%cst = arith.constant dense<[3, 4]> : tensor<2xi32>
  %cst_0 = arith.constant dense<1.000000e+00> : tensor<3x4xf32>
  %0 = "tfl.reshape"(%arg0, %cst) : (tensor<*xf32>, tensor<2xi32>) -> tensor<3x4xf32>
  %1 = "tfl.add"(%0, %cst_0) {fused_activation_function = "NONE"} : (tensor<3x4xf32>, tensor<3x4xf32>) -> tensor<3x4xf32>
  func.return %1 : tensor<3x4xf32>
// CHECK-LABEL: ReshapeAddUnknownShape

// CHECK:           %[[VALUES:.*]], %[[INDICES:.*]] = "tf.TopKV2"(%[[ARG_0]], %[[K]]) <{sorted = true}> : (tensor<3x6xf32>, tensor<i32>) -> (tensor<3x6xf32>, tensor<3x6xi32>)
// CHECK:           return %[[VALUES]], %[[INDICES]] : tensor<3x6xf32>, tensor<3x6xi32>
// CHECK:         }
func.func @convert_sort_to_topk_iota_broadcast(%arg0: tensor<3x6xf32>) -> (tensor<3x6xf32>, tensor<3x6xi32>) {
  %0 = "mhlo.iota"() <{ iota_dimension = 0 : i64 }> : () -> tensor<6xi32>

// -----

// CHECK-LABEL: func @einsum
func.func @einsum(%arg0: tensor<2x3xf32>, %arg1: tensor<3x4xf32>) -> tensor<2x4xf32> {
  // CHECK:  mhlo.einsum
  %0 = "tf.Einsum"(%arg0, %arg1) {equation = "ab,bc->ac"} : (tensor<2x3xf32>, tensor<3x4xf32>) -> tensor<2x4xf32>
  func.return %0: tensor<2x4xf32>
}

// -----

// CHECK-LABEL: func @unary_einsum