Python tensorflow.python.framework.errors.raise_exception_on_not_ok_status() Examples

def _extend_graph(self):
    # Ensure any changes to the graph are reflected in the runtime.
    with self._extend_lock:
      if self._graph.version > self._current_version:
        # pylint: disable=protected-access
        graph_def, self._current_version = self._graph._as_graph_def(
            from_version=self._current_version,
            add_shapes=self._add_shapes)
        # pylint: enable=protected-access

        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_ExtendGraph(
              self._session, graph_def.SerializeToString(), status)
        self._opened = True

  # The threshold to run garbage collection to delete dead tensors. 

def file_exists(filename):
  """Determines whether a path exists or not.

  Args:
    filename: string, a path

  Returns:
    True if the path exists, whether its a file or a directory.
    False if the path does not exist and there are no filesystem errors.

  Raises:
    errors.OpError: Propagates any errors reported by the FileSystem API.
  """
  try:
    with errors.raise_exception_on_not_ok_status() as status:
      pywrap_tensorflow.FileExists(compat.as_bytes(filename), status)
  except errors.NotFoundError:
    return False
  return True 

def get_matching_files(filename):
  """Returns a list of files that match the given pattern.

  Args:
    filename: string, the pattern

  Returns:
    Returns a list of strings containing filenames that match the given pattern.

  Raises:
    errors.OpError: If there are filesystem / directory listing errors.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    # Convert each element to string, since the return values of the
    # vector of string should be interpreted as strings, not bytes.
    return [compat.as_str_any(matching_filename)
            for matching_filename in pywrap_tensorflow.GetMatchingFiles(
                compat.as_bytes(filename), status)] 

def list_directory(dirname):
  """Returns a list of entries contained within a directory.

  The list is in arbitrary order. It does not contain the special entries "."
  and "..".

  Args:
    dirname: string, path to a directory

  Returns:
    [filename1, filename2, ... filenameN] as strings

  Raises:
    errors.NotFoundError if directory doesn't exist
  """
  if not is_directory(dirname):
    raise errors.NotFoundError(None, None, "Could not find directory")
  with errors.raise_exception_on_not_ok_status() as status:
    # Convert each element to string, since the return values of the
    # vector of string should be interpreted as strings, not bytes.
    return [
        compat.as_str_any(filename)
        for filename in pywrap_tensorflow.GetChildren(
            compat.as_bytes(dirname), status)
    ] 

def read(self, n=-1):
    """Returns the contents of a file as a string.

    Starts reading from current position in file.

    Args:
      n: Read 'n' bytes if n != -1. If n = -1, reads to end of file.

    Returns:
      'n' bytes of the file (or whole file) in bytes mode or 'n' bytes of the
      string if in string (regular) mode.
    """
    self._preread_check()
    with errors.raise_exception_on_not_ok_status() as status:
      if n == -1:
        length = self.size() - self.tell()
      else:
        length = n
      return self._prepare_value(
          pywrap_tensorflow.ReadFromStream(self._read_buf, length, status)) 

def file_exists(filename):
  """Determines whether a path exists or not.

  Args:
    filename: string, a path

  Returns:
    True if the path exists, whether its a file or a directory.
    False if the path does not exist and there are no filesystem errors.

  Raises:
    errors.OpError: Propagates any errors reported by the FileSystem API.
  """
  try:
    with errors.raise_exception_on_not_ok_status() as status:
      pywrap_tensorflow.FileExists(compat.as_bytes(filename), status)
  except errors.NotFoundError:
    return False
  return True 

def list_directory(dirname):
  """Returns a list of entries contained within a directory.

  The list is in arbitrary order. It does not contain the special entries "."
  and "..".

