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config.json

@@ -2,6 +2,10 @@
   "architectures": [
     "TransmxmModel"
   ],
+  "auto_map": {
+    "AutoConfig": "configuration_transmxm.TransmxmConfig",
+    "AutoModel": "modeling_transmxm.TransmxmModel"
+  },
   "cutoff": 5.0,
   "dim": 128,
   "envelope_exponent": 5,

modeling_transmxm.py

@@ -23,7 +23,7 @@ from torch_scatter import scatter
 from torch_geometric.nn import global_add_pool, radius
 from torch_sparse import SparseTensor
 
-# from transmxm_model.configuration_transmxm import TransmxmConfig
+from transmxm_model.configuration_transmxm import TransmxmConfig
 
 from tqdm import tqdm
 import numpy as np
@@ -1171,35 +1171,35 @@ class Local_MP(torch.nn.Module):
         return h, y
 
 
-class TransmxmConfig(PretrainedConfig):
-    model_type = "transmxm"
-
-    def __init__(
-        self,
-        dim: int=128,
-        n_layer: int=6,
-        cutoff: float=5.0,
-        num_spherical: int=7,
-        num_radial: int=6,
-        envelope_exponent: int=5,
-
-        smiles: List[str] = None,
-        processor_class: str = "SmilesProcessor",
-        **kwargs,
-    ):
-
-        self.dim = dim                                    # the dimension of input feature
-        self.n_layer = n_layer                            # the number of GCN layers
-        self.cutoff = cutoff                              # the cutoff distance for neighbor searching
-        self.num_spherical = num_spherical                # the number of spherical harmonics
-        self.num_radial = num_radial                         # the number of radial basis
-        self.envelope_exponent = envelope_exponent             # the envelope exponent
-
-        self.smiles = smiles                      # process smiles
-        self.processor_class = processor_class
-
-
-        super().__init__(**kwargs)
+# class MXMConfig(PretrainedConfig):
+#     model_type = "gcn"
+#
+#     def __init__(
+#         self,
+#         dim: int=128,
+#         n_layer: int=6,
+#         cutoff: float=5.0,
+#         num_spherical: int=7,
+#         num_radial: int=6,
+#         envelope_exponent: int=5,
+#
+#         smiles: List[str] = None,
+#         processor_class: str = "SmilesProcessor",
+#         **kwargs,
+#     ):
+#
+#         self.dim = dim                                    # the dimension of input feature
+#         self.n_layer = n_layer                            # the number of GCN layers
+#         self.cutoff = cutoff                              # the cutoff distance for neighbor searching
+#         self.num_spherical = num_spherical                # the number of spherical harmonics
+#         self.num_radial = num_radial                         # the number of radial basis
+#         self.envelope_exponent = envelope_exponent             # the envelope exponent
+#
+#         self.smiles = smiles                      # process smiles
+#         self.processor_class = processor_class
+#
+#
+#         super().__init__(**kwargs)