Python gfile.ListDirectory方法代碼示例

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def generators_from_logdir(logdir):
  """Returns a list of event generators for subdirectories with event files.

  The number of generators returned should equal the number of directories
  within logdir that contain event files. If only logdir contains event files,
  returns a list of length one.

  Args:
    logdir: A log directory that contains event files.

  Returns:
    List of event generators for each subdirectory with event files.
  """
  subdirs = event_multiplexer.GetLogdirSubdirectories(logdir)
  generators = [itertools.chain(*[
      generator_from_event_file(os.path.join(subdir, f))
      for f in gfile.ListDirectory(subdir)
      if event_accumulator.IsTensorFlowEventsFile(os.path.join(subdir, f))
  ]) for subdir in subdirs]
  return generators 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def ListPlugins(logdir):
  """List all the plugins that have registered assets in logdir.

  If the plugins_dir does not exist, it returns an empty list. This maintains
  compatibility with old directories that have no plugins written.

  Args:
    logdir: A directory that was created by a TensorFlow events writer.

  Returns:
    a list of plugin names, as strings
  """
  plugins_dir = os.path.join(logdir, _PLUGINS_DIR)
  if not gfile.IsDirectory(plugins_dir):
    return []
  entries = gfile.ListDirectory(plugins_dir)
  return [x for x in entries if _IsDirectory(plugins_dir, x)] 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def ListDirectoryAbsolute(directory):
  """Yields all files in the given directory. The paths are absolute."""
  return (os.path.join(directory, path)
          for path in gfile.ListDirectory(directory)) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def get_paths(base_dir, parser):
  """Gets a list of Paths in a given directory.

  Args:
    base_dir: directory.
    parser: a function which gets the raw Path and can augment it with
      information such as the export_version, or ignore the path by returning
      None.  An example parser may extract the export version from a path
      such as "/tmp/exports/100" an another may extract from a full file
      name such as "/tmp/checkpoint-99.out".

  Returns:
    A list of Paths contained in the base directory with the parsing function
    applied.
    By default the following fields are populated,
      - Path.path
    The parsing function is responsible for populating,
      - Path.export_version
  """
  raw_paths = gfile.ListDirectory(base_dir)
  paths = []
  for r in raw_paths:
    p = parser(Path(os.path.join(base_dir, r), None))
    if p:
      paths.append(p)
  return sorted(paths) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def __init__(self, sess, session_root, watch_fn=None, log_usage=True):
    """Constructor of DumpingDebugWrapperSession.

    Args:
      sess: The TensorFlow `Session` object being wrapped.
      session_root: (`str`) Path to the session root directory. Must be a
        directory that does not exist or an empty directory. If the directory
        does not exist, it will be created by the debugger core during debug
        [`Session.run()`](../../../g3doc/api_docs/python/client.md#session.run)
        calls.
        As the `run()` calls occur, subdirectories will be added to
        `session_root`. The subdirectories' names has the following pattern:
          run_<epoch_time_stamp>_<uuid>
        E.g., run_1480734393835964_ad4c953a85444900ae79fc1b652fb324
      watch_fn: (`Callable`) A Callable that can be used to define per-run
        debug ops and watched tensors. See the doc of
        `NonInteractiveDebugWrapperSession.__init__()` for details.
      log_usage: (`bool`) whether the usage of this class is to be logged.

    Raises:
       ValueError: If `session_root` is an existing and non-empty directory or
       if `session_root` is a file.
    """

    if log_usage:
      pass  # No logging for open-source.

    framework.NonInteractiveDebugWrapperSession.__init__(
        self, sess, watch_fn=watch_fn)

    if gfile.Exists(session_root):
      if not gfile.IsDirectory(session_root):
        raise ValueError(
            "session_root path points to a file: %s" % session_root)
      elif gfile.ListDirectory(session_root):
        raise ValueError(
            "session_root path points to a non-empty directory: %s" %
            session_root)
    self._session_root = session_root 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def testGC(self):
    export_path = os.path.join(tf.test.get_temp_dir(), "gc")
    self.doBasicsOneExportPath(export_path, global_step=100)
    self.assertEquals(gfile.ListDirectory(export_path), ["00000100"])
    self.doBasicsOneExportPath(export_path, global_step=101)
    self.assertEquals(
        sorted(gfile.ListDirectory(export_path)), ["00000100", "00000101"])
    self.doBasicsOneExportPath(export_path, global_step=102)
    self.assertEquals(
        sorted(gfile.ListDirectory(export_path)), ["00000101", "00000102"]) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def _get_paths(base_dir, parser):
  """Gets a list of Paths in a given directory.

