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Fix AllSet instantiation with default activation #378

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Merged
flovertiq merged 2 commits into from
Aug 25, 2026
Merged

Fix AllSet instantiation with default activation #378

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5ebe94d
Fix AllSet instantiation with default activation
flovertiq Aug 24, 2026
8b99f8f
Update AllSet mlp_activation docstring default/type
Copilot Aug 25, 2026
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4 changes: 2 additions & 2 deletions topomodelx/nn/hypergraph/allset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ class AllSet(torch.nn.Module):
Dropout probability for the AllSet layer.
mlp_num_layers : int, default = 2
Number of layers in the MLP.
mlp_activation : torch.nn.Module, default = None
mlp_activation : callable | None, default = torch.nn.ReLU
Activation function in the MLP.
mlp_dropout : float, default = 0.0
Dropout probability for the MLP.
Expand All @@ -46,7 +46,7 @@ def __init__(
n_layers=2,
layer_dropout=0.2,
mlp_num_layers=2,
mlp_activation=None,
mlp_activation=torch.nn.ReLU,

Copilot AI Aug 25, 2026

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Fixed in commit 8b99f8f by updating the mlp_activation docstring to callable | None with default torch.nn.ReLU.

mlp_dropout=0.0,
mlp_norm=None,
**kwargs,
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3 changes: 2 additions & 1 deletion topomodelx/nn/hypergraph/allset_layer.py
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Expand Up @@ -175,7 +175,8 @@ def __init__(
layers.append(nn.Linear(in_dim, hidden_dim, bias=bias))
if norm_layer is not None:
layers.append(norm_layer(hidden_dim))
layers.append(activation_layer(**params))
if activation_layer is not None:
layers.append(activation_layer(**params))
layers.append(nn.Dropout(dropout, **params))
in_dim = hidden_dim

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5 changes: 3 additions & 2 deletions topomodelx/nn/hypergraph/allset_transformer_layer.py
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Expand Up @@ -191,7 +191,7 @@ def __init__(
number_queries: int = 1,
dropout: float = 0.0,
mlp_num_layers: int = 1,
mlp_activation=None,
mlp_activation=nn.ReLU,
mlp_dropout: float = 0.0,
mlp_norm=None,
initialization: Literal["xavier_uniform", "xavier_normal"] = "xavier_uniform",
Expand Down Expand Up @@ -455,7 +455,8 @@ def __init__(
layers.append(nn.Linear(in_dim, hidden_dim, bias=bias))
if norm_layer is not None:
layers.append(norm_layer(hidden_dim))
layers.append(activation_layer(**params))
if activation_layer is not None:
layers.append(activation_layer(**params))
layers.append(nn.Dropout(dropout, **params))
in_dim = hidden_dim

Expand Down