Python termcolor.cprint方法代碼示例

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def adjust_learning_rate(optimizer, drop_ratio, epoch, lr_drop_epoch_list,
                         WARMUP_EPOCHS, WARMUP_LRS):
    if args.warmup and epoch < WARMUP_EPOCHS:
        # achieve the warmup lr
        lrs = np.linspace(WARMUP_LRS[0], WARMUP_LRS[1], num=WARMUP_EPOCHS)
        cprint('=> warmup lrs {}'.format(lrs), 'green')
        for param_group in optimizer.param_groups:
            param_group['lr'] = lrs[epoch]
        current_lr = lrs[epoch]
    else:
        decay = drop_ratio if epoch in lr_drop_epoch_list else 1.0
        for param_group in optimizer.param_groups:
            param_group['lr'] = args.lr * decay
        args.lr *= decay
        current_lr = args.lr
    return current_lr 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def setup_tensorboard(flags):
  """Creates summary writers, and setups default tensorboard paths."""
  if not flags.tensorboard:
    return

  # --- Do not allow experiment with same name
  assert (not tf.io.gfile.exists(flags.logdir) or
          not tf.io.gfile.listdir(flags.logdir)), \
    "CRITICAL: folder {} already exists".format(flags.logdir)

  # --- Log where summary can be found
  print("View results with: ")
  termcolor.cprint("  tensorboard --logdir {}".format(flags.logdir), "red")
  writer = tf.summary.create_file_writer(flags.logdir, flush_millis=10000)
  writer.set_as_default()

  # --- Log dir name tweak for "hypertune"
  log_dir = ""
  trial_id = int(os.environ.get("CLOUD_ML_TRIAL_ID", 0))
  if trial_id != 0:
    if log_dir.endswith(os.sep):
      log_dir = log_dir[:-1]  # removes trailing "/"
    log_dir += "_trial{0:03d}/".format(trial_id) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def run(self):
        #resetEngines()
        if not self.check():
            return
        self.set_arch()
        #enableSymbolicEngine(True)
        self.optimization()
        self.load_binary()
        self.set_regs()
        self.load_stack()

        # make Symbolic

        if self.symbolized_argv:
            self.symbolize_argv()
        self.symbolize_memory()

        # symbolic execution

        if not self.emulate(self.registers[Arch().pc_reg]):
            print(cprint("No answer is found!!!", 'red'))

    # Commands 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def _observe(self):
        #cprint('Observe called!', 'yellow')

        if self.config['USE_XVFB']:
            offset_x = 0
            offset_y = 0
        else:
            offset_x = self.config['OFFSET_X']
            offset_y = self.config['OFFSET_Y']

        image_array = \
            np.array(self.mss_grabber.grab({"top": offset_y,
                                            "left": offset_x,
                                            "width": SCR_W,
                                            "height": SCR_H}),
                     dtype=np.uint8)

        # drop the alpha channel and flip red and blue channels (BGRA -> RGB)
        self.pixel_array = np.flip(image_array[:, :, :3], 2)

        return self.pixel_array 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def handle_keyboard_interrupt(flags):
  """Informs user how to delete stale summaries."""
  print("Keyboard interrupt by user")
  if flags.logdir.startswith("gs://"):
    bucketpath = flags.logdir[5:]
    print("Delete these summaries with: ")
    termcolor.cprint("  gsutil rm -rf {}".format(flags.logdir), "red")
    baseurl = "  https://pantheon.google.com/storage/browser/{}"
    print("Or by visiting: ")
    termcolor.cprint(baseurl.format(bucketpath), "red")
  else:
    print("Delete these summaries with: ")
    termcolor.cprint("  rm -rf {}".format(flags.logdir), "red") 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def log_print(text, color=None, on_color=None, attrs=None):
    if cprint is not None:
        cprint(text, color=color, on_color=on_color, attrs=attrs)
    else:
        print(text) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def cprint(text, color):
        print(text) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def fail(text):
    cprint(text, 'red') 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def win(text):
    cprint(text, 'green') 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def banner(text):
    cprint(Figlet().renderText(text), "blue") 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def c(msg, colour):
        try:
            from termcolor import colored, cprint
            p = lambda x: cprint(x, '%s' % colour)
            return p(msg)
        except:
            print (msg) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def load_from_id(bsuite_id: str) -> base.Environment:
  """Returns a bsuite environment given a bsuite_id."""
  kwargs = sweep.SETTINGS[bsuite_id]
  experiment_name, _ = unpack_bsuite_id(bsuite_id)
  env = load(experiment_name, kwargs)
  termcolor.cprint(
      f'Loaded bsuite_id: {bsuite_id}.', color='white', attrs=['bold'])
  return env 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def load_and_record_to_sqlite(bsuite_id: str,
                              db_path: str) -> dm_env.Environment:
  """Returns a bsuite environment that saves results to an SQLite database.

  The returned environment will automatically save the results required for
  the analysis notebook when stepping through the environment.

  To load the results, specify the file path in the provided notebook, or to
  manually inspect the results use:

  ```python
  from bsuite.utils import sqlite_load

  results_df, sweep_vars = sqlite_load.load_bsuite('/path/to/database.db')
  ```

  Args:
    bsuite_id: The bsuite id identifying the environment to return. For example,
      "catch/0" or "deep_sea/3".
    db_path: Path to the database file for this set of results. The file will be
      created if it does not already exist. When generating results using
      multiple different processes, specify the *same* db_path for every
      bsuite_id.

  Returns:
    A bsuite environment determined by the bsuite_id.
  """
  raw_env = load_from_id(bsuite_id)
  experiment_name, setting_index = unpack_bsuite_id(bsuite_id)
  termcolor.cprint(
      f'Logging results to SQLite database in {db_path}.',
      color='yellow',
      attrs=['bold'])
  return sqlite_logging.wrap_environment(
      env=raw_env,
      db_path=db_path,
      experiment_name=experiment_name,
      setting_index=setting_index,
  ) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def load_and_record_to_csv(bsuite_id: str,
                           results_dir: str,
                           overwrite: bool = False) -> dm_env.Environment:
  """Returns a bsuite environment that saves results to CSV.

  To load the results, specify the file path in the provided notebook, or to
  manually inspect the results use:

  ```python
  from bsuite.utils import csv_load

  results_df, sweep_vars = csv_load.load_bsuite(results_dir)
  ```

  Args:
    bsuite_id: The bsuite id identifying the environment to return. For example,
      "catch/0" or "deep_sea/3".
    results_dir: Path to the directory to store the resultant CSV files. Note
      that this logger will generate a separate CSV file for each bsuite_id.
    overwrite: Whether to overwrite existing CSV files if found.

  Returns:
    A bsuite environment determined by the bsuite_id.
  """
  raw_env = load_from_id(bsuite_id)
  termcolor.cprint(
      f'Logging results to CSV file for each bsuite_id in {results_dir}.',
      color='yellow',
      attrs=['bold'])
  return csv_logging.wrap_environment(
      env=raw_env,
      bsuite_id=bsuite_id,
      results_dir=results_dir,
      overwrite=overwrite,
  ) 

# 需要導入模塊: import termcolor [as 別名]
# 或者: from termcolor import cprint [as 別名]
def load_and_record_to_terminal(bsuite_id: str) -> dm_env.Environment:
  """Returns a bsuite environment that logs to terminal."""
  raw_env = load_from_id(bsuite_id)
  termcolor.cprint(
      'Logging results to terminal.', color='yellow', attrs=['bold'])
  return terminal_logging.wrap_environment(raw_env)