TensorShape x_shape({1, 3, 7, 1});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));
  // Force consistent pooling regions for unit testing.
  auto y = FractionalMaxPool(
      scope_, x, {1, 1.2, 1.9, 1},
      FractionalMaxPool::Deterministic(true).Overlapping(true).Seed(1).Seed2(
          2));
  Tensor x_init_value = Tensor(DT_FLOAT, x_shape);
  SetRandomValuesForMaxPooling<float>(&x_init_value);

      op.output(2), internal::FractionalMaxPoolGrad::Overlapping(overlapping));
  grad_outputs->push_back(dx);
  return scope.status();
}
REGISTER_GRADIENT_OP("FractionalMaxPool", FractionalMaxPoolGradHelper);

// Templated constructor for FusedBatchNormGrad[..]::Attrs.
template <typename T>
T FusedBatchNormGradAttrs(float epsilon, StringPiece data_format,

*   Fixes a `CHECK` fail in `SdcaOptimizer` ([CVE-2022-41899](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-41899))
*   Fixes a heap OOB in `FractionalAvgPool` and `FractionalMaxPool`([CVE-2022-41900](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-41900))
*   Fixes a `CHECK_EQ` in `SparseMatrixNNZ` ([CVE-2022-41901](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-41901))