update examples

examples/active_learning_qe/allegro_train_input/train/input.yaml

@@ -0,0 +1,60 @@
+root: results/spinel
+run_name: run
+seed: 123
+dataset_seed: 456
+
+# network
+num_basis: 8
+BesselBasis_trainable: true
+PolynomialCutoff_p: 6
+l_max: 1
+r_max: 8.0
+parity: o3_full
+num_layers: 2
+# num_features: 16
+
+env_embed_multiplicity: 16
+embed_initial_edge: true
+two_body_latent_mlp_latent_dimensions: [32, 64]
+two_body_latent_mlp_nonlinearity: silu
+latent_mlp_latent_dimensions: [64, 64]
+latent_mlp_nonlinearity: silu
+latent_mlp_initialization: uniform
+latent_resnet: true
+env_embed_mlp_latent_dimensions: []
+env_embed_mlp_nonlinearity: null
+env_embed_mlp_initialization: uniform
+edge_eng_mlp_latent_dimensions: [16]
+edge_eng_mlp_nonlinearity: null
+edge_eng_mlp_initialization: uniform
+
+model_builders:
+ - allegro.model.Allegro
+ - PerSpeciesRescale
+ - RescaleEnergyEtc
+
+
+dataset: ase
+dataset_file_name: structure.xyz
+chemical_symbols:
+  - Mg
+  - Al
+
+# logging
+wandb: false
+# verbose: debug
+
+# training
+n_train: 80%
+n_val: 20%
+batch_size: 5
+train_val_split: random
+#shuffle: true
+metrics_key: validation_loss
+use_ema: true
+ema_decay: 0.99
+ema_use_num_updates: true
+max_epochs: 100
+learning_rate: 0.01
+# loss function
+loss_coeffs: total_energy

examples/active_learning_qe/input.toml → examples/active_learning_qe/input-aenet.toml

@@ -30,10 +30,12 @@ ignore_species = []
 [train]
 type = 'aenet'
 base_input_dir = './aenet_train_input'
-exe_command = ['generate.x-2.0.4-ifort_serial', 'srun train.x-2.0.4-ifort_intelmpi']
 ignore_species = ["O"]
 vac_map = []
 restart = false
+[train.exe_command]
+generate = 'generate.x-2.0.4-ifort_serial'
+train = 'srun train.x-2.0.4-ifort_intelmpi'
 