  Args:
    base_dir: directory.
    parser: a function which gets the raw Path and can augment it with
      information such as the export_version, or ignore the path by returning
      None.  An example parser may extract the export version from a path such
      as "/tmp/exports/100" an another may extract from a full file name such as
      "/tmp/checkpoint-99.out".

  Returns:
    A list of Paths contained in the base directory with the parsing function
    applied.
    By default the following fields are populated,
      - Path.path
    The parsing function is responsible for populating,
      - Path.export_version
  """
  # We are mocking this in the test, hence we should not use public API
  raw_paths = gfile.ListDirectory(base_dir)
  paths = []
  for r in raw_paths:
    # ListDirectory() return paths with "/" at the last if base_dir was GCS URL
    r = tf.compat.as_str_any(r)
    if r[-1] == '/':
      r = r[0:len(r) - 1]
    p = parser(Path(os.path.join(tf.compat.as_str_any(base_dir), r), None))
    if p:
      paths.append(p)
  return sorted(paths) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def testGcsDirWithSeparator(self):
    base_dir = "gs://bucket/foo"
    with tf.compat.v1.test.mock.patch.object(
        gfile, "ListDirectory") as mock_list_directory:
      # gfile.ListDirectory returns directory names with separator '/'
      mock_list_directory.return_value = ["0/", "1/"]
      self.assertEqual(
          gc._get_paths(base_dir, _create_parser(base_dir)), [
              gc.Path(os.path.join(base_dir, "0"), 0),
              gc.Path(os.path.join(base_dir, "1"), 1)
          ]) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def _get_paths(base_dir, parser):
  """Gets a list of Paths in a given directory.

  Args:
    base_dir: directory.
    parser: a function which gets the raw Path and can augment it with
      information such as the export_version, or ignore the path by returning
      None.  An example parser may extract the export version from a path
      such as "/tmp/exports/100" an another may extract from a full file
      name such as "/tmp/checkpoint-99.out".

  Returns:
    A list of Paths contained in the base directory with the parsing function
    applied.
    By default the following fields are populated,
      - Path.path
    The parsing function is responsible for populating,
      - Path.export_version
  """
  raw_paths = gfile.ListDirectory(base_dir)
  paths = []
  for r in raw_paths:
    p = parser(Path(os.path.join(compat.as_str_any(base_dir),
                                 compat.as_str_any(r)),
                    None))
    if p:
      paths.append(p)
  return sorted(paths) 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def __init__(self,
               sess,
               session_root,
               watch_fn=None,
               thread_name_filter=None,
               log_usage=True):
    """Constructor of DumpingDebugWrapperSession.

    Args:
      sess: The TensorFlow `Session` object being wrapped.
      session_root: (`str`) Path to the session root directory. Must be a
        directory that does not exist or an empty directory. If the directory
        does not exist, it will be created by the debugger core during debug
        @{tf.Session.run}
        calls.
        As the `run()` calls occur, subdirectories will be added to
        `session_root`. The subdirectories' names has the following pattern:
          run_<epoch_time_stamp>_<zero_based_run_counter>
        E.g., run_1480734393835964_ad4c953a85444900ae79fc1b652fb324
      watch_fn: (`Callable`) A Callable that can be used to define per-run
        debug ops and watched tensors. See the doc of
        `NonInteractiveDebugWrapperSession.__init__()` for details.
      thread_name_filter: Regular-expression white list for threads on which the
        wrapper session will be active. See doc of `BaseDebugWrapperSession` for
        more details.
      log_usage: (`bool`) whether the usage of this class is to be logged.

