Python logger.error方法代码示例

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def capture_frame(self):
        """Render the given `env` and add the resulting frame to the video."""
        if not self.functional: return
        logger.debug('Capturing video frame: path=%s', self.path)

        render_mode = 'ansi' if self.ansi_mode else 'rgb_array'
        frame = self.env.render(mode=render_mode)

        if frame is None:
            if self._async:
                return
            else:
                # Indicates a bug in the environment: don't want to raise
                # an error here.
                logger.warn('Env returned None on render(). Disabling further rendering for video recorder by marking as disabled: path=%s metadata_path=%s', self.path, self.metadata_path)
                self.broken = True
        else:
            self.last_frame = frame
            if self.ansi_mode:
                self._encode_ansi_frame(frame)
            else:
                self._encode_image_frame(frame) 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def __init__(self, output_path, frame_shape, frames_per_sec):
        self.proc = None
        self.output_path = output_path
        # Frame shape should be lines-first, so w and h are swapped
        h, w, pixfmt = frame_shape
        if pixfmt != 3 and pixfmt != 4:
            raise error.InvalidFrame("Your frame has shape {}, but we require (w,h,3) or (w,h,4), i.e. RGB values for a w-by-h image, with an optional alpha channl.".format(frame_shape))
        self.wh = (w,h)
        self.includes_alpha = (pixfmt == 4)
        self.frame_shape = frame_shape
        self.frames_per_sec = frames_per_sec

        if distutils.spawn.find_executable('avconv') is not None:
            self.backend = 'avconv'
        elif distutils.spawn.find_executable('ffmpeg') is not None:
            self.backend = 'ffmpeg'
        else:
            raise error.DependencyNotInstalled("""Found neither the ffmpeg nor avconv executables. On OS X, you can install ffmpeg via `brew install ffmpeg`. On most Ubuntu variants, `sudo apt-get install ffmpeg` should do it. On Ubuntu 14.04, however, you'll need to install avconv with `sudo apt-get install libav-tools`.""")

        self.start() 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def __init__(self, final_path, frame_shape, frames_per_sec):
        self.proc = None
        self.final_path = final_path
        _, self.output_path = tempfile.mkstemp(suffix='.mp4')
        # Frame shape should be lines-first, so w and h are swapped
        h, w, pixfmt = frame_shape
        if pixfmt != 3 and pixfmt != 4:
            raise error.InvalidFrame("Your frame has shape {}, but we require (w,h,3) or (w,h,4), i.e. RGB values for a w-by-h image, with an optional alpha channl.".format(frame_shape))
        self.wh = (w,h)
        self.includes_alpha = (pixfmt == 4)
        self.frame_shape = frame_shape
        self.frames_per_sec = frames_per_sec

        if distutils.spawn.find_executable('avconv') is not None:
            self.backend = 'avconv'
        elif distutils.spawn.find_executable('ffmpeg') is not None:
            self.backend = 'ffmpeg'
        else:
            raise error.DependencyNotInstalled("""Found neither the ffmpeg nor avconv executables. On OS X, you can install ffmpeg via `brew install ffmpeg`. On most Ubuntu variants, `sudo apt-get install ffmpeg` should do it. On Ubuntu 14.04, however, you'll need to install avconv with `sudo apt-get install libav-tools`.""")

        self.start() 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def _raise_if_errors(self, successes):
        if all(successes):
            return

        num_errors = self.num_envs - sum(successes)
        assert num_errors > 0
        for _ in range(num_errors):
            index, exctype, value = self.error_queue.get()
            logger.error('Received the following error from Worker-{0}: '
                '{1}: {2}'.format(index, exctype.__name__, value))
            logger.error('Shutting down Worker-{0}.'.format(index))
            self.parent_pipes[index].close()
            self.parent_pipes[index] = None

        logger.error('Raising the last exception back to the main process.')
        raise exctype(value) 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def __init__(self, output_path, frame_shape, frames_per_sec):
        self.proc = None
        self.output_path = output_path
        # Frame shape should be lines-first, so w and h are swapped
        h, w, pixfmt = frame_shape
        if pixfmt != 3 and pixfmt != 4:
            raise error.InvalidFrame("Your frame has shape {}, but we require (w,h,3) or (w,h,4), i.e., RGB values for a w-by-h image, with an optional alpha channel.".format(frame_shape))
        self.wh = (w,h)
        self.includes_alpha = (pixfmt == 4)
        self.frame_shape = frame_shape
        self.frames_per_sec = frames_per_sec

        if distutils.spawn.find_executable('avconv') is not None:
            self.backend = 'avconv'
        elif distutils.spawn.find_executable('ffmpeg') is not None:
            self.backend = 'ffmpeg'
        else:
            raise error.DependencyNotInstalled("""Found neither the ffmpeg nor avconv executables. On OS X, you can install ffmpeg via `brew install ffmpeg`. On most Ubuntu variants, `sudo apt-get install ffmpeg` should do it. On Ubuntu 14.04, however, you'll need to install avconv with `sudo apt-get install libav-tools`.""")

