tensorflow/models · error · ValueError

Value passed to `from_logits` ({from_logits}) is conflicting

Error message

Value passed to `from_logits` ({from_logits}) is conflicting with the `from_logits` value passed to the `loss_fn` metric ({metric_from_logits}). Ensure that they have the same value.

What it means

Error "Value passed to `from_logits` ({from_logits}) is conflicting with the `from_logits` value passed to the `loss_fn` metric ({metric_from_logits}). Ensure that they have the same value." thrown in tensorflow/models.

Source

Thrown at official/recommendation/uplift/metrics/loss_metric.py:111

          "`loss_fn` cannot be a Keras `Loss` object, pass a non-reducing loss"
          " function or a metric instance instead."
      )

    if isinstance(loss_fn, tf_keras.metrics.Metric):
      name = loss_fn.name
      dtype = loss_fn.dtype

    super().__init__(name=name, dtype=dtype)

    self._loss_fn = loss_fn
    self._from_logits = from_logits
    self._loss_fn_kwargs = loss_fn_kwargs
    self._slice_by_treatment = slice_by_treatment

    if isinstance(loss_fn, tf_keras.metrics.Metric):
      metric_from_logits = loss_fn.get_config().get("from_logits", from_logits)
      if from_logits != metric_from_logits:
        raise ValueError(
            f"Value passed to `from_logits` ({from_logits}) is conflicting with"
            " the `from_logits` value passed to the `loss_fn` metric"
            f" ({metric_from_logits}). Ensure that they have the same value."
        )
      loss_metric = loss_fn

    else:
      if "from_logits" in inspect.signature(loss_fn).parameters:
        self._loss_fn_kwargs.update({"from_logits": from_logits})
      loss_metric = tf_keras.metrics.Mean(name=name, dtype=dtype)

    if slice_by_treatment:
      self._loss = treatment_sliced_metric.TreatmentSlicedMetric(loss_metric)
    else:
      self._loss = loss_metric

  def update_state(
      self,

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/recommendation/uplift/metrics/loss_metric.py:111 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/8c356ef0bab732ab. Report an issue: GitHub.