"IndexError: index out of range in self " while training

[knight-fjy]

Hello!
As a newcomer to using DeepH and trying out this tool for the first time, I've encountered a bit of a problem. During the training process with my data, I've run into an issue and received a program error: "IndexError: index out of range in self." I would be deeply appreciative if you could take a look at this problem and perhaps offer some guidance or possible solutions.

Best regards!

Graph data file: HGraph-h5-Sn4-5l-FromDFT.pkl
Use existing graph data file
Atomic types: [1, 6, 8, 50]
Finish loading the processed 3 structures (spinful: False, the number of atomic types: 4), cost 1 seconds
number of train set: 1
number of val set: 1
number of test set: 1
{'normalizer': False, 'boxcox': False}
Output features length of single edge: 361
The model you built has: 518170 parameters
Traceback (most recent call last):
File "/opt/miniconda3/bin/deeph-train", line 8, in
sys.exit(main())
File "/opt/miniconda3/lib/python3.9/site-packages/deeph/scripts/train.py", line 20, in main
kernel.train(train_loader, val_loader, test_loader)
File "/opt/miniconda3/lib/python3.9/site-packages/deeph/kernel.py", line 519, in train
val_losses = self.kernel_fn(val_loader, 'VAL')
File "/opt/miniconda3/lib/python3.9/site-packages/deeph/kernel.py", line 658, in kernel_fn
output = self.model(
File "/opt/miniconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/lib/python3.9/site-packages/deeph/model.py", line 621, in forward
atom_fea0 = self.embed(atom_attr)
File "/opt/miniconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/lib/python3.9/site-packages/torch/nn/modules/sparse.py", line 158, in forward
return F.embedding(
File "/opt/miniconda3/lib/python3.9/site-packages/torch/nn/functional.py", line 2044, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
IndexError: index out of range in self