 [config]
 unitcell = [[8.1135997772, 0.0000000000, 0.0000000000],

examples/active_learning_qe/input-mlip-3.toml

@@ -0,0 +1,123 @@
+[sampling]
+nreplicas = 8
+nprocs_per_replica = 1 
+kTstart = 600.0
+kTend = 2000.0
+nsteps = 6400 # Number of steps for sampling
+RXtrial_frequency = 4
+sample_frequency = 16
+print_frequency = 1
+reload = false
+
+[sampling.solver]
+type = 'mlip_3'
+path= 'mlp'
+base_input_dir = './baseinput'
+perturb = 0.0
+run_scheme = 'subprocess'
+ignore_species = ["O"]
+
+[mlref]
+nreplicas = 8
+ndata = 5
+
+[mlref.solver]
+type = 'qe'
+base_input_dir = './baseinput_ref'
+perturb = 0.05
+ignore_species = []
+
+[train]
+type = 'mlip_3'
+base_input_dir = './mlip-3_train_input'
+ignore_species = ["O"]
+vac_map = []
+restart = false
+[train.exe_command]
+train = 'mlp'
+
+[config]
+unitcell = [[8.1135997772, 0.0000000000, 0.0000000000],
+            [0.0000000000, 8.1135997772, 0.0000000000],
+            [0.0000000000, 0.0000000000, 8.1135997772]]
+supercell = [1,1,1]
+
+[[config.base_structure]]
+type = "O"
+coords = [
+     [0.237399980, 0.237399980, 0.237399980],
+     [0.762599945, 0.762599945, 0.762599945],
+     [0.512599945, 0.012600004, 0.737399936],
+     [0.487399966, 0.987399936, 0.262599975],
+     [0.012600004, 0.737399936, 0.512599945],
+     [0.987399936, 0.262599975, 0.487399966],
+     [0.737399936, 0.512599945, 0.012600004],
+     [0.262599975, 0.487399966, 0.987399936],
+     [0.987399936, 0.487399966, 0.262599975],
+     [0.012600004, 0.512599945, 0.737399936],
+     [0.487399966, 0.262599975, 0.987399936],
+     [0.512599945, 0.737399936, 0.012600004],
+     [0.262599975, 0.987399936, 0.487399966],
+     [0.737399936, 0.012600004, 0.512599945],
+     [0.237399980, 0.737399936, 0.737399936],
+     [0.762599945, 0.262599975, 0.262599975],
+     [0.512599945, 0.512599945, 0.237399980],
+     [0.487399966, 0.487399966, 0.762599945],
+     [0.012600004, 0.237399980, 0.012600004],
+     [0.987399936, 0.762599945, 0.987399936],
+     [0.987399936, 0.987399936, 0.762599945],
+     [0.012600004, 0.012600004, 0.237399980],
+     [0.487399966, 0.762599945, 0.487399966],
+     [0.512599945, 0.237399980, 0.512599945],
+     [0.737399936, 0.237399980, 0.737399936],
+     [0.262599975, 0.762599945, 0.262599975],
+     [0.237399980, 0.512599945, 0.512599945],
+     [0.762599945, 0.487399966, 0.487399966],
+     [0.762599945, 0.987399936, 0.987399936],
+     [0.237399980, 0.012600004, 0.012600004],
+     [0.737399936, 0.737399936, 0.237399980],
+     [0.262599975, 0.262599975, 0.762599945],
+     ]
+
+[[config.defect_structure]]
+coords = [
+     [0.000000000, 0.000000000, 0.000000000],
+     [0.749999940, 0.249999985, 0.499999970],
+     [0.249999985, 0.749999940, 0.499999970],
+     [0.249999985, 0.499999970, 0.749999940],
+     [0.749999940, 0.499999970, 0.249999985],
+     [0.499999970, 0.749999940, 0.249999985],
+     [0.499999970, 0.249999985, 0.749999940],
+     [0.000000000, 0.499999970, 0.499999970],
+     [0.749999940, 0.749999940, 0.000000000],
+     [0.249999985, 0.249999985, 0.000000000],
+     [0.249999985, 0.000000000, 0.249999985],
+     [0.749999940, 0.000000000, 0.749999940],
+     [0.499999970, 0.000000000, 0.499999970],
+     [0.000000000, 0.749999940, 0.749999940],
+     [0.000000000, 0.249999985, 0.249999985],
+     [0.499999970, 0.499999970, 0.000000000],
+     [0.374999970, 0.374999970, 0.374999970],
+     [0.624999940, 0.624999940, 0.624999940],
+     [0.374999970, 0.874999940, 0.874999940],
+     [0.624999940, 0.124999993, 0.124999993],
+     [0.874999940, 0.874999940, 0.374999970],
+     [0.124999993, 0.124999993, 0.624999940],
+     [0.874999940, 0.374999970, 0.874999940],
+     [0.124999993, 0.624999940, 0.124999993],
+     ]
+[[config.defect_structure.groups]]
+name = 'Al'
+# species = ['Al']    # default
+# coords = [[[0,0,0]]]  # default
+num = 16 #432 #16000
+[[config.defect_structure.groups]]
+name = 'Mg'
+# species = ['Mg']    # default
+# coords = [[[0,0,0]]]  # default
+num = 8 #216 #8000
+
+
+[observer]
+reference_structure = "MgAl2O4.vasp"
+ignored_species = ["Al", "O"]

examples/active_learning_qe/input-nequip.toml

@@ -0,0 +1,121 @@
+[sampling]
+nreplicas = 8
+nprocs_per_replica = 1 
+kTstart = 600.0
+kTend = 2000.0
+nsteps = 6400 # Number of steps for sampling
+RXtrial_frequency = 4
+sample_frequency = 16
+print_frequency = 1
+reload = false
+
+[sampling.solver]
+type = 'nequip'
+base_input_dir = './baseinput'
+perturb = 0.0
+ignore_species = ["O"]
+
+[mlref]
+nreplicas = 8
+ndata = 5
+
+[mlref.solver]
+type = 'qe'
+base_input_dir = './baseinput_ref'
+perturb = 0.05
+ignore_species = []
+
+[train]
+type = 'nequip'
+base_input_dir = './allegro_train_input'
+ignore_species = ["O"]
+vac_map = []
+restart = false
+[train.exe_command]
+train = 'nequip-train'
+
+[config]
+unitcell = [[8.1135997772, 0.0000000000, 0.0000000000],
+            [0.0000000000, 8.1135997772, 0.0000000000],
+            [0.0000000000, 0.0000000000, 8.1135997772]]
+supercell = [1,1,1]
+
+[[config.base_structure]]
+type = "O"
+coords = [
+     [0.237399980, 0.237399980, 0.237399980],
+     [0.762599945, 0.762599945, 0.762599945],
+     [0.512599945, 0.012600004, 0.737399936],
+     [0.487399966, 0.987399936, 0.262599975],
+     [0.012600004, 0.737399936, 0.512599945],
+     [0.987399936, 0.262599975, 0.487399966],
+     [0.737399936, 0.512599945, 0.012600004],
+     [0.262599975, 0.487399966, 0.987399936],
+     [0.987399936, 0.487399966, 0.262599975],
+     [0.012600004, 0.512599945, 0.737399936],
+     [0.487399966, 0.262599975, 0.987399936],
+     [0.512599945, 0.737399936, 0.012600004],
+     [0.262599975, 0.987399936, 0.487399966],
+     [0.737399936, 0.012600004, 0.512599945],
+     [0.237399980, 0.737399936, 0.737399936],
+     [0.762599945, 0.262599975, 0.262599975],
+     [0.512599945, 0.512599945, 0.237399980],
+     [0.487399966, 0.487399966, 0.762599945],
+     [0.012600004, 0.237399980, 0.012600004],
+     [0.987399936, 0.762599945, 0.987399936],
+     [0.987399936, 0.987399936, 0.762599945],
+     [0.012600004, 0.012600004, 0.237399980],
+     [0.487399966, 0.762599945, 0.487399966],
+     [0.512599945, 0.237399980, 0.512599945],
+     [0.737399936, 0.237399980, 0.737399936],
+     [0.262599975, 0.762599945, 0.262599975],
+     [0.237399980, 0.512599945, 0.512599945],
+     [0.762599945, 0.487399966, 0.487399966],
+     [0.762599945, 0.987399936, 0.987399936],
+     [0.237399980, 0.012600004, 0.012600004],
+     [0.737399936, 0.737399936, 0.237399980],
+     [0.262599975, 0.262599975, 0.762599945],
+     ]
+
+[[config.defect_structure]]
+coords = [
+     [0.000000000, 0.000000000, 0.000000000],
+     [0.749999940, 0.249999985, 0.499999970],
+     [0.249999985, 0.749999940, 0.499999970],
+     [0.249999985, 0.499999970, 0.749999940],
+     [0.749999940, 0.499999970, 0.249999985],
+     [0.499999970, 0.749999940, 0.249999985],
+     [0.499999970, 0.249999985, 0.749999940],
+     [0.000000000, 0.499999970, 0.499999970],
+     [0.749999940, 0.749999940, 0.000000000],
+     [0.249999985, 0.249999985, 0.000000000],
+     [0.249999985, 0.000000000, 0.249999985],
+     [0.749999940, 0.000000000, 0.749999940],
+     [0.499999970, 0.000000000, 0.499999970],
+     [0.000000000, 0.749999940, 0.749999940],
+     [0.000000000, 0.249999985, 0.249999985],
+     [0.499999970, 0.499999970, 0.000000000],
+     [0.374999970, 0.374999970, 0.374999970],
+     [0.624999940, 0.624999940, 0.624999940],
+     [0.374999970, 0.874999940, 0.874999940],
+     [0.624999940, 0.124999993, 0.124999993],
+     [0.874999940, 0.874999940, 0.374999970],
+     [0.124999993, 0.124999993, 0.624999940],
+     [0.874999940, 0.374999970, 0.874999940],
+     [0.124999993, 0.624999940, 0.124999993],
+     ]
+[[config.defect_structure.groups]]
+name = 'Al'
+# species = ['Al']    # default
+# coords = [[[0,0,0]]]  # default
+num = 16 #432 #16000
+[[config.defect_structure.groups]]
+name = 'Mg'
+# species = ['Mg']    # default
+# coords = [[[0,0,0]]]  # default
+num = 8 #216 #8000
+
+
+[observer]
+reference_structure = "MgAl2O4.vasp"
+ignored_species = ["Al", "O"]

examples/active_learning_qe/mlip-3_train_input/train/input.almtp

@@ -0,0 +1,17 @@
+MTP
+version = 1.1.0
+potential_name = MTP1m
+species_count = 3
+potential_tag =
+radial_basis_type = RBChebyshev
+ min_dist = 2.3
+     max_dist = 5
+     radial_basis_size = 8
+     radial_funcs_count = 2
+alpha_moments_count = 8
+alpha_index_basic_count = 5
+alpha_index_basic = {{0, 0, 0, 0}, {0, 1, 0, 0}, {0, 0, 1, 0}, {0, 0, 0, 1}, {1, 0, 0, 0}}
+alpha_index_times_count = 5
+alpha_index_times = {{0, 0, 1, 5}, {1, 1, 1, 6}, {2, 2, 1, 6}, {3, 3, 1, 6}, {0, 5, 1, 7}}
+alpha_scalar_moments = 5
+alpha_moment_mapping = {0, 4, 5, 6, 7}

examples/active_learning_qe_lammps/input.toml

@@ -30,10 +30,12 @@ ignore_species = []
 [train]
 type = 'aenet'
 base_input_dir = './aenet_train_input'
-exe_command = ['generate.x-2.0.4-ifort_serial', 'srun train.x-2.0.4-ifort_intelmpi']
 ignore_species = ["O"]
 vac_map = []
 restart = false
+[train.exe_command]
+generate = 'generate.x-2.0.4-ifort_serial'
+train = 'srun train.x-2.0.4-ifort_intelmpi'
 
 [config]
 unitcell = [[8.1135997772, 0.0000000000, 0.0000000000],

examples/active_learning_vasp/input.toml

@@ -31,10 +31,12 @@ ignore_species = []
 [train]
 type = 'aenet'
 base_input_dir = './aenet_train_input'
-exe_command = ['generate.x-2.0.4-ifort_serial', 'srun train.x-2.0.4-ifort_intelmpi']
 ignore_species = ["O"]
 vac_map = []
 restart = false
+[train.exe_command]
+generate = 'generate.x-2.0.4-ifort_serial'
+train = 'srun train.x-2.0.4-ifort_intelmpi'
 
 [config]
 unitcell = [[8.1135997772, 0.0000000000, 0.0000000000],