// 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 {

this file with a file generated from [`api_template.__init__.py`](https://www.github.com/tensorflow/tensorflow/blob/master/tensorflow/api_template.__init__.py)
"""
# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top

import distutils as _distutils
import importlib
import inspect as _inspect
import os as _os
import site as _site
import sys as _sys

# 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

  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

  return response;
}

int TF_DeviceListCount(const TF_DeviceList* list) {
  return list->response.size();
}

#define TF_DEVICELIST_METHOD(return_type, method_name, accessor, err_val) \
  return_type method_name(const TF_DeviceList* list, const int index,     \
                          TF_Status* status) {                            \

    data[i] = 0;
  }
  if (TF_TensorDefaultAlignment() > 0) {
    EXPECT_TRUE(TF_TensorIsAligned(a));
  }
  TF_DeleteTensor(a);
}

TEST(CAPI, TestTensorIsNotAligned) {
  // Test unaligned access via a Slice.
  Tensor x(DT_FLOAT, TensorShape({30}));
  x.flat<float>().setConstant(0.0);

  // Take an unaligned slice.
  Tensor y = x.Slice(1, 13);
  Status status;

  // Execute.
  TF_ExecuteOperation(add_op, 2, inputs, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Test that full type information can be accessed.
  auto outs = unwrap(add_outputs);
  auto h = outs->outputs[0];
  ASSERT_NE(h, nullptr);
  ASSERT_EQ(h->FullType().type_id(), TFT_UNSET);
  ASSERT_EQ(unwrap(inputs[0])->FullType().type_id(), TFT_UNSET);

  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_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,