirs);

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  std::string translated_name = TranslateName(dirname);
  uint64_t plugin_undeleted_files, plugin_undeleted_dirs;
  ops_->delete_recursively(filesystem_.get(), translated_name.c_str(),
                           &plugin_undeleted_files, &plugin_undeleted_dirs,

  if (!status.ok()) GTEST_SKIP() << "CreateDir() not supported: " << status;

  uint64 size;
  status = env_->GetFileSize(dirpath, &size);
  EXPECT_PRED2(UnimplementedOrReturnsCode, status, Code::FAILED_PRECONDITION);
}

TEST_P(ModularFileSystemTest, TestGetFileSizeNotFound) {
  const std::string filepath = GetURIForPath("a_dir");
  uint64 size;
  Status status = env_->GetFileSize(filepath, &size);

  EXPECT_EQ(value, 4);
  EXPECT_TRUE(cache2.Lookup("e", &value));
  EXPECT_EQ(value, 5);
}

TEST(ExpiringLRUCacheTest, LookupOrCompute) {
  // max_age of 0 means we should always compute.
  uint64 num_compute_calls = 0;
  tf_gcs_filesystem::ExpiringLRUCache<int>::ComputeFunc compute_func =
      [&num_compute_calls](const string& key, int* value, TF_Status* status) {
        *value = num_compute_calls;

  return cache_size_;
}

void RamFileBlockCache::Prune() {
  while (!stop_pruning_thread_.WaitForNotificationWithTimeout(
      absl::Microseconds(1000000))) {
    absl::MutexLock lock(&mu_);
    uint64_t now = timer_seconds_();
    while (!lra_list_.empty()) {
      auto it = block_map_.find(lra_list_.back());
      if (now - it->second->timestamp <= max_staleness_) {