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The dataset generation failed
Error code: DatasetGenerationError
Exception: IndexError
Message: list index out of range
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1901, in _prepare_split_single
original_shard_lengths[original_shard_id] += len(table)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
IndexError: list index out of range
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1342, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1922, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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====== CONFIG ====== |
[basic] |
graph_dir=/home/apolyukhin/scripts/ml/diamond-qe/deeph-data/graph |
save_dir=/home/apolyukhin/scripts/ml/diamond-qe/pristine-222/reconstruction/aohamiltonian/pred_ham_std |
raw_dir=/home/apolyukhin/scripts/ml/diamond-qe/deeph-data/preprocess |
dataset_name=diamond_qe |
only_get_graph=False |
interface=h5 |
target=hamiltonian |
disable_cuda=True |
device=cpu |
num_threads=-1 |
save_to_time_folder=False |
save_csv=True |
tb_writer=False |
seed=42 |
multiprocessing=0 |
orbital=[{"6 6": [0, 0]}, {"6 6": [0, 1]}, {"6 6": [0, 2]}, {"6 6": [0, 3]}, {"6 6": [0, 4]}, {"6 6": [0, 5]}, {"6 6": [0, 6]}, {"6 6": [0, 7]}, {"6 6": [0, 8]}, {"6 6": [0, 9]}, {"6 6": [0, 10]}, {"6 6": [0, 11]}, {"6 6": [0, 12]}, {"6 6": [1, 0]}, {"6 6": [1, 1]}, {"6 6": [1, 2]}, {"6 6": [1, 3]}, {"6 6": [1, 4]}, {"6 6": [1, 5]}, {"6 6": [1, 6]}, {"6 6": [1, 7]}, {"6 6": [1, 8]}, {"6 6": [1, 9]}, {"6 6": [1, 10]}, {"6 6": [1, 11]}, {"6 6": [1, 12]}, {"6 6": [2, 0]}, {"6 6": [2, 1]}, {"6 6": [2, 2]}, {"6 6": [2, 3]}, {"6 6": [2, 4]}, {"6 6": [2, 5]}, {"6 6": [2, 6]}, {"6 6": [2, 7]}, {"6 6": [2, 8]}, {"6 6": [2, 9]}, {"6 6": [2, 10]}, {"6 6": [2, 11]}, {"6 6": [2, 12]}, {"6 6": [3, 0]}, {"6 6": [3, 1]}, {"6 6": [3, 2]}, {"6 6": [3, 3]}, {"6 6": [3, 4]}, {"6 6": [3, 5]}, {"6 6": [3, 6]}, {"6 6": [3, 7]}, {"6 6": [3, 8]}, {"6 6": [3, 9]}, {"6 6": [3, 10]}, {"6 6": [3, 11]}, {"6 6": [3, 12]}, {"6 6": [4, 0]}, {"6 6": [4, 1]}, {"6 6": [4, 2]}, {"6 6": [4, 3]}, {"6 6": [4, 4]}, {"6 6": [4, 5]}, {"6 6": [4, 6]}, {"6 6": [4, 7]}, {"6 6": [4, 8]}, {"6 6": [4, 9]}, {"6 6": [4, 10]}, {"6 6": [4, 11]}, {"6 6": [4, 12]}, {"6 6": [5, 0]}, {"6 6": [5, 1]}, {"6 6": [5, 2]}, {"6 6": [5, 3]}, {"6 6": [5, 4]}, {"6 6": [5, 5]}, {"6 6": [5, 6]}, {"6 6": [5, 7]}, {"6 6": [5, 8]}, {"6 6": [5, 9]}, {"6 6": [5, 10]}, {"6 6": [5, 11]}, {"6 6": [5, 12]}, {"6 6": [6, 0]}, {"6 6": [6, 1]}, {"6 6": [6, 2]}, {"6 6": [6, 3]}, {"6 6": [6, 4]}, {"6 6": [6, 5]}, {"6 6": [6, 6]}, {"6 6": [6, 7]}, {"6 6": [6, 8]}, {"6 6": [6, 9]}, {"6 6": [6, 10]}, {"6 6": [6, 11]}, {"6 6": [6, 12]}, {"6 6": [7, 0]}, {"6 6": [7, 1]}, {"6 6": [7, 2]}, {"6 6": [7, 3]}, {"6 6": [7, 4]}, {"6 6": [7, 5]}, {"6 6": [7, 6]}, {"6 6": [7, 7]}, {"6 6": [7, 8]}, {"6 6": [7, 9]}, {"6 6": [7, 10]}, {"6 6": [7, 11]}, {"6 6": [7, 12]}, {"6 6": [8, 0]}, {"6 6": [8, 1]}, {"6 6": [8, 2]}, {"6 6": [8, 3]}, {"6 