Here's my ini:
[basic]
graph_dir = /share/3_train/result3/
save_dir = /share/3_train/result3/
raw_dir = /share/3_train/3_stru/
dataset_name = Sn4
only_get_graph = False
;choices = ['h5', 'npz']
interface = h5
target = hamiltonian
disable_cuda = False
device = cpu
;-1 for cpu_count(logical=False) // torch.cuda.device_count()
num_threads = -1
save_to_time_folder = True
save_csv = False
tb_writer = True
seed = 42
multiprocessing = 0
orbital = [{"50 50": [0, 0]}, {"50 50": [0, 1]}, {"50 50": [0, 2]}, {"50 50": [0, 3]}, {"50 50": [0, 4]}, {"50 50": [0, 5]}, {"50 50": [0, 6]}, {"50 50": [0, 7]}, {"50 50": [0, 8]}, {"50 50": [0, 9]}, {"50 50": [0, 10]}, {"50 50": [0, 11]}, {"50 50": [0, 12]}, {"50 50": [0, 13]}, {"50 50": [0, 14]}, {"50 50": [0, 15]}, {"50 50": [0, 16]}, {"50 50": [0, 17]}, {"50 50": [0, 18]}, {"50 50": [1, 0]}, {"50 50": [1, 1]}, {"50 50": [1, 2]}, {"50 50": [1, 3]}, {"50 50": [1, 4]}, {"50 50": [1, 5]}, {"50 50": [1, 6]}, {"50 50": [1, 7]}, {"50 50": [1, 8]}, {"50 50": [1, 9]}, {"50 50": [1, 10]}, {"50 50": [1, 11]}, {"50 50": [1, 12]}, {"50 50": [1, 13]}, {"50 50": [1, 14]}, {"50 50": [1, 15]}, {"50 50": [1, 16]}, {"50 50": [1, 17]}, {"50 50": [1, 18]}, {"50 50": [2, 0]}, {"50 50": [2, 1]}, {"50 50": [2, 2]}, {"50 50": [2, 3]}, {"50 50": [2, 4]}, {"50 50": [2, 5]}, {"50 50": [2, 6]}, {"50 50": [2, 7]}, {"50 50": [2, 8]}, {"50 50": [2, 9]}, {"50 50": [2, 10]}, {"50 50": [2, 11]}, {"50 50": [2, 12]}, {"50 50": [2, 13]}, {"50 50": [2, 14]}, {"50 50": [2, 15]}, {"50 50": [2, 16]}, {"50 50": [2, 17]}, {"50 50": [2, 18]}, {"50 50": [3, 0]}, {"50 50": [3, 1]}, {"50 50": [3, 2]}, {"50 50": [3, 3]}, {"50 50": [3, 4]}, {"50 50": [3, 5]}, {"50 50": [3, 6]}, {"50 50": [3, 7]}, {"50 50": [3, 8]}, {"50 50": [3, 9]}, {"50 50": [3, 10]}, {"50 50": [3, 11]}, {"50 50": [3, 12]}, {"50 50": [3, 13]}, {"50 50": [3, 14]}, {"50 50": [3, 15]}, {"50 50": [3, 16]}, {"50 50": [3, 17]}, {"50 50": [3, 18]}, {"50 50": [4, 0]}, {"50 50": [4, 1]}, {"50 50": [4, 2]}, {"50 50": [4, 3]}, {"50 50": [4, 4]}, {"50 50": [4, 5]}, {"50 50": [4, 6]}, {"50 50": [4, 7]}, {"50 50": [4, 8]}, {"50 50": [4, 9]}, {"50 50": [4, 10]}, {"50 50": [4, 11]}, {"50 50": [4, 12]}, {"50 50": [4, 13]}, {"50 50": [4, 14]}, {"50 50": [4, 15]}, {"50 50": [4, 16]}, {"50 50": [4, 17]}, {"50 50": [4, 18]}, {"50 50": [5, 0]}, {"50 50": [5, 1]}, {"50 50": [5, 2]}, {"50 50": [5, 3]}, {"50 50": [5, 4]}, {"50 50": [5, 5]}, {"50 50": [5, 6]}, {"50 50": [5, 7]}, {"50 50": [5, 8]}, {"50 50": [5, 9]}, {"50 50": [5, 10]}, {"50 50": [5, 11]}, {"50 50": [5, 12]}, {"50 50": [5, 13]}, {"50 50": [5, 14]}, {"50 50": [5, 15]}, {"50 50": [5, 16]}, {"50 50": [5, 17]}, {"50 50": [5, 18]}, {"50 50": [6, 0]}, {"50 50": [6, 1]}, {"50 50": [6, 2]}, {"50 50": [6, 3]}, {"50 50": [6, 4]}, {"50 50": [6, 5]}, {"50 50": [6, 6]}, {"50 50": [6, 7]}, {"50 50": [6, 8]}, {"50 50": [6, 9]}, {"50 50": [6, 10]}, {"50 50": [6, 11]}, {"50 50": [6, 12]}, {"50 50": [6, 13]}, {"50 50": [6, 14]}, {"50 50": [6, 15]}, {"50 50": [6, 16]}, {"50 50": [6, 17]}, {"50 50": [6, 18]}, {"50 50": [7, 0]}, {"50 50": [7, 1]}, {"50 50": [7, 2]}, {"50 50": [7, 3]}, {"50 50": [7, 4]}, {"50 50": [7, 5]}, {"50 50": [7, 6]}, {"50 50": [7, 7]}, {"50 50": [7, 8]}, {"50 50": [7, 9]}, {"50 50": [7, 10]}, {"50 50": [7, 11]}, {"50 50": [7, 12]}, {"50 50": [7, 13]}, {"50 50": [7, 14]}, {"50 50": [7, 15]}, {"50 50": [7, 16]}, {"50 50": [7, 17]}, {"50 50": [7, 18]}, {"50 50": [8, 0]}, {"50 50": [8, 1]}, {"50 50": [8, 2]}, {"50 50": [8, 3]}, {"50 50": [8, 4]}, {"50 50": [8, 5]}, {"50 50": [8, 6]}, {"50 50": [8, 7]}, {"50 50": [8, 8]}, {"50 50": [8, 9]}, {"50 50": [8, 10]}, {"50 50": [8, 11]}, {"50 50": [8, 12]}, {"50 50": [8, 13]}, {"50 50": [8, 14]}, {"50 50": [8, 15]}, {"50 50": [8, 16]}, {"50 50": [8, 17]}, {"50 50": [8, 18]}, {"50 50": [9, 0]}, {"50 50": [9, 1]}, {"50 50": [9, 2]}, {"50 50": [9, 3]}, {"50 50": [9, 4]}, {"50 50": [9, 