Function _process_raw_parameters

tensorflow/python/ops/parsing_ops.py:879–982

Process raw parameters to params used by `gen_parsing_ops`. Args: names: A vector (1-D Tensor) of strings (optional), the names of the serialized protos. dense_defaults: A dict mapping string keys to `Tensor`s. The keys of the dict must match the dense_keys of the feature.

(names, dense_defaults, sparse_keys, sparse_types,
                            dense_keys, dense_types, dense_shapes)

def _process_raw_parameters(names, dense_defaults, sparse_keys, sparse_types,
                            dense_keys, dense_types, dense_shapes):
  """Process raw parameters to params used by `gen_parsing_ops`.

  Args:
    names: A vector (1-D Tensor) of strings (optional), the names of
      the serialized protos.
    dense_defaults: A dict mapping string keys to `Tensor`s.
      The keys of the dict must match the dense_keys of the feature.
    sparse_keys: A list of string keys in the examples' features.
      The results for these keys will be returned as `SparseTensor` objects.
    sparse_types: A list of `DTypes` of the same length as `sparse_keys`.
      Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
      and `tf.string` (`BytesList`) are supported.
    dense_keys: A list of string keys in the examples' features.
      The results for these keys will be returned as `Tensor`s
    dense_types: A list of DTypes of the same length as `dense_keys`.
      Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
      and `tf.string` (`BytesList`) are supported.
    dense_shapes: A list of tuples with the same length as `dense_keys`.
      The shape of the data for each dense feature referenced by `dense_keys`.
      Required for any input tensors identified by `dense_keys`.  Must be
      either fully defined, or may contain an unknown first dimension.
      An unknown first dimension means the feature is treated as having
      a variable number of blocks, and the output shape along this dimension
      is considered unknown at graph build time.  Padding is applied for
      minibatch elements smaller than the maximum number of blocks for the
      given feature along this dimension.

  Returns:
    Tuple of `names`, `dense_defaults_vec`, `sparse_keys`, `sparse_types`,
    `dense_keys`, `dense_shapes`.

  Raises:
    ValueError: If sparse and dense key sets intersect, or input lengths do not
      match up.
  """
  names = [] if names is None else names
  dense_defaults = collections.OrderedDict(
  ) if dense_defaults is None else dense_defaults
  sparse_keys = [] if sparse_keys is None else sparse_keys
  sparse_types = [] if sparse_types is None else sparse_types
  dense_keys = [] if dense_keys is None else dense_keys
  dense_types = [] if dense_types is None else dense_types
  dense_shapes = ([[]] * len(dense_keys)
                  if dense_shapes is None else dense_shapes)

  num_dense = len(dense_keys)
  num_sparse = len(sparse_keys)

  if len(dense_shapes) != num_dense:
    raise ValueError("len(dense_shapes) != len(dense_keys): %d vs. %d" %
                     (len(dense_shapes), num_dense))
  if len(dense_types) != num_dense:
    raise ValueError("len(dense_types) != len(num_dense): %d vs. %d" %
                     (len(dense_types), num_dense))
  if len(sparse_types) != num_sparse:
    raise ValueError("len(sparse_types) != len(sparse_keys): %d vs. %d" %