<< entry.InitializationErrorString();
    for (int i = 0; i < entry.slices_size(); ++i) {
      const auto& slice_proto = entry.slices(i);
      CHECK(filtered_keys
                .insert(EncodeTensorNameSlice(
                    string(v2_reader_->key()) /* full var's name */,
                    TensorSlice(slice_proto)))
                .second);
    }
  }

#include "tensorflow/core/util/tensor_slice_reader.h"

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

// A wrapper around BundleReader (for V2 checkpoints) and
// checkpoint::TensorSliceReader (for V1), that is more easily SWIG wrapped for
// other languages.
//
// The class currently only interacts with single-slice (i.e., non-partitioned)
// variables.
class CheckpointReader {

  }
  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;
  TF_Tensor* a = TF_TensorFromTensor(y, &status);
  if (TF_TensorDefaultAlignment() > 0) {

`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually

# Experimental filesystem C APIs for TensorFlow.
# Will be moved in proper place once all filesystems are converted to the
# modular framework.
load("//tensorflow:tensorflow.bzl", "tf_cc_test")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# This is only for plugins
cc_library(
    name = "filesystem_interface",

# Note that files created under Docker will be owned by "root".
ls build_output
```

## Contribution & Maintenance

The TensorFlow team does not yet have guidelines in place for contributing to
this directory. We are working on it. Please join a TF SIG Build meeting (see:
bit.ly/tf-sig-build-notes) if you'd like to discuss the future of contributions.

### Brief System Overview

  echo "Use 'devtoolset-9' to build a manylinux2014 compatible toolchain"
  exit 1
  ;;
esac

mkdir -p "${TARGET}"

mkdir -p ${TARGET}/usr/include

# Put the current kernel headers from ubuntu in place.
ln -s "/usr/include/linux" "${TARGET}/usr/include/linux"
ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm"

#include "tensorflow/core/framework/versions.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/graph/node_builder.h"
#include "tensorflow/core/graph/validate.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/platform/coding.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/mem.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/platform/protobuf.h"

/// can be used to track state in between calls (from an object oriented point
/// of view, this can be viewed as a "vtable" for a "class" -- that is the
/// corresponding struct above --; the first argument is in place of `this`).
///
/// Except where noted otherwise, all pointer arguments are owned by core
/// TensorFlow and are guaranteed to not be `nullptr`.
///

# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no
# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via
# REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from