dmlc--dgl
Mufei Li
fdbf5a0fda
* Update * Update * Update * Update Co-authored-by: Ubuntu <ubuntu@ip-172-31-53-142.us-west-2.compute.internal> Co-authored-by: Xin Yao <xiny@nvidia.com>
38 行
1.7 KiB
YAML
38 行
1.7 KiB
YAML
version: 0.0.2
|
|
pipeline_name: graphpred
|
|
pipeline_mode: train
|
|
device: cuda:0 # Torch device name, e.q. cpu or cuda or cuda:0
|
|
data:
|
|
name: ogbg-molhiv
|
|
split_ratio: # Ratio to generate data split, for example set to [0.8, 0.1, 0.1] for 80% train/10% val/10% test. Leave blank to use builtin split in original dataset
|
|
model:
|
|
name: pna
|
|
embed_size: 80 # Embedding size.
|
|
aggregators: mean max min std # Aggregation function names separated by space, can include mean, max, min, std, sum
|
|
scalers: identity amplification attenuation # Scaler function names separated by space, can include identity, amplification, and attenuation
|
|
dropout: 0.3 # Dropout rate.
|
|
batch_norm: true # Whether to use batch normalization.
|
|
residual: true # Whether to use residual connection.
|
|
num_mlp_layers: 1 # Number of MLP layers to use after message aggregation in each PNA layer.
|
|
num_layers: 4 # Number of PNA layers.
|
|
readout: mean # Readout for computing graph-level representations, can be 'sum' or 'mean'.
|
|
general_pipeline:
|
|
num_runs: 10 # Number of experiments to run
|
|
train_batch_size: 128 # Graph batch size when training
|
|
eval_batch_size: 128 # Graph batch size when evaluating
|
|
num_workers: 4 # Number of workers for data loading
|
|
optimizer:
|
|
name: Adam
|
|
lr: 0.01
|
|
weight_decay: 0.000003
|
|
lr_scheduler:
|
|
name: ReduceLROnPlateau
|
|
mode: max
|
|
factor: 0.5
|
|
patience: 20
|
|
verbose: true
|
|
loss: BCEWithLogitsLoss
|
|
metric: roc_auc_score
|
|
num_epochs: 200 # Number of training epochs
|
|
save_path: "results" # Directory to save the experiment results
|