  Args:
    dirname: string, path to a directory

  Returns:
    [filename1, filename2, ... filenameN] as strings

  Raises:
    errors.NotFoundError if directory doesn't exist
  """
  if not is_directory(dirname):
    raise errors.NotFoundError(None, None, "Could not find directory")
  with errors.raise_exception_on_not_ok_status() as status:
    # Convert each element to string, since the return values of the
    # vector of string should be interpreted as strings, not bytes.
    return [
        compat.as_str_any(filename)
        for filename in pywrap_tensorflow.GetChildren(
            compat.as_bytes(dirname), status)
    ] 

def read(self, n=-1):
    """Returns the contents of a file as a string.

    Starts reading from current position in file.

    Args:
      n: Read 'n' bytes if n != -1. If n = -1, reads to end of file.

    Returns:
      'n' bytes of the file (or whole file) requested as a string.
    """
    self._preread_check()
    with errors.raise_exception_on_not_ok_status() as status:
      if n == -1:
        length = self.size() - self.tell()
      else:
        length = n
      return pywrap_tensorflow.ReadFromStream(self._read_buf, length, status) 

def _extend_graph(self):
    # Ensure any changes to the graph are reflected in the runtime.
    with self._extend_lock:
      if self._graph.version > self._current_version:
        # pylint: disable=protected-access
        graph_def, self._current_version = self._graph._as_graph_def(
            from_version=self._current_version,
            add_shapes=self._add_shapes)
        # pylint: enable=protected-access

        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_ExtendGraph(
              self._session, graph_def.SerializeToString(), status)
        self._opened = True

  # The threshold to run garbage collection to delete dead tensors. 

def close(self):
    """Closes this session.

    Calling this method frees all resources associated with the session.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        closing the TensorFlow session.
    """
    if self._created_with_new_api:
      if self._session and not self._closed:
        self._closed = True
        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_CloseSession(self._session, status)

    else:
      with self._extend_lock:
        if self._opened and not self._closed:
          self._closed = True
          with errors.raise_exception_on_not_ok_status() as status:
            tf_session.TF_CloseDeprecatedSession(self._session, status) 

def _extend_graph(self):
    # Nothing to do if we're using the new session interface
    # TODO(skyewm): remove this function altogether eventually
    if self._created_with_new_api: return

    # Ensure any changes to the graph are reflected in the runtime.
    with self._extend_lock:
      if self._graph.version > self._current_version:
        # pylint: disable=protected-access
        graph_def, self._current_version = self._graph._as_graph_def(
            from_version=self._current_version,
            add_shapes=self._add_shapes)
        # pylint: enable=protected-access

        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_ExtendGraph(
              self._session, graph_def.SerializeToString(), status)
        self._opened = True

  # The threshold to run garbage collection to delete dead tensors. 

def _extend_graph(self):
    # Ensure any changes to the graph are reflected in the runtime.
    with self._extend_lock:
      if self._graph.version > self._current_version:
        # pylint: disable=protected-access
        graph_def, self._current_version = self._graph._as_graph_def(
            from_version=self._current_version,
            add_shapes=self._add_shapes)
        # pylint: enable=protected-access

        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_ExtendGraph(
              self._session, graph_def.SerializeToString(), status)
        self._opened = True

  # The threshold to run garbage collection to delete dead tensors. 

def _initialize_handle_and_devices(self):
    """Initialize handle and devices."""
    with self._initialize_lock:
      if self._context_handle is not None:
        return
      assert self._context_devices is None
      opts = pywrap_tensorflow.TF_NewSessionOptions(
          target=compat.as_bytes(""), config=self._config)
      with errors.raise_exception_on_not_ok_status() as status:
        self._context_handle = pywrap_tensorflow.TFE_NewContext(opts, status)
        pywrap_tensorflow.TF_DeleteSessionOptions(opts)
      # Store list of devices
      self._context_devices = []
      with errors.raise_exception_on_not_ok_status() as status:
        device_list = pywrap_tensorflow.TFE_ContextListDevices(
            self._context_handle, status)
      try:
        for i in range(pywrap_tensorflow.TF_DeviceListCount(device_list)):
          with errors.raise_exception_on_not_ok_status() as status:
            dev_name = pywrap_tensorflow.TF_DeviceListName(
                device_list, i, status)
          self._context_devices.append(pydev.canonical_name(dev_name))
      finally:
        pywrap_tensorflow.TF_DeleteDeviceList(device_list) 

def add_function_def(self, fdef):
    """Add a function definition to the context.