5]}, {"50 50": [9, 6]}, {"50 50": [9, 7]}, {"50 50": [9, 8]}, {"50 50": [9, 9]}, {"50 50": [9, 10]}, {"50 50": [9, 11]}, {"50 50": [9, 12]}, {"50 50": [9, 13]}, {"50 50": [9, 14]}, {"50 50": [9, 15]}, {"50 50": [9, 16]}, {"50 50": [9, 17]}, {"50 50": [9, 18]}, {"50 50": [10, 0]}, {"50 50": [10, 1]}, {"50 50": [10, 2]}, {"50 50": [10, 3]}, {"50 50": [10, 4]}, {"50 50": [10, 5]}, {"50 50": [10, 6]}, {"50 50": [10, 7]}, {"50 50": [10, 8]}, {"50 50": [10, 9]}, {"50 50": [10, 10]}, {"50 50": [10, 11]}, {"50 50": [10, 12]}, {"50 50": [10, 13]}, {"50 50": [10, 14]}, {"50 50": [10, 15]}, {"50 50": [10, 16]}, {"50 50": [10, 17]}, {"50 50": [10, 18]}, {"50 50": [11, 0]}, {"50 50": [11, 1]}, {"50 50": [11, 2]}, {"50 50": [11, 3]}, {"50 50": [11, 4]}, {"50 50": [11, 5]}, {"50 50": [11, 6]}, {"50 50": [11, 7]}, {"50 50": [11, 8]}, {"50 50": [11, 9]}, {"50 50": [11, 10]}, {"50 50": [11, 11]}, {"50 50": [11, 12]}, {"50 50": [11, 13]}, {"50 50": [11, 14]}, {"50 50": [11, 15]}, {"50 50": [11, 16]}, {"50 50": [11, 17]}, {"50 50": [11, 18]}, {"50 50": [12, 0]}, {"50 50": [12, 1]}, {"50 50": [12, 2]}, {"50 50": [12, 3]}, {"50 50": [12, 4]}, {"50 50": [12, 5]}, {"50 50": [12, 6]}, {"50 50": [12, 7]}, {"50 50": [12, 8]}, {"50 50": [12, 9]}, {"50 50": [12, 10]}, {"50 50": [12, 11]}, {"50 50": [12, 12]}, {"50 50": [12, 13]}, {"50 50": [12, 14]}, {"50 50": [12, 15]}, {"50 50": [12, 16]}, {"50 50": [12, 17]}, {"50 50": [12, 18]}, {"50 50": [13, 0]}, {"50 50": [13, 1]}, {"50 50": [13, 2]}, {"50 50": [13, 3]}, {"50 50": [13, 4]}, {"50 50": [13, 5]}, {"50 50": [13, 6]}, {"50 50": [13, 7]}, {"50 50": [13, 8]}, {"50 50": [13, 9]}, {"50 50": [13, 10]}, {"50 50": [13, 11]}, {"50 50": [13, 12]}, {"50 50": [13, 13]}, {"50 50": [13, 14]}, {"50 50": [13, 15]}, {"50 50": [13, 16]}, {"50 50": [13, 17]}, {"50 50": [13, 18]}, {"50 50": [14, 0]}, {"50 50": [14, 1]}, {"50 50": [14, 2]}, {"50 50": [14, 3]}, {"50 50": [14, 4]}, {"50 50": [14, 5]}, {"50 50": [14, 6]}, {"50 50": [14, 7]}, {"50 50": [14, 8]}, {"50 50": [14, 9]}, {"50 50": [14, 10]}, {"50 50": [14, 11]}, {"50 50": [14, 12]}, {"50 50": [14, 13]}, {"50 50": [14, 14]}, {"50 50": [14, 15]}, {"50 50": [14, 16]}, {"50 50": [14, 17]}, {"50 50": [14, 18]}, {"50 50": [15, 0]}, {"50 50": [15, 1]}, {"50 50": [15, 2]}, {"50 50": [15, 3]}, {"50 50": [15, 4]}, {"50 50": [15, 5]}, {"50 50": [15, 6]}, {"50 50": [15, 7]}, {"50 50": [15, 8]}, {"50 50": [15, 9]}, {"50 50": [15, 10]}, {"50 50": [15, 11]}, {"50 50": [15, 12]}, {"50 50": [15, 13]}, {"50 50": [15, 14]}, {"50 50": [15, 15]}, {"50 50": [15, 16]}, {"50 50": [15, 17]}, {"50 50": [15, 18]}, {"50 50": [16, 0]}, {"50 50": [16, 1]}, {"50 50": [16, 2]}, {"50 50": [16, 3]}, {"50 50": [16, 4]}, {"50 50": [16, 5]}, {"50 50": [16, 6]}, {"50 50": [16, 7]}, {"50 50": [16, 8]}, {"50 50": [16, 9]}, {"50 50": [16, 10]}, {"50 50": [16, 11]}, {"50 50": [16, 12]}, {"50 50": [16, 13]}, {"50 50": [16, 14]}, {"50 50": [16, 15]}, {"50 50": [16, 16]}, {"50 50": [16, 17]}, {"50 50": [16, 18]}, {"50 50": [17, 0]}, {"50 50": [17, 1]}, {"50 50": [17, 2]}, {"50 50": [17, 3]}, {"50 50": [17, 4]}, {"50 50": [17, 5]}, {"50 50": [17, 6]}, {"50 50": [17, 7]}, {"50 50": [17, 8]}, {"50 50": [17, 9]}, {"50 50": [17, 10]}, {"50 50": [17, 11]}, {"50 50": [17, 12]}, {"50 50": [17, 13]}, {"50 50": [17, 14]}, {"50 50": [17, 15]}, {"50 50": [17, 16]}, {"50 50": [17, 17]}, {"50 50": [17, 18]}, {"50 50": [18, 0]}, {"50 50": [18, 1]}, {"50 50": [18, 2]}, {"50 50": [18, 3]}, {"50 50": [18, 4]}, {"50 50": [18, 5]}, {"50 50": [18, 6]}, {"50 50": [18, 7]}, {"50 50": [18, 8]}, {"50 50": [18, 9]}, {"50 50": [18, 10]}, {"50 50": [18, 11]}, {"50 50": [18, 12]}, {"50 50": [18, 13]}, {"50 50": [18, 14]}, {"50 50": [18, 15]}, {"50 50": [18, 16]}, {"50 50": [18, 17]}, {"50 50": [18, 18]}]
O_component = H
energy_component = summation
max_element = -1
statistics = False
normalizer = False
boxcox = False