6": [8, 4]}, {"6 6": [8, 5]}, {"6 6": [8, 6]}, {"6 6": [8, 7]}, {"6 6": [8, 8]}, {"6 6": [8, 9]}, {"6 6": [8, 10]}, {"6 6": [8, 11]}, {"6 6": [8, 12]}, {"6 6": [9, 0]}, {"6 6": [9, 1]}, {"6 6": [9, 2]}, {"6 6": [9, 3]}, {"6 6": [9, 4]}, {"6 6": [9, 5]}, {"6 6": [9, 6]}, {"6 6": [9, 7]}, {"6 6": [9, 8]}, {"6 6": [9, 9]}, {"6 6": [9, 10]}, {"6 6": [9, 11]}, {"6 6": [9, 12]}, {"6 6": [10, 0]}, {"6 6": [10, 1]}, {"6 6": [10, 2]}, {"6 6": [10, 3]}, {"6 6": [10, 4]}, {"6 6": [10, 5]}, {"6 6": [10, 6]}, {"6 6": [10, 7]}, {"6 6": [10, 8]}, {"6 6": [10, 9]}, {"6 6": [10, 10]}, {"6 6": [10, 11]}, {"6 6": [10, 12]}, {"6 6": [11, 0]}, {"6 6": [11, 1]}, {"6 6": [11, 2]}, {"6 6": [11, 3]}, {"6 6": [11, 4]}, {"6 6": [11, 5]}, {"6 6": [11, 6]}, {"6 6": [11, 7]}, {"6 6": [11, 8]}, {"6 6": [11, 9]}, {"6 6": [11, 10]}, {"6 6": [11, 11]}, {"6 6": [11, 12]}, {"6 6": [12, 0]}, {"6 6": [12, 1]}, {"6 6": [12, 2]}, {"6 6": [12, 3]}, {"6 6": [12, 4]}, {"6 6": [12, 5]}, {"6 6": [12, 6]}, {"6 6": [12, 7]}, {"6 6": [12, 8]}, {"6 6": [12, 9]}, {"6 6": [12, 10]}, {"6 6": [12, 11]}, {"6 6": [12, 12]}] |
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=5000 |
pretrained= |
resume= |
train_ratio=0.6 |
val_ratio=0.2 |
test_ratio=0.2 |
early_stopping_loss=0.0 |
early_stopping_loss_epoch=[0.000000, 500] |
revert_then_decay=True |
revert_threshold=30 |
revert_decay_epoch=[800, 2000, 3000, 4000] |
revert_decay_gamma=[0.4, 0.5, 0.5, 0.4] |
clip_grad=True |
clip_grad_value=4.2 |
switch_sgd=False |
switch_sgd_lr=1e-4 |
switch_sgd_epoch=-1 |
[hyperparameter] |
batch_size=1 |
dtype=float32 |
optimizer=adam |
learning_rate=0.001 |
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=6.0 |
num_l=4 |
aggr=add |
distance_expansion=GaussianBasis |
if_exp=True |
if_multiplelinear=False |
if_edge_update=True |
if_lcmp=True |
normalization=LayerNorm |
atom_update_net=PAINN |
trainable_gaussians=False |
type_affine=False |
=> load best checkpoint (epoch 1070) |
=> Atomic types: [6], spinful: False, the number of atomic types: 1. |
Save processed graph to /home/apolyukhin/scripts/ml/diamond-qe/pristine-222/reconstruction/aohamiltonian/graph.pkl, cost 1.6528115272521973 seconds |
The code in this folder was obtained from "https://github.com/sakuraiiiii/HermNet" |
The code in this folder was obtained from "https://github.com/rusty1s/pytorch_geometric", which has the following license: |
Copyright (c) 2020 Matthias Fey <matthias.fey@tu-dortmund.de> |
Permission is hereby granted, free of charge, to any person obtaining a copy |
of this software and associated documentation files (the "Software"), to deal |
in the Software without restriction, including without limitation the rights |
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
copies of the Software, and to permit persons to whom the Software is |
furnished to do so, subject to the following conditions: |
The above copyright notice and this permission notice shall be included in |
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