Method find

tensorflow/python/debug/lib/debug_data.py:1417–1464

Find dumped tensor data by a certain predicate. Args: predicate: A callable that takes two input arguments: ```python def predicate(debug_tensor_datum, tensor): # returns a bool ``` where `debug_tensor_datum` is an instance of `DebugTensorDatum`

(self,
           predicate,
           first_n=0,
           device_name=None,
           exclude_node_names=None)

    return self._watch_key_to_datum[device_name].get(debug_watch_key, [])

  def find(self,
           predicate,
           first_n=0,
           device_name=None,
           exclude_node_names=None):
    """Find dumped tensor data by a certain predicate.

    Args:
      predicate: A callable that takes two input arguments:

        ```python
        def predicate(debug_tensor_datum, tensor):
          # returns a bool
        ```

        where `debug_tensor_datum` is an instance of `DebugTensorDatum`, which
        carries the metadata, such as the `Tensor`'s node name, output slot
        timestamp, debug op name, etc.; and `tensor` is the dumped tensor value
        as a `numpy.ndarray`.
      first_n: (`int`) return only the first n `DebugTensotDatum` instances (in
        time order) for which the predicate returns True. To return all the
        `DebugTensotDatum` instances, let first_n be <= 0.
      device_name: optional device name.
      exclude_node_names: Optional regular expression to exclude nodes with
        names matching the regular expression.

    Returns:
      A list of all `DebugTensorDatum` objects in this `DebugDumpDir` object
       for which predicate returns True, sorted in ascending order of the
       timestamp.
    """
    if exclude_node_names:
      exclude_node_names = re.compile(exclude_node_names)

    matched_data = []
    for device in (self._dump_tensor_data if device_name is None
                   else (self._dump_tensor_data[device_name],)):
      for datum in self._dump_tensor_data[device]:
        if exclude_node_names and exclude_node_names.match(datum.node_name):
          continue

        if predicate(datum, datum.get_tensor()):
          matched_data.append(datum)

          if first_n > 0 and len(matched_data) >= first_n:
            return matched_data

    return matched_data

  def get_tensor_file_paths(self,
                            node_name,