v2_reader_->Seek(kHeaderEntryKey);
  for (v2_reader_->Next(); v2_reader_->Valid(); v2_reader_->Next()) {
    if (filtered_keys.count(string(v2_reader_->key())) > 0) continue;
    CHECK(entry.ParseFromArray(v2_reader_->value().data(),
                               v2_reader_->value().size()))
        << entry.InitializationErrorString();
    string key(v2_reader_->key());

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >
  BuildV2VarMaps();

  // Invariant: exactly one of "reader_" and "v2_reader_" is non-null.

semantics to match NumPy. * `tf.split` now takes arguments in a reversed order
and with different keywords. In particular, we now match NumPy order as
`tf.split(value, num_or_size_splits, axis)`. * `tf.sparse_split` now takes
arguments in reversed order and with different keywords. In particular we now
match NumPy order as `tf.sparse_split(sp_input, num_split, axis)`. NOTE: we have

# Do not sort: Copybara rule
# copybara:uncomment_begin
# # buildifier: disable=out-of-order-load
# load("//devtools/build_cleaner/skylark:action_config_test.bzl", "action_config_test")
# load("//devtools/copybara/rules:copybara.bzl", "copybara_config_test")
# load("@rules_license//rules:license.bzl", "license")
# # buildifier: enable=out-of-order-load
# copybara:uncomment_end

# copybara:comment_begin(oss-only)

              "Internal state of the gradient tape is invalid: "
              "none of operations outputs match expected tensor");
        }
      } else {
        // This target tensor was not generated by any operation recorded on
        // the tape, so no gradient needs to be computed from it unless this
        // target is also a source.
        auto source_tensor = sources_that_are_targets.find(id);

// order, and type) the op declaration.  For example, the "Concat" op
// has registration:
//   REGISTER_OP("Concat")
//       .Input("concat_dim: int32")
//       .Input("values: N * T")
//       .Output("output: T")
//       .Attr("N: int >= 2")
//       .Attr("T: type");
// that defines two inputs, "concat_dim" and "values" (in that order).