*   <li>With finite tolerance, {@code Double.POSITIVE_INFINITY} and {@code
   *       Double.NEGATIVE_INFINITY} are fuzzily equal only to themselves.
   * </ul>
   *
   * <p>This is reflexive and symmetric, but not transitive, so it is not an
   * equivalence relation and not suitable for use in {@link Object#equals}
   * implementations.
   *

		blockSize *= 2
	}
}

// symMerge{{.FuncSuffix}} merges the two sorted subsequences data[a:m] and data[m:b] using
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
// Computer Science, pages 714-723. Springer, 2004.
//
// Let M = m-a and N = b-n. Wolog M < N.

}

table LeakyReluOptions {
  alpha:float;
}

table SquaredDifferenceOptions {
}

enum MirrorPadMode : byte {
  // Doesn't include borders.
  REFLECT = 0,
  // Includes borders.
  SYMMETRIC = 1,
}

table MirrorPadOptions {
  mode:MirrorPadMode;
}

table UniqueOptions {
  idx_out_type:TensorType = INT32;
}

table ReverseV2Options {
}

table AddNOptions {
}

   * {@linkplain #intersection intersection} (as a single, possibly-empty range) if and only if this
   * method returns {@code true}.
   *
   * <p>The connectedness relation is both reflexive and symmetric, but does not form an {@linkplain
   * Equivalence equivalence relation} as it is not transitive.
   *
   * <p>Note that certain discrete ranges are not considered connected, even though there are no

   * {@linkplain #intersection intersection} (as a single, possibly-empty range) if and only if this
   * method returns {@code true}.
   *
   * <p>The connectedness relation is both reflexive and symmetric, but does not form an {@linkplain
   * Equivalence equivalence relation} as it is not transitive.
   *
   * <p>Note that certain discrete ranges are not considered connected, even though there are no

	}

	// Add final 0 utilization event to any remaining series. This
	// is important to mark the end of the trace. The exact value
	// shouldn't matter since no window should extend beyond this,
	// but using 0 is symmetric with the start of the trace.
	mu := MutatorUtil{int64(lastEv.Time()), 0}
	for i := range ps {
		out[ps[i].series] = addUtil(out[ps[i].series], mu)
	}
	return out
}

			u.tracef("depth %d >= %d", u.depth, unificationDepthLimit)
		}
		if panicAtUnificationDepthLimit {
			panic("unification reached recursion depth limit")
		}
		return false
	}

	// Unification is symmetric, so we can swap the operands.
	// Ensure that if we have at least one
	// - defined type, make sure one is in y
	// - type parameter recorded with u, make sure one is in x

  alpha:float;
}

table SquaredDifferenceOptions {
}

// LINT.IfChange
enum MirrorPadMode : byte {
  // Doesn't include borders.
  REFLECT = 0,
  // Includes borders.
  SYMMETRIC = 1,
}
// LINT.ThenChange(//tensorflow/compiler/mlir/lite/ir/tfl_op_enums.td)

table MirrorPadOptions {
  mode:MirrorPadMode;
}

table UniqueOptions {
  idx_out_type:TensorType = INT32;

			u.tracef("depth %d >= %d", u.depth, unificationDepthLimit)
		}
		if panicAtUnificationDepthLimit {
			panic("unification reached recursion depth limit")
		}
		return false
	}

	// Unification is symmetric, so we can swap the operands.
	// Ensure that if we have at least one
	// - defined type, make sure one is in y
	// - type parameter recorded with u, make sure one is in x

  func.func @mirror_pad(%arg0: tensor<2x3xcomplex<f64>>) -> tensor<4x7xcomplex<f64>> {
    %0 = mhlo.constant dense<[[1, 1], [2, 2]]> : tensor<2x2xi32>
    // CHECK-NOT: tf.MirrorPad
    %1 = "tf.MirrorPad"(%arg0, %0) {mode = "SYMMETRIC"} : (tensor<2x3xcomplex<f64>>, tensor<2x2xi32>) -> tensor<4x7xcomplex<f64>>
    func.return %1 : tensor<4x7xcomplex<f64>>
  }

  // CHECK-LABEL: bucketize