        self.start() 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def close(self):
        super(Monitor, self)._close()

        # _monitor will not be set if super(Monitor, self).__init__ raises, this check prevents a confusing error message
        if getattr(self, '_monitor', None):
            self.close() 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def _set_mode(self, mode):
        if mode == 'evaluation':
            type = 'e'
        elif mode == 'training':
            type = 't'
        else:
            raise error.Error('Invalid mode {}: must be "training" or "evaluation"', mode)
        self.stats_recorder.type = type 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def load_results(training_dir):
    if not os.path.exists(training_dir):
        logger.error('Training directory %s not found', training_dir)
        return

    manifests = detect_training_manifests(training_dir)
    if not manifests:
        logger.error('No manifests found in training directory %s', training_dir)
        return

    logger.debug('Uploading data from manifest %s', ', '.join(manifests))

    # Load up stats + video files
    stats_files = []
    videos = []
    env_infos = []

    for manifest in manifests:
        with open(manifest) as f:
            contents = json.load(f)
            # Make these paths absolute again
            stats_files.append(os.path.join(training_dir, contents['stats']))
            videos += [(os.path.join(training_dir, v), os.path.join(training_dir, m))
                       for v, m in contents['videos']]
            env_infos.append(contents['env_info'])

    env_info = collapse_env_infos(env_infos, training_dir)
    data_sources, initial_reset_timestamps, timestamps, episode_lengths, episode_rewards, episode_types, initial_reset_timestamp = merge_stats_files(stats_files)

    return {
        'manifests': manifests,
        'env_info': env_info,
        'data_sources': data_sources,
        'timestamps': timestamps,
        'episode_lengths': episode_lengths,
        'episode_rewards': episode_rewards,
        'episode_types': episode_types,
        'initial_reset_timestamps': initial_reset_timestamps,
        'initial_reset_timestamp': initial_reset_timestamp,
        'videos': videos,
    } 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def merge_stats_files(stats_files):
    timestamps = []
    episode_lengths = []
    episode_rewards = []
    episode_types = []
    initial_reset_timestamps = []
    data_sources = []

    for i, path in enumerate(stats_files):
        with open(path) as f:
            content = json.load(f)
            if len(content['timestamps'])==0: continue # so empty file doesn't mess up results, due to null initial_reset_timestamp
            data_sources += [i] * len(content['timestamps'])
            timestamps += content['timestamps']
            episode_lengths += content['episode_lengths']
            episode_rewards += content['episode_rewards']
            # Recent addition
            episode_types += content.get('episode_types', [])
            # Keep track of where each episode came from.
            initial_reset_timestamps.append(content['initial_reset_timestamp'])

    idxs = np.argsort(timestamps)
    timestamps = np.array(timestamps)[idxs].tolist()
    episode_lengths = np.array(episode_lengths)[idxs].tolist()
    episode_rewards = np.array(episode_rewards)[idxs].tolist()
    data_sources = np.array(data_sources)[idxs].tolist()

    if episode_types:
        episode_types = np.array(episode_types)[idxs].tolist()
    else:
        episode_types = None

    if len(initial_reset_timestamps) > 0:
        initial_reset_timestamp = min(initial_reset_timestamps)
    else:
        initial_reset_timestamp = 0

    return data_sources, initial_reset_timestamps, timestamps, episode_lengths, episode_rewards, episode_types, initial_reset_timestamp

# TODO training_dir isn't used except for error messages, clean up the layering 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def _encode_image_frame(self, frame):
        if not self.encoder:
            self.encoder = ImageEncoder(self.path, frame.shape, self.frames_per_sec)
            self.metadata['encoder_version'] = self.encoder.version_info

        try:
            self.encoder.capture_frame(frame)
        except error.InvalidFrame as e:
            logger.warn('Tried to pass invalid video frame, marking as broken: %s', e)
            self.broken = True
        else:
            self.empty = False 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def close(self):
        self.proc.stdin.close()
        ret = self.proc.wait()
        if ret != 0:
            logger.error("VideoRecorder encoder exited with status {}".format(ret)) 

# 需要导入模块: from gym import logger [as 别名]
# 或者: from gym.logger import error [as 别名]
def close(self):
        self.proc.stdin.close()
        ret = self.proc.wait()
        if ret != 0:
            logger.error("VideoRecorder encoder exited with status {}".format(ret))
        gfile.Copy(self.output_path, self.final_path, overwrite=True)
        os.remove(self.output_path)