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Add hop-prioritized graph transformer sequences #759

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Add hop-prioritized graph transformer sequences #759

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11 changes: 11 additions & 0 deletions gigl/nn/graph_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1122,6 +1122,9 @@ class GraphTransformerEncoder(nn.Module):
when ``sequence_construction_method="khop"``. Directed relative
encodings such as ``"hop_distance"`` should be computed with the
same direction.
prioritize_hop_order: If True, k-hop sequence construction fills tokens
by hop depth before truncating to ``max_seq_len``. The default False
preserves existing homogeneous-node-id ordering.
feature_embedding_layer_dict: Optional ModuleDict mapping node types to
feature embedding layers. If provided, these are applied to node
features before node projection. (default: None)
Expand Down Expand Up @@ -1213,6 +1216,7 @@ def __init__(
anchor_based_input_embedding_dict: Optional[nn.ModuleDict] = None,
pairwise_attention_bias_attr_names: Optional[list[str]] = None,
sampling_direction: Literal["in", "out"] = "out",
prioritize_hop_order: bool = False,
feature_embedding_layer_dict: Optional[nn.ModuleDict] = None,
pe_integration_mode: Literal["concat", "add"] = "concat",
activation: str = "gelu",
Expand Down Expand Up @@ -1264,6 +1268,11 @@ def __init__(
"sequence_construction_method='ppr' supports only "
"sampling_direction='out'."
)
if prioritize_hop_order and sequence_construction_method != "khop":
raise ValueError(
"prioritize_hop_order=True is supported only with "
"sequence_construction_method='khop'."
)
if sequence_positional_encoding_type is not None:
sequence_positional_encoding_type = (
sequence_positional_encoding_type.lower()
Expand Down Expand Up @@ -1333,6 +1342,7 @@ def __init__(
)
self._sequence_construction_method = sequence_construction_method
self._sampling_direction = sampling_direction
self._prioritize_hop_order = prioritize_hop_order
self._sequence_positional_encoding_type = sequence_positional_encoding_type
self._should_l2_normalize_embedding_layer_output = (
should_l2_normalize_embedding_layer_output
Expand Down Expand Up @@ -1598,6 +1608,7 @@ def forward(
hop_distance=self._hop_distance,
sequence_construction_method=self._sequence_construction_method,
sampling_direction=self._sampling_direction,
prioritize_hop_order=self._prioritize_hop_order,
anchor_based_attention_bias_attr_names=self._anchor_based_attention_bias_attr_names,
anchor_based_input_attr_names=self._anchor_based_input_attr_names,
pairwise_attention_bias_attr_names=self._pairwise_attention_bias_attr_names,
Expand Down
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