# Path: compiler_opt/rl/compilation_runner.py
# class RewardStat:
# class DataClassJSONEncoder(json.JSONEncoder):
# class ProcessKilledError(Exception):
# class ProcessCancellationToken:
# class WorkerCancellationManager:
# class CompilationRunner:
#   def default(self, o):
# def _postprocessing_sequence_example(
#     sequence_example: tf.train.SequenceExample, moving_average_reward: float,
#     policy_reward: float) -> tf.train.SequenceExample:
# def get_command_line_for_bundle(cmd_file: str,
#                                 ir_file: str,
#                                 thinlto: Optional[str] = None) -> List[str]:
#   def __init__(self):
#   def __init__(self):
#   def signal(self):
#   def wait(self):
# def kill_process_ignore_exceptions(p: subprocess.Popen):
#   def __init__(self):
#   def register_process(self, p: subprocess.Popen):
#   def signal(self):
#   def unregister_process(self, p: subprocess.Popen):
# def start_cancellable_process(
#     cmdline: List[str],
#     timeout: float,
#     cancellation_manager: Optional[WorkerCancellationManager],
#     want_output: bool = False) -> Optional[bytes]:
#   def init_pool():
#   def _get_pool():
#   def __init__(self,
#                clang_path: str,
#                llvm_size_path: str,
#                launcher_path: Optional[str] = None,
#                moving_average_decay_rate: float = 1):
#   def _get_cancellation_manager(
#       self, cancellation_token: Optional[ProcessCancellationToken]
#   ) -> Optional[WorkerCancellationManager]:
#     def signaler():
#   def collect_data(
#       self,
#       file_paths: Tuple[str, ...],
#       tf_policy_path: str,
#       reward_stat: Optional[Dict[str, RewardStat]],
#       cancellation_token: Optional[ProcessCancellationToken] = None
#   ) -> Tuple[List[str], Dict[str, RewardStat], List[float]]:
#   def _compile_fn(
#       self, file_paths: Tuple[str, ...], tf_policy_path: str, reward_only: bool,
#       cancellation_manager: Optional[WorkerCancellationManager]
#   ) -> Dict[str, Tuple[tf.train.SequenceExample, float]]:
#   _POOL: concurrent.futures.ThreadPoolExecutor = None
# 
# Path: compiler_opt/rl/constant.py
# BASE_DIR = 'compiler_opt/rl'
# BASE_MODULE_DIR = 'compiler_opt.rl'
# DELTA = 0.01
#   BEHAVIORAL_CLONE = 0
#   DQN = 1
#   PPO = 2
# class AgentName(enum.Enum):


import os
import string
import subprocess
import time
import tensorflow as tf
from unittest import mock
from absl import flags
from google.protobuf import text_format
from compiler_opt.rl import compilation_runner
from compiler_opt.rl import constant
        [tf.train.SequenceExample.FromString(x) for x in example])
    self.assertCountEqual(
        {
            'default':
                compilation_runner.RewardStat(
                    default_reward=_DEFAULT_REWARD,
                    moving_average_reward=7 * _MOVING_AVERAGE_DECAY_RATE +
                    _POLICY_REWARD * (1 - _MOVING_AVERAGE_DECAY_RATE))
        }, reward_stat)
    self.assertAllClose([0.199800], rewards)

  @mock.patch(constant.BASE_MODULE_DIR +
              '.compilation_runner.CompilationRunner._compile_fn')
  def test_exception_handling(self, mock_compile_fn):
    mock_compile_fn.side_effect = subprocess.CalledProcessError(
        returncode=1, cmd='error')
    runner = compilation_runner.CompilationRunner('', '', '',
                                                  _MOVING_AVERAGE_DECAY_RATE)

    with self.assertRaisesRegex(subprocess.CalledProcessError, 'error'):
      _, _, _ = runner.collect_data(
          file_paths=('bc', 'cmd'),
          tf_policy_path='policy_path',
          reward_stat=None)
    self.assertEqual(1, mock_compile_fn.call_count)

  def test_command_line_file(self):
    data = ['-cc1', '-foo', '-bar=baz']
    argfile = self.create_tempfile(content='\0'.join(data))
    self.assertEqual(

# Path: compiler_opt/rl/compilation_runner.py
# class RewardStat:
# class DataClassJSONEncoder(json.JSONEncoder):
# class ProcessKilledError(Exception):
# class ProcessCancellationToken:
# class WorkerCancellationManager:
# class CompilationRunner:
#   def default(self, o):
# def _postprocessing_sequence_example(
#     sequence_example: tf.train.SequenceExample, moving_average_reward: float,
#     policy_reward: float) -> tf.train.SequenceExample:
# def get_command_line_for_bundle(cmd_file: str,
#                                 ir_file: str,
#                                 thinlto: Optional[str] = None) -> List[str]:
#   def __init__(self):
#   def __init__(self):
#   def signal(self):
#   def wait(self):
# def kill_process_ignore_exceptions(p: subprocess.Popen):
#   def __init__(self):
#   def register_process(self, p: subprocess.Popen):
#   def signal(self):
#   def unregister_process(self, p: subprocess.Popen):
# def start_cancellable_process(
#     cmdline: List[str],
#     timeout: float,
#     cancellation_manager: Optional[WorkerCancellationManager],
#     want_output: bool = False) -> Optional[bytes]:
#   def init_pool():
#   def _get_pool():
#   def __init__(self,
#                clang_path: str,
#                llvm_size_path: str,
#                launcher_path: Optional[str] = None,
#                moving_average_decay_rate: float = 1):
#   def _get_cancellation_manager(
#       self, cancellation_token: Optional[ProcessCancellationToken]
#   ) -> Optional[WorkerCancellationManager]:
#     def signaler():
#   def collect_data(
#       self,
#       file_paths: Tuple[str, ...],
#       tf_policy_path: str,
#       reward_stat: Optional[Dict[str, RewardStat]],
#       cancellation_token: Optional[ProcessCancellationToken] = None
#   ) -> Tuple[List[str], Dict[str, RewardStat], List[float]]:
#   def _compile_fn(
#       self, file_paths: Tuple[str, ...], tf_policy_path: str, reward_only: bool,
#       cancellation_manager: Optional[WorkerCancellationManager]
#   ) -> Dict[str, Tuple[tf.train.SequenceExample, float]]:
#   _POOL: concurrent.futures.ThreadPoolExecutor = None
# 
# Path: compiler_opt/rl/constant.py
# BASE_DIR = 'compiler_opt/rl'
# BASE_MODULE_DIR = 'compiler_opt.rl'
# DELTA = 0.01
#   BEHAVIORAL_CLONE = 0
#   DQN = 1
#   PPO = 2
# class AgentName(enum.Enum):


# Path: compiler_opt/rl/compilation_runner_test.py
import os
import string
import subprocess
import time
import tensorflow as tf
from unittest import mock
from absl import flags
from google.protobuf import text_format
from compiler_opt.rl import compilation_runner
from compiler_opt.rl import constant

        [tf.train.SequenceExample.FromString(x) for x in example])
    self.assertCountEqual(
        {
            'default':
                compilation_runner.RewardStat(
                    default_reward=_DEFAULT_REWARD,
                    moving_average_reward=7 * _MOVING_AVERAGE_DECAY_RATE +
                    _POLICY_REWARD * (1 - _MOVING_AVERAGE_DECAY_RATE))
        }, reward_stat)
    self.assertAllClose([0.199800], rewards)

  @mock.patch(constant.BASE_MODULE_DIR +
              '.compilation_runner.CompilationRunner._compile_fn')
  def test_exception_handling(self, mock_compile_fn):
    mock_compile_fn.side_effect = subprocess.CalledProcessError(
        returncode=1, cmd='error')
    runner = compilation_runner.CompilationRunner('', '', '',
                                                  _MOVING_AVERAGE_DECAY_RATE)

    with self.assertRaisesRegex(subprocess.CalledProcessError, 'error'):
      _, _, _ = runner.collect_data(
          file_paths=('bc', 'cmd'),
          tf_policy_path='policy_path',
          reward_stat=None)
    self.assertEqual(1, mock_compile_fn.call_count)

  def test_command_line_file(self):
    data = ['-cc1', '-foo', '-bar=baz']
    argfile = self.create_tempfile(content='\0'.join(data))
    self.assertEqual(

        compilation_runner.get_command_line_for_bundle(argfile.full_path,