// SECTION 3. Implementation for `TF_ReadOnlyMemoryRegion`
// ----------------------------------------------------------------------------
namespace tf_read_only_memory_region {

// TODO(b/139060984): Implement later

}  // namespace tf_read_only_memory_region

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------

                                    /*remote_func_outputs=*/true);
}
TEST(CAPI, RemoteExecuteSilentCopiesLocalAsyncFuncOrdering) {
  // A remote input may be not ready when we start running a function. Test that
  // the function execution should wait until the remote input is ready.
  TestRemoteExecuteSilentCopiesFunc(/*async=*/true, /*remote=*/false,
                                    /*heavy_load_on_streaming_rpc=*/true);
}

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

  }
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> read_op(
      TFE_NewOp(context.get(), "ReadVariableOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpSetAttrType(read_op.get(), "dtype", TF_FLOAT);
  parallel_device.Execute(context.get(), handle_inputs, "ReadVariableOp",
                          TFE_OpGetAttrs(read_op.get()),

  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TF_DeleteStatus(status);
}

// Read the value of variable `var` and save it into `out_value`.
void ReadVariable(TFE_Context* ctx, TFE_TensorHandle* var,
                  TFE_TensorHandle** out_value) {
  TF_Status* status = TF_NewStatus();

  std::vector<char> out;

  // First read.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

  // Second read. Hit cache.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

  // Third read. File signatures are different.

}

int64_t RamFileBlockCache::Read(const std::string& filename, size_t offset,
                                size_t n, char* buffer, TF_Status* status) {
  if (n == 0) {
    TF_SetStatus(status, TF_OK, "");
    return 0;
  }
  if (!IsCacheEnabled() || (n > max_bytes_)) {
    // The cache is effectively disabled, so we pass the read through to the
    // fetcher without breaking it up into blocks.

    size_t chunk = size - offset;
    if (chunk > kPosixCopyFileBufferSize) chunk = kPosixCopyFileBufferSize;

    rc = read(src_fd, buffer.get(), chunk);
    if (rc < 0) return -1;

    int total_write = 0;
    int total_read = rc;
    while (total_write < total_read && rc > 0) {
      rc = write(dst_fd, buffer.get() + total_write, chunk - total_write);
      if (rc < 0) return -1;

      total_write += rc;

  tf_gcs_filesystem::ExpiringLRUCache<int> cache2(2, 4);
  num_compute_calls = 0;
  value = -1;

  // Read our first value
  cache2.LookupOrCompute("a", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 0);
  EXPECT_EQ(num_compute_calls, 1);
  // Re-read, exepct no additional function compute_func calls.
  cache2.LookupOrCompute("a", &value, compute_func, &status);

}

Status ModularRandomAccessFile::Read(uint64 offset, size_t n,
                                     StringPiece* result, char* scratch) const {
  if (ops_->read == nullptr)
    return errors::Unimplemented(
        tensorflow::strings::StrCat("Read() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  int64_t read =