Function staged

tensorflow/python/ops/prefetch.py:92–238

Prefetch samples. Args: features: Nest structure of tensors to prefetch. feed_dict: (Optional.) A dictionary that maps graph elements to values. Each key in `feed_dict` can be one of the following types: * `tf.Tensor` or `tf.compat.v1.placeholder`: the value should be a tensor

(
    features,
    feed_dict={},
    capacity=1,
    num_threads=1,
    num_clients=1,
    timeout_millis=300000,
    closed_exception_types=(errors.OUT_OF_RANGE,),
    ignored_exception_types=(),
    use_stage_subgraph_thread_pool=False,
    stage_subgraph_thread_pool_id = 0,
    stage_subgraph_stream_id = 0,
    name=None)

@tf_export(v1=["staged"])
def staged(
    features,
    feed_dict={},
    capacity=1,
    num_threads=1,
    num_clients=1,
    timeout_millis=300000,
    closed_exception_types=(errors.OUT_OF_RANGE,),
    ignored_exception_types=(),
    use_stage_subgraph_thread_pool=False,
    stage_subgraph_thread_pool_id = 0,
    stage_subgraph_stream_id = 0,
    name=None):
  """Prefetch samples.

  Args:
    features: Nest structure of tensors to prefetch.
    feed_dict: (Optional.) A dictionary that maps graph elements to values.
      Each key in `feed_dict` can be one of the following types:
      * `tf.Tensor` or `tf.compat.v1.placeholder`: the value should be a tensor.
      * `tf.SparseTensor`: the value should be a `tf.compat.v1.SparseTensorValue`.
      * a nested tuple of `Tensor`s or `SparseTensor`s, the value should be a
        nested tuple with the same structure that maps to their corresponding
        values as above.
    capacity: (Optional.) Max number of samples to keep in the buffer.
    num_threads: (Optional.) Number of threads for prefetching. 1 by
      default.
    num_clients: (Optional.) Number of clients of prefetched sample. 1 by
      default.
    timeout_millis: (Optional.) Max milliseconds put op can take, 5 min by
      default.
    closed_exception_types: (Optional.) Exception types indicating that the
      prefetching is normally finished. Defaults to
      `(errors.OUT_OF_RANGE,)`.
    ignored_exception_types: (Optional.) Exception types indicating that the
      prefetching can continue. Defaults to `()`.
    use_stage_subgraph_thread_pool: (Optional.) Use stage subgraph thread pool
      to run stage graph or not.
    stage_subgraph_thread_pool_id: (Optional.) Specifies the stage subgraph
      thread pool to use when enable use_stage_subgraph_thread_pool. 0 by default.
    stage_subgraph_stream_id: (Optional.) Specifies which stream to use for the
      Stage subgraph. The default value is 0.
    name: (Optional.) Name of prefetching operations.

  Returns:
    Prefetched sample.
  """
  if num_threads < 1:
    raise ValueError('num_threads must >= 1')

  if name is None:
    name = ops.get_default_graph().unique_name(PREFETCH)
  with ops.name_scope(name):
    local_device = control_flow_ops.no_op().device
  tensor_or_sparse_tensor_or_nones = nest.flatten(features)

  tensor_or_nones = []
  for t in tensor_or_sparse_tensor_or_nones: