tensorflow/models · error · ValueError

filter_size_scale is not greater than zero.

Error message

filter_size_scale is not greater than zero.

What it means

Error "filter_size_scale is not greater than zero." thrown in tensorflow/models.

Source

Thrown at official/vision/modeling/backbones/mobilenet.py:1294

        this number.
      stochastic_depth_drop_rate: A `float` of drop rate for drop connect layer.
      flat_stochastic_depth_drop_rate: A `bool`, indicating that the stochastic
        depth drop rate will be fixed and equal to all blocks.
      regularize_depthwise: If Ture, apply regularization on depthwise.
      use_sync_bn: If True, use synchronized batch normalization.
      finegrain_classification_mode: If True, the model will keep the last layer
        large even for small multipliers, following
        https://arxiv.org/abs/1801.04381.
      output_intermediate_endpoints: A `bool` of whether or not output the
        intermediate endpoints.
      **kwargs: Additional keyword arguments to be passed.
    """
    if model_id not in SUPPORTED_SPECS_MAP:
      raise ValueError('The MobileNet version {} '
                       'is not supported'.format(model_id))

    if filter_size_scale <= 0:
      raise ValueError('filter_size_scale is not greater than zero.')

    if output_stride is not None:
      if model_id == 'MobileNetV1':
        if output_stride not in [8, 16, 32]:
          raise ValueError('Only allowed output_stride values are 8, 16, 32.')
      else:
        if output_stride == 0 or (output_stride > 1 and output_stride % 2):
          raise ValueError('Output stride must be None, 1 or a multiple of 2.')

    self._model_id = model_id
    self._input_specs = input_specs
    self._filter_size_scale = filter_size_scale
    self._min_depth = min_depth
    self._output_stride = output_stride
    self._divisible_by = divisible_by
    self._stochastic_depth_drop_rate = stochastic_depth_drop_rate
    self._flat_stochastic_depth_drop_rate = flat_stochastic_depth_drop_rate
    self._regularize_depthwise = regularize_depthwise

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Set filter_size_scale to a positive float (e.g. 1.0).
2. Remove filter_size_scale from the config to use the default scaling.

When it happens

Trigger: Thrown at official/vision/modeling/backbones/mobilenet.py:1294 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/8e938649b8d97cde. Report an issue: GitHub.