keras-team/keras · error · ValueError

`idf_weights` should only be set if output_mode is `'tf_idf'

Error message

`idf_weights` should only be set if output_mode is `'tf_idf'`. Received: output_mode={self.output_mode} and idf_weights={idf_weights}

What it means

The mirror of the missing-weights check: set_vocabulary() rejects `idf_weights` when the layer's output_mode is anything other than tf_idf, keeping the weight vector and the mode consistent.

Source

Thrown at keras/src/layers/preprocessing/index_lookup.py:438

        Args:
            vocabulary: Either an array or a string path to a text file.
                If passing an array, can pass a tuple, list,
                1D numpy array, or 1D tensor containing the vocbulary terms.
                If passing a file path, the file should contain one line
                per term in the vocabulary.
            idf_weights: A tuple, list, 1D numpy array, or 1D tensor
                of inverse document frequency weights with equal
                length to vocabulary. Must be set if `output_mode`
                is `"tf_idf"`. Should not be set otherwise.
        """
        if self.output_mode == "tf_idf":
            if idf_weights is None:
                raise ValueError(
                    "`idf_weights` must be set if output_mode is 'tf_idf'."
                )
        elif idf_weights is not None:
            raise ValueError(
                "`idf_weights` should only be set if output_mode is "
                f"`'tf_idf'`. Received: output_mode={self.output_mode} "
                f"and idf_weights={idf_weights}"
            )

        if isinstance(vocabulary, str):
            if serialization_lib.in_safe_mode():
                raise ValueError(
                    "Requested the loading of a vocabulary file outside of the "
                    "model archive. This carries a potential risk of loading "
                    "arbitrary and sensitive files and thus it is disallowed "
                    "by default. If you trust the source of the artifact, you "
                    "can override this error by passing `safe_mode=False` to "
                    "the loading function, or calling "
                    "`keras.config.enable_unsafe_deserialization(). "
                    f"Vocabulary file: '{vocabulary}'"
                )

View on GitHub (pinned to 7a34a03db6)

Solutions

1. Only pass idf_weights to the tf_idf layer; branch on `layer.output_mode`.
2. Or rebuild the layer with `output_mode='tf_idf'` if idf scaling is wanted.

Example fix

# before
def set_vocab(layer, vocab, idf):
    layer.set_vocabulary(vocab, idf_weights=idf)

# after
def set_vocab(layer, vocab, idf):
    if layer.output_mode == 'tf_idf':
        layer.set_vocabulary(vocab, idf_weights=idf)
    else:
        layer.set_vocabulary(vocab)

if layer.output_mode == 'tf_idf':
    layer.set_vocabulary(vocab, idf_weights=idf)
else:
    layer.set_vocabulary(vocab)

When it happens

Trigger: `layer.set_vocabulary(vocab, idf_weights=w)` on a layer constructed with output_mode 'int', 'multi_hot', 'count' or 'one_hot'.

Common situations: Shared vocabulary-setting helper code used for both a tf_idf layer and an int-index layer.

Related errors

• `idf_weights` should only be set if `output_mode` is `'tf_id
• `num_oov_indices` must be greater than or equal to 0. Receiv
• `salt` can only be used when `oov_method='farmhash'`. Receiv
• The `salt` argument for `IndexLookup` can only be a tuple of
• `output_mode` must be `'int'` when `invert` is true. Receive

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/277391e268479143. Report an issue: GitHub.