default resnet: False

mir-group · Jan 19, 2022 · b44ef02 · b44ef02
1 parent ea91cab
commit b44ef02
Show file tree

Hide file tree

Showing 7 changed files with 5 additions and 7 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -14,6 +14,7 @@ Most recent change on the bottom.
 
 ### Changed
 - `minimal.yaml`, `minimal_eng.yaml`, and `example.yaml` now use the simplified irreps options `l_max`, `parity`, and `num_features`
+- Default value for `resnet` is now `False`
 
 ### Fixed
 - Handle one of `per_species_shifts`/`scales` being `null` when the other is a dataset statistc

diff --git a/configs/example.yaml b/configs/example.yaml
@@ -18,7 +18,6 @@ l_max: 1
 parity: true                                                                      # whether to include features with odd mirror parity
 num_features: 32                                                                  # the multiplicity of the features
 nonlinearity_type: gate                                                           # may be 'gate' or 'norm', 'gate' is recommended
-resnet: false                                                                     # set true to make interaction block a resnet-style update
 
 # scalar nonlinearities to use — available options are silu, ssp (shifted softplus), tanh, and abs.
 # Different nonlinearities are specified for e (even) and o (odd) parity;

diff --git a/configs/full.yaml b/configs/full.yaml
@@ -36,6 +36,7 @@ num_features: 32
 
 nonlinearity_type: gate                                                           # may be 'gate' or 'norm', 'gate' is recommended
 resnet: false                                                                     # set true to make interaction block a resnet-style update
+                                                                                  # the resnet update will only be applied when the input and output irreps of the layer are the same
 
 # scalar nonlinearities to use — available options are silu, ssp (shifted softplus), tanh, and abs.
 # Different nonlinearities are specified for e (even) and o (odd) parity;

diff --git a/docs/options/model.rst b/docs/options/model.rst
@@ -99,7 +99,7 @@ invariant_neurons
 resnet
 ^^^^^^
     | Type: bool
-    | Default: ``True``
+    | Default: ``False``
 
 nonlinearity_type
 ^^^^^^^^^^^^^^^^^

diff --git a/nequip/nn/_convnetlayer.py b/nequip/nn/_convnetlayer.py
@@ -37,7 +37,7 @@ def __init__(
         convolution=InteractionBlock,
         convolution_kwargs: dict = {},
         num_layers: int = 3,
-        resnet: bool = True,
+        resnet: bool = False,
         nonlinearity_type: str = "gate",
         nonlinearity_scalars: Dict[int, Callable] = {"e": "ssp", "o": "tanh"},
         nonlinearity_gates: Dict[int, Callable] = {"e": "ssp", "o": "abs"},

diff --git a/nequip/nn/_interaction_block.py b/nequip/nn/_interaction_block.py
@@ -144,7 +144,7 @@ def __init__(
 
     def forward(self, data: AtomicDataDict.Type) -> AtomicDataDict.Type:
         """
-        Evaluate interaction Block with ResNet.
+        Evaluate interaction Block with ResNet (self-connection).
 
         :param node_input:
         :param node_attr:

diff --git a/tests/unit/model/test_eng_force.py b/tests/unit/model/test_eng_force.py
@@ -28,7 +28,6 @@
     irreps_edge_sh="0e + 1o",
     r_max=4,
     feature_irreps_hidden="4x0e + 4x1o",
-    resnet=True,
     num_layers=2,
     num_basis=8,
     PolynomialCutoff_p=6,
@@ -47,7 +46,6 @@
     irreps_edge_sh="0e + 1o",
     r_max=4,
     feature_irreps_hidden="4x0e + 4x1o",
-    resnet=True,
     num_layers=2,
     num_basis=8,
     PolynomialCutoff_p=6,
@@ -58,7 +56,6 @@
     irreps_edge_sh="0e + 1o + 2e",
     r_max=4,
     feature_irreps_hidden="2x0e + 2x1o + 2x2e",
-    resnet=False,
     num_layers=2,
     num_basis=3,
     PolynomialCutoff_p=6,