    Once added, the function (identified by its name) can be executed like any
    other operation.

    Args:
      fdef: A FunctionDef protocol buffer message.
    """
    fdef_string = fdef.SerializeToString()
    with errors.raise_exception_on_not_ok_status() as status:
      pywrap_tensorflow.TFE_ContextAddFunctionDef(
          self._handle,  # pylint: disable=protected-access
          fdef_string,
          len(fdef_string),
          status) 

def Load(self):
    """Loads all new values from disk.

    Calling Load multiple times in a row will not 'drop' events as long as the
    return value is not iterated over.

    Yields:
      All values that were written to disk that have not been yielded yet.
    """
    while True:
      try:
        with errors.raise_exception_on_not_ok_status() as status:
          self._reader.GetNext(status)
      except (errors.DataLossError, errors.OutOfRangeError):
        # We ignore partial read exceptions, because a record may be truncated.
        # PyRecordReader holds the offset prior to the failed read, so retrying
        # will succeed.
        break
      event = event_pb2.Event()
      event.ParseFromString(self._reader.record())
      yield event
    logging.debug('No more events in %s', self._file_path) 

def TF_Reset(target, containers=None, config=None):
  from tensorflow.python.framework import errors
  opts = TF_NewSessionOptions(target=target, config=config)
  try:
    with errors.raise_exception_on_not_ok_status() as status:
      TF_Reset_wrapper(opts, containers, status)
  finally:
    TF_DeleteSessionOptions(opts) 

def delete_recursively(dirname):
  """Deletes everything under dirname recursively.

  Args:
    dirname: string, a path to a directory

  Raises:
    errors.OpError: If the operation fails.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    pywrap_tensorflow.DeleteRecursively(compat.as_bytes(dirname), status) 

def rename(oldname, newname, overwrite=False):
  """Rename or move a file / directory.

  Args:
    oldname: string, pathname for a file
    newname: string, pathname to which the file needs to be moved
    overwrite: boolean, if false its an error for newpath to be occupied by an
        existing file.

  Raises:
    errors.OpError: If the operation fails.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    pywrap_tensorflow.RenameFile(
        compat.as_bytes(oldname), compat.as_bytes(newname), overwrite, status) 

def delete_file(filename):
  """Deletes the file located at 'filename'.

  Args:
    filename: string, a filename

  Raises:
    errors.OpError: Propagates any errors reported by the FileSystem API.  E.g.,
    NotFoundError if the file does not exist.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    pywrap_tensorflow.DeleteFile(compat.as_bytes(filename), status) 

def list_devices():
  from tensorflow.python.framework import errors

  with errors.raise_exception_on_not_ok_status() as status:
    return ListDevices(status) 

def list_devices(self):
    """Lists available devices in this session.

    ```python
    devices = sess.list_devices()
    for d in devices:
      print(d.name)
    ```

    Each element in the list has the following properties:
     - `name`: A string with the full name of the device. ex:
          `/job:worker/replica:0/task:3/device:CPU:0`
     - `device_type`: The type of the device (e.g. `CPU`, `GPU`, `TPU`.)
     - `memory_limit`: The maximum amount of memory available on the device.
          Note: depending on the device, it is possible the usable memory could
          be substantially less.
    Raises:
      tf.errors.OpError: If it encounters an error (e.g. session is in an
      invalid state, or network errors occur).

