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

      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)),

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.

  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*>(

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

    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;

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

# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.platform import tf_logging as _logging