[graph]
radius = -1.0
max_num_nbr = 0
create_from_DFT = True
if_lcmp_graph = True
separate_onsite = False
new_sp = False

[train]
epochs = 200
pretrained =
resume =
train_ratio = 0.34
val_ratio = 0.34
test_ratio = 0.34
early_stopping_loss = 0.0
early_stopping_loss_epoch = [0.000000, 500]
revert_then_decay = True
revert_threshold = 30
revert_decay_epoch = [500, 2000, 3000]
revert_decay_gamma = [0.4, 0.5, 0.5]
clip_grad = True
clip_grad_value = 4.2
switch_sgd = False
switch_sgd_lr = 1e-4
switch_sgd_epoch = -1

[hyperparameter]
batch_size = 3
dtype = float32
;choices = ['sgd', 'sgdm', 'adam', 'lbfgs']
optimizer = adam
;initial learning rate
learning_rate = 0.001
;choices = ['', 'MultiStepLR', 'ReduceLROnPlateau', 'CyclicLR']
lr_scheduler =
lr_milestones = []
momentum = 0.9
weight_decay = 0
criterion = MaskMSELoss
retain_edge_fea = True
lambda_Eij = 0.0
lambda_Ei = 0.1
lambda_Etot = 0.0

[network]
atom_fea_len = 64
edge_fea_len = 128
gauss_stop = 6
;The number of angular quantum numbers that spherical harmonic functions have
num_l = 5
aggr = add
distance_expansion = GaussianBasis
if_exp = True
if_MultipleLinear = False
if_edge_update = True
if_lcmp = True
normalization = LayerNorm
;choices = ['CGConv', 'GAT', 'PAINN']
atom_update_net = CGConv
trainable_gaussians = False
type_affine = False

[mzjb]

It appears from your standard output that your materials contain four elements (Atomic types: [1, 6, 8, 50]). Please first verify if all three of your materials indeed contain these four elements.

[knight-fjy]

Following your advice, I have successfully resolved the issue. Thank you for your kind and friendly response!