added missing sevennet initial config

resources/models/sevennet/sevennet-initial-model.py

@@ -17,7 +17,7 @@ def get_statistics(filename='../../data/alexandria+mptraj-statistics.json'):
     return statistics
 
 
-def get_config(filename='input.yaml'):
+def get_config(filename='sevennet-initial-model.yaml'):
     print(f'Reading initial config from `{filename}`')
 
     statistics = get_statistics()

resources/models/sevennet/sevennet-initial-model.yaml

@@ -0,0 +1,80 @@
+# SevenNet-0, should be run with `sevenn -m train_v1` as it uses old routine
+model:
+    chemical_species: 'auto'
+    cutoff: 5.0
+    channel: 128
+    is_parity: False
+    lmax: 2
+    num_convolution_layer: 5
+    irreps_manual:
+        - "128x0e"
+        - "128x0e+64x1e+32x2e"
+        - "128x0e+64x1e+32x2e"
+        - "128x0e+64x1e+32x2e"
+        - "128x0e+64x1e+32x2e"
+        - "128x0e"
+
+    weight_nn_hidden_neurons: [64, 64]
+    radial_basis:
+        radial_basis_name: 'bessel'
+        bessel_basis_num: 8
+    cutoff_function:
+        cutoff_function_name: 'XPLOR'
+        cutoff_on: 4.5
+
+    act_gate: {'e': 'silu', 'o': 'tanh'}
+    act_scalar: {'e': 'silu', 'o': 'tanh'}
+
+    conv_denominator: 'avg_num_neigh'
+    train_shift_scale: False
+    train_denominator: False
+    self_connection_type: 'linear'
+train:
+    train_shuffle: False
+    random_seed: 1
+    is_train_stress : True
+    epoch: 600
+
+    loss: 'Huber'
+    loss_param:
+        delta: 0.01
+
+    optimizer: 'adam'
+    optim_param:
+        lr: 0.01
+    scheduler: 'linearlr'
+    scheduler_param:
+        start_factor: 1.0
+        total_iters: 600
+        end_factor: 0.0001
+
+    force_loss_weight : 1.00
+    stress_loss_weight: 0.01
+
+    error_record:
+        - ['Energy', 'RMSE']
+        - ['Force', 'RMSE']
+        - ['Stress', 'RMSE']
+        - ['Energy', 'MAE']
+        - ['Force', 'MAE']
+        - ['Stress', 'MAE']
+        - ['Energy', 'Loss']
+        - ['Force', 'Loss']
+        - ['Stress', 'Loss']
+        - ['TotalLoss', 'None']
+
+    per_epoch: 10
+    # continue:
+    #    checkpoint: './checkpoint_last.pth'
+    #    reset_optimizer: False
+    #    reset_scheduler: False
+data:
+    batch_size: 128  # per GPU batch size, as the model trained with 32 GPUs, the effective batch size equals 4096.
+    scale: 'per_atom_energy_std'
+    shift: 'elemwise_reference_energies'
+
+    data_format: 'ase'
+    save_by_train_valid: False
+    #load_dataset_path: ["path_to_MPtrj_total.sevenn_data"]
+    #load_validset_path: ["validaset.sevenn_data"]
+