DefaultValuedOptionalAttr<TF_AnyStrAttrOf<["NDHWC", "NCDHW"]>, "\"NDHWC\"">:$data_format
  );

  let results = (outs
    Res<TF_IntOrFpTensor, [{Gradients of gradients w.r.t. the input to `max_pool`.}]>:$output
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}

def TF_MaxPoolGradOp : TF_Op<"MaxPoolGrad", [Pure]> {

    ConvertAvgPoolGradOp<TF::AvgPool3DGradOp, /*num_dims=*/5>;

// Converts MaxPool op to HLO ReduceWindow op by setting appropriate window
// dimensions with max as the reduction function.
//
// Sample result for VALID padding mode:
//
//   %init = arith.constant dense<...> : tensor<i32>
//   %max_pool = "mhlo.reduce"(%inp, %init) ["mhlo.maximum"]

*   Fixes a `CHECK` fail in `tf.linalg.matrix_rank` ([CVE-2022-35988](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35988))
*   Fixes a `CHECK` fail in `MaxPool` ([CVE-2022-35989](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35989))
*   Fixes a `CHECK` fail in `Conv2DBackpropInput` ([CVE-2022-35999](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35999))