// CHECK:           %12 = "tf.Reshape"(%0, %11) : (tensor<2x?x3x4xf32>, tensor<4xi32>) -> tensor<2x?x3x4xf32>
// CHECK:           %13 = "tf.BatchMatMulV3"(%6, %12) <{adj_x = false, adj_y = false, grad_x = false, grad_y = false}> : (tensor<2x?x2x3xf32>, tensor<2x?x3x4xf32>) -> tensor<2x?x2x4xf32>
// CHECK:           %14 = "tf.Shape"(%arg0) : (tensor<2x?x2x3xf32>) -> tensor<4xi32>

func.func @ConvertIdentityGatherNdOp3D(%arg0: tensor<4x3x4xf32>) -> tensor<4x3x4xf32> {
  %cst = arith.constant dense<[[0], [1], [2], [3]]> : tensor<4x1xi32>
  %0 = "tfl.gather_nd"(%arg0, %cst) : (tensor<4x3x4xf32>, tensor<4x1xi32>) -> tensor<4x3x4xf32>
  func.return %0 : tensor<4x3x4xf32>

// CHECK-LABEL: ConvertIdentityGatherNdOp3D
// CHECK-SAME: (%[[ARG:.*]]: tensor<4x3x4xf32>) -> tensor<4x3x4xf32>

  %permutation = "tf.Const"() {value = dense<[2, 1, 0]> : tensor<3xi32>} : () -> (tensor<3xi32>)
  // CHECK: "mhlo.transpose"
  %0 = "tf.Transpose"(%arg0, %permutation) : (tensor<1x2x3xf32>, tensor<3xi32>) -> tensor<3x2x1xf32>
  func.return %0 : tensor<3x2x1xf32>
}

// -----

// CHECK-LABEL: @transpose_3d
func.func @transpose_3d(%arg0: tensor<1x2x3xf32>) -> tensor<3x2x1xf32> {