<< 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 {

    }
    auto begin = data.begin();
    if (offset > pos) {
      // The block begins before the slice we're reading.
      begin += offset - pos;
    }
    auto end = data.end();
    if (pos + data.size() > offset + n) {
      // The block extends past the end of the slice we're reading.
      end -= (pos + data.size()) - (offset + n);
    }
    if (begin < end) {

  }
  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"

    "creators": [
        {
            "name": "TensorFlow Developers"
        }
    ],
    "access_right": "open",
    "notes": "Specific TensorFlow versions can be found in the \"Versions\" list on the right side of this page.<br>See the full list of authors <a href=\"https://github.com/tensorflow/tensorflow/graphs/contributors\">on GitHub</a>."

### 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"