device: "/job:localhost/replica:0/task:0/device:GPU:0"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
}
node {
  name: "max_pooling2d_1/MaxPool"
  op: "MaxPool"
  input: "pool1_pad_1/Pad"
  device: "/job:localhost/replica:0/task:0/device:GPU:0"
  attr {
    key: "T"
    value {
      type: DT_HALF
    }
  }
  attr {

}

// CHECK-LABEL:   func @convert_maxpool_valid(
// CHECK-SAME:                                %[[VAL_0:.*]]: tensor<4x16x16x8xf32>) -> tensor<4x7x7x8xf32> {
// CHECK:           %[[VAL_1:.*]] = "tf.MaxPool"(%[[VAL_0]]) <{data_format = "NHWC", explicit_paddings = [], ksize = [1, 3, 3, 1], padding = "VALID", strides = [1, 2, 2, 1]}> : (tensor<4x16x16x8xf32>) -> tensor<4x7x7x8xf32>
// CHECK:           return %[[VAL_1]] : tensor<4x7x7x8xf32>

    key: "_class"
    value {
      list {
        s: "loc:@bn_conv1_1/AssignMovingAvg_1/AssignSubVariableOp"
      }
    }
  }
}
node {
  name: "max_pooling2d_1/MaxPool"
  op: "MaxPool"
  input: "activation_50/Relu"
  device: "/job:localhost/replica:0/task:0/device:GPU:0"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {

};

using ConvertAvgPool2DGradOp =
    ConvertAvgPoolGradOp<TF::AvgPoolGradOp, /*num_dims=*/4>;
using ConvertAvgPool3DGradOp =
    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>

*   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))

  let builders = [
    OpBuilder<(ins "Value":$input, "Value":$reduction_indices,
      "BoolAttr":$keep_dims)>
  ];
}

def TF_MaxPoolOp : TF_Op<"MaxPool", [Pure, TF_FoldOperandsTransposeInterface, TF_LayoutSensitiveInterface]> {
  let summary = "Performs max pooling on the input.";

  let arguments = (ins