tensorflow/models · error · ValueError

`slice_by_treatment` must be set to `False` when `y_pred` is

Error message

`slice_by_treatment` must be set to `False` when `y_pred` is not of type `TwoTowerTrainingOutputs`.

What it means

Error "`slice_by_treatment` must be set to `False` when `y_pred` is not of type `TwoTowerTrainingOutputs`." thrown in tensorflow/models.

Source

Thrown at official/recommendation/uplift/metrics/poisson_metrics.py:180

    self._slice_by_treatment = slice_by_treatment

    if slice_by_treatment:
      self._mean_label = treatment_sliced_metric.TreatmentSlicedMetric(
          metric=tf_keras.metrics.Mean(name=name, dtype=dtype)
      )
    else:
      self._mean_label = tf_keras.metrics.Mean(name=name, dtype=dtype)

  def update_state(
      self,
      y_true: tf.Tensor,
      y_pred: types.TwoTowerTrainingOutputs | tf.Tensor | None = None,
      sample_weight: tf.Tensor | None = None,
  ):
    is_treatment = {}
    if self._slice_by_treatment:
      if not isinstance(y_pred, types.TwoTowerTrainingOutputs):
        raise ValueError(
            "`slice_by_treatment` must be set to `False` when `y_pred` is not"
            " of type `TwoTowerTrainingOutputs`."
        )
      is_treatment["is_treatment"] = y_pred.is_treatment

    self._mean_label.update_state(
        y_true, sample_weight=sample_weight, **is_treatment
    )

  def result(self) -> tf.Tensor | dict[str, tf.Tensor]:
    return tf.nest.map_structure(_safe_x_minus_xlogx, self._mean_label.result())

  def get_config(self) -> dict[str, Any]:
    config = super().get_config()
    config["compute_full_loss"] = self._compute_full_loss
    config["slice_by_treatment"] = self._slice_by_treatment
    return config

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/recommendation/uplift/metrics/poisson_metrics.py:180 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/587088e0288e4c89. Report an issue: GitHub.