tensorflow/models · error · ValueError

%s classifier type not supported.

Error message

%s classifier type not supported.

What it means

Error "%s classifier type not supported." thrown in tensorflow/models.

Source

Thrown at official/projects/videoglue/modeling/video_classification_model.py:113

    inputs = {
        k: tf_keras.Input(shape=v.shape[1:]) for k, v in input_specs.items()
    }
    endpoints = backbone(inputs['image'])

    if classifier_type == 'linear':
      pool_or_flatten_op = tf_keras.layers.GlobalAveragePooling3D()
    elif classifier_type == 'pooler':
      pool_or_flatten_op = lambda x: tf.reshape(  # pylint:disable=g-long-lambda
          x,
          [
              tf.shape(x)[0],
              tf.shape(x)[1],
              tf.shape(x)[2] * tf.shape(x)[3],
              tf.shape(x)[4],
          ],
      )
    else:
      raise ValueError('%s classifier type not supported.' % classifier_type)

    if aggregate_endpoints:
      pooled_feats = []
      for endpoint in endpoints.values():
        x_pool = pool_or_flatten_op(endpoint)
        pooled_feats.append(x_pool)
      x = tf.concat(pooled_feats, axis=1)
    else:
      if not require_endpoints:
        # Use the last endpoint for prediction.
        x = endpoints[max(endpoints.keys())]
        x = pool_or_flatten_op(x)
      else:
        # Concat all the required endpoints for prediction.
        outputs = []
        for name in require_endpoints:
          x = endpoints[name]
          x = pool_or_flatten_op(x)

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/videoglue/modeling/video_classification_model.py:113 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/9616d46a1395ef6a. Report an issue: GitHub.