#define NULL ((void *)0)
typedef unsigned long size_t; // Customize by platform.
typedef long intptr_t;
typedef unsigned long uintptr_t;
typedef long scalar_t__; // Either arithmetic or pointer type.
/* By default, we understand bool (as a convenience). */
typedef int bool;
#define false 0
#define true 1

/* Forward declarations */

/* Type definitions */
struct recurrent_neural_network {
  int dummy;
};
struct output_files {
  int dummy;
};
struct general_parameters {
  int dummy;
};

/* Variables and functions */
int /*<<< orphan*/
print_closed_loop_data_with_epoch(long, struct general_parameters const *,
                                  struct recurrent_neural_network *,
                                  struct output_files *);
int /*<<< orphan*/
print_open_loop_data_with_epoch(long, struct general_parameters const *,
                                struct recurrent_neural_network *,
                                struct output_files *);
int /*<<< orphan*/
print_parameters_with_epoch(long, struct general_parameters const *,
                            struct recurrent_neural_network *,
                            struct output_files *);
void print_training_main_loop(long epoch, const struct general_parameters *gp,
                              struct recurrent_neural_network *rnn,
                              struct output_files *fp_list) {
  print_parameters_with_epoch(epoch, gp, rnn, fp_list);
  print_open_loop_data_with_epoch(epoch, gp, rnn, fp_list);
  print_closed_loop_data_with_epoch(epoch, gp, rnn, fp_list);
}


x86 assembly (clang, -O0):
<print_training_main_loop>:
push   %rbp
mov    %rsp,%rbp
sub    $0x20,%rsp
mov    %rdi,-0x8(%rbp)
mov    %rsi,-0x10(%rbp)
mov    %rdx,-0x18(%rbp)
mov    %rcx,-0x20(%rbp)
mov    -0x8(%rbp),%rdi
mov    -0x10(%rbp),%rsi
mov    -0x18(%rbp),%rdx
mov    -0x20(%rbp),%rcx
call   1040 <print_parameters_with_epoch@plt>
mov    -0x8(%rbp),%rdi
mov    -0x10(%rbp),%rsi
mov    -0x18(%rbp),%rdx
mov    -0x20(%rbp),%rcx
call   1030 <print_open_loop_data_with_epoch@plt>
mov    -0x8(%rbp),%rdi
mov    -0x10(%rbp),%rsi
mov    -0x18(%rbp),%rdx
mov    -0x20(%rbp),%rcx
call   1050 <print_closed_loop_data_with_epoch@plt>
add    $0x20,%rsp
pop    %rbp
ret

x86 assembly (clang, -O2):
<print_training_main_loop>:
push   %r15
push   %r14
push   %r12
push   %rbx
push   %rax
mov    %rcx,%r14
mov    %rdx,%r15
mov    %rsi,%r12
mov    %rdi,%rbx
call   1040 <print_parameters_with_epoch@plt>
mov    %rbx,%rdi
mov    %r12,%rsi
mov    %r15,%rdx
mov    %r14,%rcx
call   1030 <print_open_loop_data_with_epoch@plt>
mov    %rbx,%rdi
mov    %r12,%rsi
mov    %r15,%rdx
mov    %r14,%rcx
add    $0x8,%rsp
pop    %rbx
pop    %r12
pop    %r14
pop    %r15
jmp    1050 <print_closed_loop_data_with_epoch@plt>

LLVM IR (-O0):
%struct.general_parameters = type { i32 }
%struct.recurrent_neural_network = type { i32 }
%struct.output_files = type { i32 }
define void @print_training_main_loop(i64 %0, %struct.general_parameters* %1, %struct.recurrent_neural_network* %2, %struct.output_files* %3) {
%5 = alloca i64
%6 = alloca %struct.general_parameters*
%7 = alloca %struct.recurrent_neural_network*
%8 = alloca %struct.output_files*
store i64 %0, i64* %5
store %struct.general_parameters* %1, %struct.general_parameters** %6
store %struct.recurrent_neural_network* %2, %struct.recurrent_neural_network** %7
store %struct.output_files* %3, %struct.output_files** %8
%9 = load i64, i64* %5
%10 = load %struct.general_parameters*, %struct.general_parameters** %6
%11 = load %struct.recurrent_neural_network*, %struct.recurrent_neural_network** %7
%12 = load %struct.output_files*, %struct.output_files** %8
%13 = call i32 @print_parameters_with_epoch(i64 %9, %struct.general_parameters* %10, %struct.recurrent_neural_network* %11, %struct.output_files* %12)
%14 = load i64, i64* %5
%15 = load %struct.general_parameters*, %struct.general_parameters** %6
%16 = load %struct.recurrent_neural_network*, %struct.recurrent_neural_network** %7
%17 = load %struct.output_files*, %struct.output_files** %8
%18 = call i32 @print_open_loop_data_with_epoch(i64 %14, %struct.general_parameters* %15, %struct.recurrent_neural_network* %16, %struct.output_files* %17)
%19 = load i64, i64* %5
%20 = load %struct.general_parameters*, %struct.general_parameters** %6
%21 = load %struct.recurrent_neural_network*, %struct.recurrent_neural_network** %7
%22 = load %struct.output_files*, %struct.output_files** %8
%23 = call i32 @print_closed_loop_data_with_epoch(i64 %19, %struct.general_parameters* %20, %struct.recurrent_neural_network* %21, %struct.output_files* %22)
ret void
}

LLVM IR (-O2):
%struct.general_parameters = type { i32 }
%struct.recurrent_neural_network = type { i32 }
%struct.output_files = type { i32 }
define void @print_training_main_loop(i64 %0, %struct.general_parameters* %1, %struct.recurrent_neural_network* %2, %struct.output_files* %3) {
%5 = tail call i32 @print_parameters_with_epoch(i64 %0, %struct.general_parameters* %1, %struct.recurrent_neural_network* %2, %struct.output_files* %3)
%6 = tail call i32 @print_open_loop_data_with_epoch(i64 %0, %struct.general_parameters* %1, %struct.recurrent_neural_network* %2, %struct.output_files* %3)
%7 = tail call i32 @print_closed_loop_data_with_epoch(i64 %0, %struct.general_parameters* %1, %struct.recurrent_neural_network* %2, %struct.output_files* %3)
ret void
}