train_shapenet.yamlΒΆ

recipes/aero_cfd/configs/train_shapenet.yaml

 1# @package _global_
 2
 3# Define key values here that are used multiple times in the config files.
 4dataset_root: <path to your shapenet dataset root>
 5dataset_kind: noether.data.datasets.cfd.ShapeNetCarDataset
 6excluded_properties: 
 7  - surface_friction
 8  - surface_area
 9  - volume_pressure
10  - volume_vorticity
11defaults:
12  - data_specs: shapenet_car
13  - dataset_normalizers: shapenet_dataset_normalizers
14  - model: ??? # models are undefined and will be defined per experiment 
15  - trainer: shapenet_trainer
16  - datasets: shapenet_dataset
17  - tracker: ?? # trackers are undefined and will be defined depending on either development, training or evaluation
18  - callbacks: training_callbacks_shapenet
19  - pipeline: shapenet_pipeline
20  - optimizer: adamw
21  - slurm: slurm_config 
22  - _self_
23
24stage_name: train
25store_code_in_output: false
26output_path: ./outputs
27
28
29# to continue training from a previous run checkpoint (which has not eneded yet), specify the run_id and stage_name to resume from. 
30#The model will be initialized from the lastest checkpoint of the specified stage if no checkpoint is specified.
31#resume_run_id: 2026-02-19_f7dy0
32#resume_stage_name: train
33#` stage_name: continue_training # optional, only needed if you want to use a different stage name for the continued training run. If not specified, the stage name will be the same as the stage name of the previous run (train in this case).
34#resume_checkpoint: E3 #If a full checkpoint path is E3_U5523_S5523. Either E*, U*, S* need to be provided
35
36# example of how to use the PreviousRunInitializer to initialize the model from a previous run.
37
38#model:
39#  initializers:
40#    - kind: noether.core.initializers.PreviousRunInitializer
41#      run_id: 2026-02-19_f7dy0
42#      model_name: transformer
43#      stage_name: train # only when a stage name is used for the previous run
44#      checkpoint_tag: E4_U3156_S3156 # can be `latest`, `last`, `best`, or a specific epoch like E3_U100_S1000
45#      model_info: ema=0.9999 # only needed when a checkoint has additional model info