return false
		}
		s.nbytes = s.nbytes + start
	}
	arg32, err := strconv.ParseInt(s.format[start:s.nbytes], 10, 32)
	if err != nil || !ok || arg32 <= 0 || arg32 > int64(len(s.call.Args)-s.firstArg) {
		s.pass.ReportRangef(s.call, "%s format has invalid argument index [%s]", s.name, s.format[start:s.nbytes])
		return false
	}
	s.nbytes++ // skip ']'
	arg := int(arg32)
	arg += s.firstArg - 1 // We want to zero-index the actual arguments.

  // CHECK-SAME: %arg30: tensor<!tf_type.resource<tensor<512xf32>>>
  // CHECK-SAME: %arg31: tensor<!tf_type.resource<tensor<640xf32>>>
  // CHECK-SAME: %arg32: tensor<!tf_type.resource<tensor<640xf32>>>
  // CHECK-SAME: %arg33: tensor<!tf_type.resource<tensor<640xf32>>>
  // CHECK-SAME: %arg34: tensor<!tf_type.resource<tensor<640xf32>>>
  // CHECK-SAME: %arg35: tensor<!tf_type.resource<tensor<4096xf32>>>)

  %0:2 = "tfl.bidirectional_sequence_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %arg18, %arg19, %arg20, %arg21, %arg22, %arg23, %arg24, %arg25, %arg26, %arg27, %arg28, %arg29, %arg30, %arg31, %arg32, %arg33, %arg34, %arg35, %arg36, %arg37, %arg38, %arg39, %arg40, %arg41, %arg42, %arg43, %arg44, %arg45, %arg46, %arg47) {cell_clip = 1.000000e+00 : f32, fused_activation_function...

  // CHECK: "tfl.unidirectional_sequence_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %arg18, %arg19, %arg20, %arg21, %arg22, %arg23) <{fused_activation_function = "NONE", time_major = false}> : (tensor<600x10x20xf32>, tensor<?x?xf32>,...

  // CHECK: "tfl.unidirectional_sequence_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %arg18, %arg19, %arg20, %arg21, %arg22, %arg23) <{asymmetric_quantize_inputs = false, cell_clip = 1.000000e+01 : f32, diagonal_recurrent_tensors...

    %assign_control_1 = tf_executor.island wraps "tf.AssignVariableOp"(%arg1, %arg3) : (tensor<!tf_type.resource<tensor<f32>>>, tensor<f32>) -> ()
    %add, %add_control = tf_executor.island wraps "tf.Add"(%arg2, %arg3) : (tensor<f32>, tensor<f32>) -> tensor<f32>

  %0 = "vhlo.dynamic_update_slice_v1"(%arg0, %arg1, %arg2, %arg3) : (tensor<4x4xi64>, tensor<2x3xi64>, tensor<i64>, tensor<i64>) -> tensor<4x4xi64>
  return %0 : tensor<4x4xi64>
}

//CHECK:func.func private @dynamic_update_slice(%arg0: tensor<4x4xi64>, %arg1: tensor<2x3xi64>, %arg2: tensor<i64>, %arg3: tensor<i64>) -> tensor<4x4xi64> {

  ^bb0(%arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<i32>, %arg4: tensor<!tf_type.resource>, %arg5: tensor<f32>):
    %9 = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
    %10 = "tf.Less"(%arg3, %9) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i1>
    "tfl.yield"(%10) : (tensor<i1>) -> ()
  },  {

// StableHLO functions.

// CHECK-LABEL: module
module {
  // CHECK-LABEL: func @main
  // CHECK-SAME: %[[ARG_0:.*]]: tensor<10xf32>, %[[ARG_1:.*]]: tensor<10xf32>, %[[ARG_2:.*]]: tensor<6xi32>
  func.func @main(
      %arg0: tensor<10xf32>, %arg1: tensor<10xf32>, %arg2: tensor<6xi32>
    ) -> (tensor<10xf32>, tensor<6xi32>) {
    // CHECK: %[[CAST_0:.*]] = "tf.Cast"(%[[ARG_0]]) <{Truncate = false}> : (tensor<10xf32>) -> tensor<10xbf16>

    reducer(%arg1: tensor<i32>, %arg3: tensor<i32>) (%arg2: tensor<i32>, %arg4: tensor<i32>)  {
    %6 = mhlo.compare  GE, %arg1, %arg3 : (tensor<i32>, tensor<i32>) -> tensor<i1>
    %7 = mhlo.select %6, %arg1, %arg3 : tensor<i1>, tensor<i32>
    %8 = mhlo.compare  EQ, %arg1, %arg3 : (tensor<i32>, tensor<i32>) -> tensor<i1>
    %9 = mhlo.minimum %arg2, %arg4 : tensor<i32>
    %10 = mhlo.select %6, %arg2, %arg4 : tensor<i1>, tensor<i32>