<< 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) {

#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"

### Hardware attacks

Physical GPUs or TPUs can also be the target of attacks. [Published
research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running

///   invariants (i.e., guarantee the preconditions before calling the operation
///   and check the postconditions after the operation returns). If plugins need
///   additional invariants, they should be checked on the plugin side and the
///   `status` out variable should be updated accordingly (e.g., to include
///   plugin version information that relates to the condition change).
///

   ```
   @tf.py_function(Tout=tf.float32)
   def my_fun(x):
     print("This always executes eagerly.")
     return x+1
   ```

* `tf.lite`
    * Strided_Slice now supports `UINT32`.

* `tf.config.experimental.enable_tensor_float_32_execution`

#include "tensorflow/core/config/flag_defs.h"
#include "tensorflow/core/config/flags.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/lib/gtl/flatmap.h"
#include "tensorflow/core/lib/gtl/flatset.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/types.h"

# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#

#       export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#       export TF_ANY_MODE="test" or "build" or "run" (default: "test")
#       ./any.sh
#
# 2. RUN ANY OTHER SCRIPT AND ENV WITH NO SIDE EFFECTS (NO UPLOADS)
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_SCRIPT=ci/official/wheel.sh
#       ./any.sh
#
# 3. DO THE SAME WITH A LOCAL CACHE OR RBE: