Added ANI-1ccx model with a similar loader to Builtins. (#167)

* Added ANI-1ccx model with a similar loader to Builtins.

* Apply suggestions from code review
Co-Authored-By: LeanAndMean <40122815+LeanAndMean@users.noreply.github.com>

* Fixed linter errors.

torchani/neurochem/__init__.py

@@ -259,8 +259,16 @@ def load_model_ensemble(species, prefix, count):
     return Ensemble(models)
 
 
-class Builtins:
-    """Container for all builtin stuffs.
+class BuiltinsAbstract:
+    """Base class for loading ANI neural network from configuration files.
+
+    Arguments:
+        parent_name (:class:`str`): Base path that other paths are relative to.
+        const_file_path (:class:`str`): Path to constant file for ANI model(s).
+        sae_file_path (:class:`str`): Path to sae file for ANI model(s).
+        ensemble_size (:class:`int`): Number of models in model ensemble.
+        ensemble_prefix_path (:class:`str`): Path to prefix of directories of
+            models.
 
     Attributes:
         const_file (:class:`str`): Path to the builtin constant file.
@@ -275,28 +283,96 @@ class Builtins:
         ensemble_prefix (:class:`str`): Prefix of directories of models.
         models (:class:`torchani.Ensemble`): Ensemble of models.
     """
-
-    def __init__(self):
-        parent_name = '.'.join(__name__.split('.')[:-1])
+    def __init__(
+            self,
+            parent_name,
+            const_file_path,
+            sae_file_path,
+            ensemble_size,
+            ensemble_prefix_path):
         self.const_file = pkg_resources.resource_filename(
             parent_name,
-            'resources/ani-1x_dft_x8ens/rHCNO-5.2R_16-3.5A_a4-8.params')
+            const_file_path)
         self.consts = Constants(self.const_file)
         self.species = self.consts.species
         self.aev_computer = AEVComputer(**self.consts)
-
         self.sae_file = pkg_resources.resource_filename(
-            parent_name, 'resources/ani-1x_dft_x8ens/sae_linfit.dat')
+            parent_name,
+            sae_file_path)
         self.energy_shifter = load_sae(self.sae_file)
-
-        self.ensemble_size = 8
+        self.ensemble_size = ensemble_size
         self.ensemble_prefix = pkg_resources.resource_filename(
-            parent_name, 'resources/ani-1x_dft_x8ens/train')
+            parent_name,
+            ensemble_prefix_path)
         self.models = load_model_ensemble(self.consts.species,
                                           self.ensemble_prefix,
                                           self.ensemble_size)
 
 
+class Builtins(BuiltinsAbstract):
+    """Container for the builtin ANI-1x model.
+
+    Attributes:
+        const_file (:class:`str`): Path to the builtin constant file.
+        consts (:class:`Constants`): Constants loaded from builtin constant
+            file.
+        aev_computer (:class:`torchani.AEVComputer`): AEV computer with builtin
+            constants.
+        sae_file (:class:`str`): Path to the builtin self atomic energy file.
+        energy_shifter (:class:`torchani.EnergyShifter`): AEV computer with
+            builtin constants.
+        ensemble_size (:class:`int`): Number of models in model ensemble.
+        ensemble_prefix (:class:`str`): Prefix of directories of models.
+        models (:class:`torchani.Ensemble`): Ensemble of models.
+    """
+    def __init__(self):
+        parent_name = '.'.join(__name__.split('.')[:-1])
+        const_file_path = 'resources/ani-1x_dft_x8ens'\
+            '/rHCNO-5.2R_16-3.5A_a4-8.params'
+        sae_file_path = 'resources/ani-1x_dft_x8ens/sae_linfit.dat'
+        ensemble_size = 8
+        ensemble_prefix_path = 'resources/ani-1x_dft_x8ens/train'
+        super(Builtins, self).__init__(
+            parent_name,
+            const_file_path,
+            sae_file_path,
+            ensemble_size,
+            ensemble_prefix_path
+        )
+
+
+class BuiltinsANI1CCX(BuiltinsAbstract):
+    """Container for the builtin ANI-1ccx model.
+
+    Attributes:
+        const_file (:class:`str`): Path to the builtin constant file.
+        consts (:class:`Constants`): Constants loaded from builtin constant
+            file.
+        aev_computer (:class:`torchani.AEVComputer`): AEV computer with builtin
+            constants.
+        sae_file (:class:`str`): Path to the builtin self atomic energy file.
+        energy_shifter (:class:`torchani.EnergyShifter`): AEV computer with
+            builtin constants.
+        ensemble_size (:class:`int`): Number of models in model ensemble.
+        ensemble_prefix (:class:`str`): Prefix of directories of models.
+        models (:class:`torchani.Ensemble`): Ensemble of models.
+    """
+    def __init__(self):
+        parent_name = '.'.join(__name__.split('.')[:-1])
+        const_file_path = 'resources/ani-1ccx_8x'\
+            '/rHCNO-5.2R_16-3.5A_a4-8.params'
+        sae_file_path = 'resources/ani-1ccx_8x/sae_linfit.dat'
+        ensemble_size = 8
+        ensemble_prefix_path = 'resources/ani-1ccx_8x/train'
+        super(BuiltinsANI1CCX, self).__init__(
+            parent_name,
+            const_file_path,
+            sae_file_path,
+            ensemble_size,
+            ensemble_prefix_path
+        )
+
+
 def hartree2kcal(x):
     return 627.509 * x
 

