tfrt.return %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,

            // %arg30 is used in the cond function, %arg31 has other uses (%id0), and
            // %arg32 is not a pass-through.
            "tf_device.launch"() ({
              "tf.TPUExecuteAndUpdateVariables"(%arg30, %arg31, %arg32, %compile#1)
                    {device_var_reads_indices = [0, 1, 2], device_var_updates_indices = [0, 1, 2]}

			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...

  -> (tensor<i64>) attributes {tf._tf_data_function = true, tf.signature.is_stateful} {
    %0 = "tf.JustPretend"(%arg1, %arg2, %arg3) : (tensor<32xf32>, tensor<!tf_type.resource<tensor<64xf32>>>, tensor<!tf_type.resource<tensor<128xf32>>>) -> (tensor<i64>)

    %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>

  %arg4: tensor<!tf_type.string>) {
  // CHECK: tf_device.replicate
  // CHECK-SAME: [%[[ARG_0]], %[[ARG_1]]] as %[[RI_0:[a-z0-9]+]]: tensor<*x!tf_type.resource<tensor<32xf32>>>
  // CHECK-SAME: [%[[ARG_2]], %[[ARG_3]]] as %[[RI_1:[a-z0-9]+]]: tensor<*x!tf_type.resource<tensor<64xf32>>>
  tf_device.replicate([%arg0, %arg1] as %ri0: tensor<*x!tf_type.resource<tensor<32xf32>>>,