tensorflow/models · error · ValueError

Shape not supported, {}, {}

Error message

Shape not supported, {}, {}

What it means

Error "Shape not supported, {}, {}" thrown in tensorflow/models.

Source

Thrown at official/modeling/fast_training/experimental/tf2_utils_2x_wide.py:161

    var_to.assign(expand_vector(var_from_np))
    return

  a_from, z_from = shape_from[0], shape_from[-1]
  a_to, z_to = shape_to[0], shape_to[-1]

  if a_to == 2 * a_from and z_to == z_from:
    var_to.assign(expand_1_axis(var_from_np, epsilon=epsilon, axis=0))
    return

  if a_to == a_from and z_to == 2 * z_from:
    var_to.assign(expand_1_axis(var_from_np, epsilon=epsilon, axis=-1))
    return

  if a_to == 2 * a_from and z_to == 2 * z_from:
    var_to.assign(expand_2_axes(var_from_np, epsilon=epsilon))
    return

  raise ValueError("Shape not supported, {}, {}".format(shape_from, shape_to))


def model_to_model_2x_wide(model_from: tf.Module,
                           model_to: tf.Module,
                           epsilon: float = 0.1):
  """Expands a model to a wider version.

  Also makes sure that the output of the model is not changed after expanding.
  For example:
  ```
  model_narrow = tf_keras.Sequential()
  model_narrow.add(tf_keras.Input(shape=(3,)))
  model_narrow.add(tf_keras.layers.Dense(4))
  model_narrow.add(tf_keras.layers.Dense(1))

  model_wide = tf_keras.Sequential()
  model_wide.add(tf_keras.Input(shape=(6,)))
  model_wide.add(tf_keras.layers.Dense(8))

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/modeling/fast_training/experimental/tf2_utils_2x_wide.py:161 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/a234cfdbc8baf2af. Report an issue: GitHub.