tensorflow/models · error · ValueError
Setting `diff_q_and_kv_attention_layer_norm` to Truewhen `no
Error message
Setting `diff_q_and_kv_attention_layer_norm` to Truewhen `norm_first` is False is invalid.
What it means
Error "Setting `diff_q_and_kv_attention_layer_norm` to Truewhen `norm_first` is False is invalid." thrown in tensorflow/models.
Source
Thrown at official/projects/lra/linformer_encoder_block.py:173
self._inner_dropout = inner_dropout
self._use_query_residual = use_query_residual
self._key_dim = key_dim
self._value_dim = value_dim
self._output_last_dim = output_last_dim
self._diff_q_kv_att_layer_norm = diff_q_kv_att_layer_norm
self._return_attention_scores = return_attention_scores
if attention_initializer:
self._attention_initializer = tf_keras.initializers.get(
attention_initializer
)
else:
self._attention_initializer = tf_utils.clone_initializer(
self._kernel_initializer
)
self._attention_axes = attention_axes
if self._diff_q_kv_att_layer_norm and not self._norm_first:
raise ValueError(
"Setting `diff_q_and_kv_attention_layer_norm` to True"
"when `norm_first` is False is invalid."
)
def build(self, input_shape):
if isinstance(input_shape, tf.TensorShape):
input_tensor_shape = input_shape
elif isinstance(input_shape, (list, tuple)):
input_tensor_shape = tf.TensorShape(input_shape[0])
else:
raise ValueError(
"The type of input shape argument is not supported, got: %s"
% type(input_shape)
)
einsum_equation = "abc,cd->abd"
if len(input_tensor_shape.as_list()) > 3:
einsum_equation = "...bc,cd->...bd"
hidden_size = input_tensor_shape[-1]View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/lra/linformer_encoder_block.py:173 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/88aca33f46fa729f.
Report an issue: GitHub.