tensorflow/models · error · ValueError
Unrecognized ViT-3D implementation variant choice: %s
Error message
Unrecognized ViT-3D implementation variant choice: %s
What it means
Error "Unrecognized ViT-3D implementation variant choice: %s" thrown in tensorflow/models.
Source
Thrown at official/projects/videoglue/modeling/backbones/vit_3d.py:196
self._patch_size = (
self._temporal_patch_size,
self._spatial_patch_size,
self._spatial_patch_size,
)
nt = self._input_specs.shape[1] // self._temporal_patch_size
nh = self._input_specs.shape[2] // self._spatial_patch_size
nw = self._input_specs.shape[3] // self._spatial_patch_size
inputs = tf_keras.Input(shape=input_specs.shape[1:])
add_pos_embed = True
if self._variant == 'native':
x = self._tokenize(inputs)
elif self._variant == 'mae':
x = self._mae_tokenize(inputs)
# NOTE: MAE variant adds pos_embed in the tokenizer.
add_pos_embed = False
else:
raise ValueError(
'Unrecognized ViT-3D implementation variant choice: %s' %
variant)
# If we want to add a class token, add it here.
if pooler == 'token':
x = TokenLayer(name='cls')(x)
x = vit.Encoder(
num_layers=num_layers,
mlp_dim=mlp_dim,
num_heads=num_heads,
dropout_rate=dropout_rate,
attention_dropout_rate=attention_dropout_rate,
kernel_regularizer=kernel_regularizer,
kernel_initializer='glorot_uniform' if original_init else dict(
class_name='TruncatedNormal', config=dict(stddev=.02)),
init_stochastic_depth_rate=init_stochastic_depth_rate,
pos_embed_origin_shape=pos_embed_shape,View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/videoglue/modeling/backbones/vit_3d.py:196 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/a05d641a7d4f813c.
Report an issue: GitHub.