if (ops_->new_random_access_file == nullptr)
    return errors::Unimplemented(tensorflow::strings::StrCat(
        "Filesystem for ", fname, " does not support NewRandomAccessFile()"));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  auto file = std::make_unique<TF_RandomAccessFile>();
  std::string translated_name = TranslateName(fname);
  ops_->new_random_access_file(filesystem_.get(), translated_name.c_str(),

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

  TF_RETURN_IF_ERROR(
      CheckABI(ops->filesystem_ops_abi, TF_FILESYSTEM_OPS_ABI, "filesystem"));

  if (ops->random_access_file_ops != nullptr)
    TF_RETURN_IF_ERROR(CheckABI(ops->random_access_file_ops_abi,
                                TF_RANDOM_ACCESS_FILE_OPS_ABI,
                                "random access file"));

  if (ops->writable_file_ops != nullptr)
    TF_RETURN_IF_ERROR(CheckABI(ops->writable_file_ops_abi,

// SECTION 1. Implementation for `TF_RandomAccessFile`
// ----------------------------------------------------------------------------
namespace tf_random_access_file {

// TODO(b/139060984): Implement later

}  // namespace tf_random_access_file

// SECTION 2. Implementation for `TF_WritableFile`
// ----------------------------------------------------------------------------
namespace tf_writable_file {

      std::function<void(void*)> plugin_memory_free)
      : filesystem_(std::move(filesystem)),
        ops_(std::move(filesystem_ops)),
        random_access_file_ops_(std::move(random_access_file_ops)),
        writable_file_ops_(std::move(writable_file_ops)),
        read_only_memory_region_ops_(std::move(read_only_memory_region_ops)),
        plugin_memory_allocate_(std::move(plugin_memory_allocate)),

  ops->filesystem_ops_api = TF_FILESYSTEM_OPS_API;
  ops->filesystem_ops_size = TF_FILESYSTEM_OPS_SIZE;
  ops->random_access_file_ops_abi = TF_RANDOM_ACCESS_FILE_OPS_ABI;
  ops->random_access_file_ops_api = TF_RANDOM_ACCESS_FILE_OPS_API;
  ops->random_access_file_ops_size = TF_RANDOM_ACCESS_FILE_OPS_SIZE;
  ops->writable_file_ops_abi = TF_WRITABLE_FILE_OPS_ABI;
  ops->writable_file_ops_api = TF_WRITABLE_FILE_OPS_API;

code in context of the TensorFlow service, it is important to design isolation
mechanisms that prevent unwanted access to the data from other tenants.

Network isolation between different models is also important not only to prevent
unauthorized access to data or models, but also to prevent malicious users or
tenants sending graphs to execute under another tenant’s identity.

    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }
    ],
    "access_right": "open",

  TF_SetFilesystemVersionMetadata(ops);
  ops->scheme = strdup(uri);

  ops->random_access_file_ops = static_cast<TF_RandomAccessFileOps*>(
      plugin_memory_allocate(TF_RANDOM_ACCESS_FILE_OPS_SIZE));
  ops->random_access_file_ops->cleanup = tf_random_access_file::Cleanup;
  ops->random_access_file_ops->read = tf_random_access_file::Read;

  ops->writable_file_ops = static_cast<TF_WritableFileOps*>(

  TF_SetFilesystemVersionMetadata(ops);
  ops->scheme = strdup(uri);

  ops->random_access_file_ops = static_cast<TF_RandomAccessFileOps*>(
      plugin_memory_allocate(TF_RANDOM_ACCESS_FILE_OPS_SIZE));
  ops->random_access_file_ops->cleanup = tf_random_access_file::Cleanup;
  ops->random_access_file_ops->read = tf_random_access_file::Read;

  ops->writable_file_ops = static_cast<TF_WritableFileOps*>(