    Raises:
       ValueError: If `session_root` is an existing and non-empty directory or
       if `session_root` is a file.
    """

    if log_usage:
      pass  # No logging for open-source.

    framework.NonInteractiveDebugWrapperSession.__init__(
        self, sess, watch_fn=watch_fn, thread_name_filter=thread_name_filter)

    if gfile.Exists(session_root):
      if not gfile.IsDirectory(session_root):
        raise ValueError(
            "session_root path points to a file: %s" % session_root)
      elif gfile.ListDirectory(session_root):
        raise ValueError(
            "session_root path points to a non-empty directory: %s" %
            session_root)
    self._session_root = session_root

    self._run_counter = 0
    self._run_counter_lock = threading.Lock() 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def get_inspection_units(logdir='', event_file='', tag=''):
  """Returns a list of InspectionUnit objects given either logdir or event_file.

  If logdir is given, the number of InspectionUnits should equal the
  number of directories or subdirectories that contain event files.

  If event_file is given, the number of InspectionUnits should be 1.

  Args:
    logdir: A log directory that contains event files.
    event_file: Or, a particular event file path.
    tag: An optional tag name to query for.

  Returns:
    A list of InspectionUnit objects.
  """
  if logdir:
    subdirs = event_multiplexer.GetLogdirSubdirectories(logdir)
    inspection_units = []
    for subdir in subdirs:
      generator = itertools.chain(*[
          generator_from_event_file(os.path.join(subdir, f))
          for f in gfile.ListDirectory(subdir)
          if event_accumulator.IsTensorFlowEventsFile(os.path.join(subdir, f))
      ])
      inspection_units.append(InspectionUnit(
          name=subdir,
          generator=generator,
          field_to_obs=get_field_to_observations_map(generator, tag)))
    if inspection_units:
      print('Found event files in:\n{}\n'.format('\n'.join(
          [u.name for u in inspection_units])))
    elif event_accumulator.IsTensorFlowEventsFile(logdir):
      print(
          'It seems that {} may be an event file instead of a logdir. If this '
          'is the case, use --event_file instead of --logdir to pass '
          'it in.'.format(logdir))
    else:
      print('No event files found within logdir {}'.format(logdir))
    return inspection_units
  elif event_file:
    generator = generator_from_event_file(event_file)
    return [InspectionUnit(
        name=event_file,
        generator=generator,
        field_to_obs=get_field_to_observations_map(generator, tag))] 

# 需要導入模塊: from tensorflow.python.platform import gfile [as 別名]
# 或者: from tensorflow.python.platform.gfile import ListDirectory [as 別名]
def __init__(self,
               sess,
               session_root,
               watch_fn=None,
               thread_name_filter=None,
               pass_through_operrors=None,
               log_usage=True):
    """Constructor of DumpingDebugWrapperSession.

    Args:
      sess: The TensorFlow `Session` object being wrapped.
      session_root: (`str`) Path to the session root directory. Must be a
        directory that does not exist or an empty directory. If the directory
        does not exist, it will be created by the debugger core during debug
        @{tf.Session.run}
        calls.
        As the `run()` calls occur, subdirectories will be added to
        `session_root`. The subdirectories' names has the following pattern:
          run_<epoch_time_stamp>_<zero_based_run_counter>
        E.g., run_1480734393835964_ad4c953a85444900ae79fc1b652fb324
      watch_fn: (`Callable`) A Callable that can be used to define per-run
        debug ops and watched tensors. See the doc of
        `NonInteractiveDebugWrapperSession.__init__()` for details.
      thread_name_filter: Regular-expression white list for threads on which the
        wrapper session will be active. See doc of `BaseDebugWrapperSession` for
        more details.
      pass_through_operrors: If true, all captured OpErrors will be
        propagated. By default this captures all OpErrors.
      log_usage: (`bool`) whether the usage of this class is to be logged.

    Raises:
       ValueError: If `session_root` is an existing and non-empty directory or
       if `session_root` is a file.
    """

    if log_usage:
      pass  # No logging for open-source.

    framework.NonInteractiveDebugWrapperSession.__init__(
        self, sess, watch_fn=watch_fn, thread_name_filter=thread_name_filter,
        pass_through_operrors=pass_through_operrors)

    if gfile.Exists(session_root):
      if not gfile.IsDirectory(session_root):
        raise ValueError(
            "session_root path points to a file: %s" % session_root)
      elif gfile.ListDirectory(session_root):
        raise ValueError(
            "session_root path points to a non-empty directory: %s" %
            session_root)
    else:
      gfile.MakeDirs(session_root)
    self._session_root = session_root

    self._run_counter = 0
    self._run_counter_lock = threading.Lock()