tensorflow/models · error · ValueError

values and is_treatment must be tensors of shapes (D0, D1, .

Error message

values and is_treatment must be tensors of shapes (D0, D1, ..., DN) and (D0, 1) (or (D0,)), but got tensors of shapes {values.shape} and {is_treatment.shape} respectively.

What it means

Error "values and is_treatment must be tensors of shapes (D0, D1, ..., DN) and (D0, 1) (or (D0,)), but got tensors of shapes {values.shape} and {is_treatment.shape} respectively." thrown in tensorflow/models.

Source

Thrown at official/recommendation/uplift/utils.py:61

  Args:
    values: a `tf.Tensor` of shape (D0, D1, ..., DN).
    is_treatment: a `tf.Tensor` of shape (D0,) or (D0, 1) castable to boolean
      indicating if the example belongs to the treatment group (True) or control
      group (False).

  Returns:
    A tuple with control and treatment values sliced by the is_treatment tensor.
  """
  if is_treatment.shape.rank > 2 or (
      is_treatment.shape == 2 and is_treatment.shape[1] != 1  # pyrefly: ignore[unsupported-operation]
  ):
    raise ValueError(
        "is_treatment tensor must be a tensor of shape (D0,) (D0, 1) but got a"
        f" tensor of shape {is_treatment.shape} instead."
    )

  if values.shape[0] != is_treatment.shape[0]:
    raise ValueError(
        "values and is_treatment must be tensors of shapes (D0, D1, ..., DN)"
        f" and (D0, 1) (or (D0,)), but got tensors of shapes {values.shape} and"
        f" {is_treatment.shape} respectively."
    )

  if is_treatment.dtype == tf.string:
    raise ValueError(
        "is_treatment must be a tensor castable to boolean but got tensor"
        f" {is_treatment} of dtype {is_treatment.dtype} instead."
    )

  # Assert is_treatment tensor containss only 0 or 1 values.
  if is_treatment.dtype != tf.bool:
    is_treatment_float = tf.cast(is_treatment, tf.float32)
    tf.debugging.assert_equal(
        tf.reduce_all(
            tf.logical_or(is_treatment_float == 1.0, is_treatment_float == 0.0)
        ),

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/recommendation/uplift/utils.py:61 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/3c48e9081386de56. Report an issue: GitHub.