tensorflow/models · error · ValueError
Requested downsampling at a non-existing starting depthwise
Error message
Requested downsampling at a non-existing starting depthwise conv.
What it means
Error "Requested downsampling at a non-existing starting depthwise conv." thrown in tensorflow/models.
Source
Thrown at official/projects/qat/vision/modeling/layers/nn_blocks.py:841
self._use_residual = use_residual
self._activation = activation
self._depthwise_activation = depthwise_activation
self._kernel_initializer = kernel_initializer
self._use_layer_scale = use_layer_scale
self._layer_scale_init_value = layer_scale_init_value
self._norm_momentum = norm_momentum
self._norm_epsilon = norm_epsilon
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._output_intermediate_endpoints = output_intermediate_endpoints
if strides > 1:
if middle_dw_downsample and not middle_dw_kernel_size:
raise ValueError(
'Requested downsampling at a non-existing middle depthwise conv.'
)
if not middle_dw_downsample and not start_dw_kernel_size:
raise ValueError(
'Requested downsampling at a non-existing starting depthwise conv.'
)
if use_sync_bn:
norm_layer = tf_keras.layers.experimental.SyncBatchNormalization
else:
norm_layer = tf_keras.layers.BatchNormalization
self._norm_with_quantize = helper.BatchNormalizationQuantized(norm_layer)
self._norm = helper.BatchNormalizationNoQuantized(norm_layer)
if tf_keras.backend.image_data_format() == 'channels_last':
self._bn_axis = -1
else:
self._bn_axis = 1
if not depthwise_activation:
self._depthwise_activation = activation
if regularize_depthwise:
self._depthwise_regularizer = kernel_regularizerView on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/qat/vision/modeling/layers/nn_blocks.py:841 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/824d8cdc8dca479d.
Report an issue: GitHub.