tensorflow/models · error · ValueError

Number of blocks in temporal specs should equal to resnet_sp

Error message

Number of blocks in temporal specs should equal to resnet_specs.

What it means

Error "Number of blocks in temporal specs should equal to resnet_specs." thrown in tensorflow/models.

Source

Thrown at official/projects/const_cl/modeling/backbones/resnet_3d.py:145

      inputs: the Keras input spec.

    Returns:
      endpoints: A dictionary of backbone endpoint features.
    """
    # Build stem.
    self._build_stem(inputs, stem_type=self._stem_type)

    temporal_kernel_size = 1 if self._stem_pool_temporal_stride == 1 else 3
    self._max_pool = layers.MaxPool3D(
        pool_size=[temporal_kernel_size, 3, 3],
        strides=[self._stem_pool_temporal_stride, 2, 2],
        padding='same')

    # Build intermediate blocks and endpoints.
    resnet_specs = RESNET_SPECS[self._model_id]
    if len(self._temporal_strides) != len(resnet_specs) or len(
        self._temporal_kernel_sizes) != len(resnet_specs):
      raise ValueError(
          'Number of blocks in temporal specs should equal to resnet_specs.')

    self._blocks = {}
    for i, resnet_spec in enumerate(resnet_specs):
      if resnet_spec[0] == 'bottleneck3d':
        block_fn = nn_blocks_3d.BottleneckBlock3D
      else:
        raise ValueError('Block fn `{}` is not supported.'.format(
            resnet_spec[0]))

      use_self_gating = (
          self._use_self_gating[i] if self._use_self_gating else False)
      self._blocks[f'res_{i+2}'] = self._build_block_group(
          inputs=inputs,
          filters=resnet_spec[1],
          temporal_kernel_sizes=self._temporal_kernel_sizes[i],
          temporal_strides=self._temporal_strides[i],
          spatial_strides=(1 if i == 0 else 2),

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/const_cl/modeling/backbones/resnet_3d.py:145 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/0e7a2bfc5d1d79ba. Report an issue: GitHub.