// 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 {

    if (TF_GetCode(status) != TF_OK) {
      TF_DeleteStatus(status);
      return "";
    }
    TF_DeleteStatus(status);

    // We add a random value into `test_dir` to ensures that two consecutive
    // runs are unlikely to clash.
    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<> distribution;
    std::string rng_val = std::to_string(distribution(gen));

  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*>(

  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);

limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/filesystem/modular_filesystem.h"

#include <memory>
#include <random>
#include <string>

#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/stacktrace_handler.h"
#include "tensorflow/core/platform/test.h"

}

TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype,
                            TF_Graph* graph, TF_Status* s) {
  TF_OperationDescription* desc =
      TF_NewOperation(graph, "RandomUniform", "random_uniform");
  TF_AddInput(desc, {shape, 0});
  TF_SetAttrType(desc, "dtype", dtype);
  return TF_FinishOperation(desc, s);
}

void Split3Helper(TF_Operation* input, TF_Graph* graph, TF_Status* s,

  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,

  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_Tensor* tensor_shape = Int32Tensor({37, 1});
  TF_Operation* shape = Const(tensor_shape, func_graph.get(), s.get(), "shape");
  TF_Operation* random =
      RandomUniform(shape, TF_FLOAT, func_graph.get(), s.get());

  TF_Output outputs[] = {{random, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name,
                             /*append_hash_to_fn_name=*/false, -1,