tensorflow/models · error · ValueError

Stem type {stem_type} not supported.

Error message

Stem type {stem_type} not supported.

What it means

Error "Stem type {stem_type} not supported." thrown in tensorflow/models.

Source

Thrown at official/projects/const_cl/modeling/backbones/resnet_3d.py:220

    if stem_type == 'v0':
      self._stem_conv = layers.Conv3D(
          filters=64,
          kernel_size=[self._stem_conv_temporal_kernel_size, 7, 7],
          strides=[self._stem_conv_temporal_stride, 2, 2],
          use_bias=False,
          padding='same',
          kernel_initializer=self._kernel_initializer,
          kernel_regularizer=self._kernel_regularizer,
          bias_regularizer=self._bias_regularizer,
          name='stem')
      self._stem_bn = self._norm(
          axis=self._bn_axis,
          momentum=self._norm_momentum,
          epsilon=self._norm_epsilon,
          name='stem/batch_norm')
      self._stem_activation = tf_utils.get_activation(self._activation)
    else:
      raise ValueError(f'Stem type {stem_type} not supported.')

  def _build_block_group(
      self,
      inputs: tf.Tensor,
      filters: int,
      temporal_kernel_sizes: Tuple[int],
      temporal_strides: int,
      spatial_strides: int,
      block_fn: Callable[
          ..., tf_keras.layers.Layer] = nn_blocks_3d.BottleneckBlock3D,
      block_repeats: int = 1,
      stochastic_depth_drop_rate: float = 0.0,
      use_self_gating: bool = False,
      name: str = 'block_group'):
    """Creates one group of blocks for the ResNet3D model.

    Args:
      inputs: A `tf.Tensor` of size `[batch, channels, height, width]`.

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/const_cl/modeling/backbones/resnet_3d.py:220 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/176f7f295dcfa9e9. Report an issue: GitHub.