    Returns:
      A list of devices in the session.
    """
    with errors.raise_exception_on_not_ok_status() as status:
      if self._created_with_new_api:
        raw_device_list = tf_session.TF_SessionListDevices(
            self._session, status)
      else:
        raw_device_list = tf_session.TF_DeprecatedSessionListDevices(
            self._session, status)
      device_list = []
      size = tf_session.TF_DeviceListCount(raw_device_list)
      for i in range(size):
        name = tf_session.TF_DeviceListName(raw_device_list, i, status)
        device_type = tf_session.TF_DeviceListType(raw_device_list, i, status)
        memory = tf_session.TF_DeviceListMemoryBytes(raw_device_list, i, status)
        device_list.append(_DeviceAttributes(name, device_type, memory))
      tf_session.TF_DeleteDeviceList(raw_device_list)
      return device_list 

def TF_NewSessionOptions(target=None, config=None):
# NOTE: target and config are validated in the session constructor.
  opts = _TF_NewSessionOptions()
  if target is not None:
    _TF_SetTarget(opts, target)
  if config is not None:
    from tensorflow.python.framework import errors
    with errors.raise_exception_on_not_ok_status() as status:
      config_str = config.SerializeToString()
      _TF_SetConfig(opts, config_str, status)
  return opts 

def copy(oldpath, newpath, overwrite=False):
  """Copies data from oldpath to newpath.

  Args:
    oldpath: string, name of the file who's contents need to be copied
    newpath: string, name of the file to which to copy to
    overwrite: boolean, if false its an error for newpath to be occupied by an
        existing file.

  Raises:
    errors.OpError: If the operation fails.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    pywrap_tensorflow.CopyFile(
        compat.as_bytes(oldpath), compat.as_bytes(newpath), overwrite, status) 

def recursive_create_dir(dirname):
  """Creates a directory and all parent/intermediate directories.

  It succeeds if dirname already exists and is writable.

  Args:
    dirname: string, name of the directory to be created

  Raises:
    errors.OpError: If the operation fails.
  """
  with errors.raise_exception_on_not_ok_status() as status:
    pywrap_tensorflow.RecursivelyCreateDir(compat.as_bytes(dirname), status) 

def close(self):
    """Closes this session.

    Calling this method frees all resources associated with the session.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        closing the TensorFlow session.
    """
    with self._extend_lock:
      if self._opened and not self._closed:
        self._closed = True
        with errors.raise_exception_on_not_ok_status() as status:
          tf_session.TF_CloseDeprecatedSession(self._session, status) 

def close(self):
    """Closes FileIO. Should be called for the WritableFile to be flushed."""
    self._read_buf = None
    if self._writable_file:
      with errors.raise_exception_on_not_ok_status() as status:
        ret_status = self._writable_file.Close()
        pywrap_tensorflow.Set_TF_Status_from_Status(status, ret_status)
    self._writable_file = None 

def flush(self):
    """Flushes the Writable file.

    This only ensures that the data has made its way out of the process without
    any guarantees on whether it's written to disk. This means that the
    data would survive an application crash but not necessarily an OS crash.
    """
    if self._writable_file:
      with errors.raise_exception_on_not_ok_status() as status:
        ret_status = self._writable_file.Flush()
        pywrap_tensorflow.Set_TF_Status_from_Status(status, ret_status) 

def write(self, file_content):
    """Writes file_content to the file. Appends to the end of the file."""
    self._prewrite_check()
    with errors.raise_exception_on_not_ok_status() as status:
      pywrap_tensorflow.AppendToFile(
          compat.as_bytes(file_content), self._writable_file, status) 

def _prewrite_check(self):
    if not self._writable_file:
      if not self._write_check_passed:
        raise errors.PermissionDeniedError(None, None,
                                           "File isn't open for writing")
      with errors.raise_exception_on_not_ok_status() as status:
        self._writable_file = pywrap_tensorflow.CreateWritableFile(
            compat.as_bytes(self.__name), compat.as_bytes(self.__mode), status) 

def _preread_check(self):
    if not self._read_buf:
      if not self._read_check_passed:
        raise errors.PermissionDeniedError(None, None,
                                           "File isn't open for reading")
      with errors.raise_exception_on_not_ok_status() as status:
        self._read_buf = pywrap_tensorflow.CreateBufferedInputStream(
            compat.as_bytes(self.__name), 1024 * 512, status)