tensorflow/models · error · KeyError

The call method expects either `inputs` or `embedded_inputs`

Error message

The call method expects either `inputs` or `embedded_inputs` and `input_masks` as input features.

What it means

Error "The call method expects either `inputs` or `embedded_inputs` and `input_masks` as input features." thrown in tensorflow/models.

Source

Thrown at official/nlp/modeling/models/seq2seq_transformer.py:143

  def _parse_inputs(self, inputs):
    """Parses the `call` inputs and returns an uniformed output."""
    sources = inputs.get("inputs", None)
    input_mask = inputs.get("input_masks", None)
    embedded = inputs.get("embedded_inputs", None)

    if sources is None and embedded is not None:
      embedded_inputs = embedded
      boolean_mask = input_mask
      input_shape = tf_utils.get_shape_list(embedded, expected_rank=3)
      source_dtype = embedded.dtype
    elif sources is not None:
      embedded_inputs = self.embedding_lookup(sources)
      boolean_mask = tf.not_equal(sources, 0)
      input_shape = tf_utils.get_shape_list(sources, expected_rank=2)
      source_dtype = sources.dtype
    else:
      raise KeyError(
          "The call method expects either `inputs` or `embedded_inputs` and "
          "`input_masks` as input features.")

    return embedded_inputs, boolean_mask, input_shape, source_dtype

  def call(self, inputs):  # pytype: disable=signature-mismatch  # overriding-parameter-count-checks
    """Calculate target logits or inferred target sequences.

    Args:
      inputs: a dictionary of tensors.
        Feature `inputs` (optional): int tensor with shape
          `[batch_size, input_length]`.
        Feature `embedded_inputs` (optional): float tensor with shape
          `[batch_size, input_length, embedding_width]`.
        Feature `targets` (optional): None or int tensor with shape
          `[batch_size, target_length]`.
        Feature `input_masks` (optional): When providing the `embedded_inputs`,
          the dictionary must provide a boolean mask marking the filled time

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/nlp/modeling/models/seq2seq_transformer.py:143 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/8bef6d3b57ddc900. Report an issue: GitHub.