torchani/resources/ani-1ccx_8x/rHCNO-5.2R_16-3.5A_a4-8.params

+TM = 1
+Rcr = 5.2000e+00
+Rca = 3.5000e+00
+EtaR = [1.6000000e+01]
+ShfR = [9.0000000e-01,1.1687500e+00,1.4375000e+00,1.7062500e+00,1.9750000e+00,2.2437500e+00,2.5125000e+00,2.7812500e+00,3.0500000e+00,3.3187500e+00,3.5875000e+00,3.8562500e+00,4.1250000e+00,4.3937500e+00,4.6625000e+00,4.9312500e+00]
+Zeta = [3.2000000e+01]
+ShfZ = [1.9634954e-01,5.8904862e-01,9.8174770e-01,1.3744468e+00,1.7671459e+00,2.1598449e+00,2.5525440e+00,2.9452431e+00]
+EtaA = [8.0000000e+00]
+ShfA = [9.0000000e-01,1.5500000e+00,2.2000000e+00,2.8500000e+00]
+Atyp = [H,C,N,O]

torchani/resources/ani-1ccx_8x/sae_linfit.dat

+H,0=-0.5991501324919538
+C,1=-38.03750806057356
+N,2=-54.67448347695333
+O,3=-75.16043537275567

torchani/resources/ani-1ccx_8x/train0/inputtrain.ipt

+!InputFile for Force Prediction Network
+sflparamsfile=rHCNO-5.2R_16-3.5A_a4-8.params
+ntwkStoreDir=networks/
+atomEnergyFile=sae_linfit.dat
+nmax=0! Maximum number of iterations (0 = inf)
+tolr=200! Tolerance - early stopping
+emult=0.5!Multiplier by eta after tol switch
+eta=0.001! Eta -- Learning rate
+tcrit=1.0E-6! Eta termination criterion
+tmax=0! Maximum time (0 = inf)
+tbtchsz=2560
+vbtchsz=2560
+gpuid=0
+ntwshr=0
+nkde=2
+energy=1
+freezelayer=0,2
+force=0
+fmult=0.0
+pbc=0
+cmult =0.001
+runtype=ANNP_CREATE_HDNN_AND_TRAIN!Create and train a HDN network
+network_setup {
+  inputsize=384;
+  atom_net H $
+    layer [
+          nodes=160;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.0001;
+    ]
+    layer [
+          nodes=128;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.00001;
+    ]
+    layer [
+          nodes=96;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.000001;
+    ]
+    layer [
+          nodes=1;
+          activation=6;
+          type=0;
+    ]
+    $
+  atom_net C $
+    layer [
+          nodes=144;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.0001;
+    ]
+    layer [
+          nodes=112;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.00001;
+    ]
+    layer [
+          nodes=96;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.000001;
+    ]
+    layer [
+          nodes=1;
+          activation=6;
+          type=0;
+    ]
+    $
+  atom_net N $
+    layer [
+          nodes=128;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.0001;
+    ]
+    layer [
+          nodes=112;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.00001;
+    ]
+    layer [
+          nodes=96;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.000001;
+    ]
+    layer [
+          nodes=1;
+          activation=6;
+          type=0;
+    ]
+    $
+  atom_net O $
+    layer [
+          nodes=128;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.0001;
+    ]
+    layer [
+          nodes=112;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.00001;
+    ]
+    layer [
+          nodes=96;
+          activation=9;
+          type=0;
+          l2norm=1;
+          l2valu=0.000001;
+    ]
+    layer [
+          nodes=1;
+          activation=6;
+          type=0;
+    ]
+    $
+
+}
+adptlrn=OFF ! Adaptive learning (OFF,RMSPROP)
+decrate=0.9 !Decay rate of RMSPROP
+moment=ADAM! Turn on momentum or nesterov momentum (OFF,CNSTTEMP,TMANNEAL,REGULAR,NESTEROV)
+mu=0.99 ! Mu factor for momentum
+

torchani/resources/ani-1ccx_8x/train0/networks/ANN-C.nnf-l4.bparam

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torchani/resources/ani-1ccx_8x/train0/networks/ANN-C.nnf-l4.wparam

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