Add model configuration
Browse files- config.json +91 -0
config.json
ADDED
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{
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"architectures": [
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"CNO2d"
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],
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"framework": "pytorch",
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"model_name": "CNO",
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"model_type": "cno",
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"source_config": "config/config.yaml",
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"experiment": {
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"name": "cno_navier_stokes_2d",
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"paper": "https://arxiv.org/pdf/2302.01178",
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"seed": 0,
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"deterministic": true
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},
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"paths": {
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"data_dir": "/public/share/sugonhpcapp01/onestore/onedatasets/RPB_CNO/data",
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"train_file": "NavierStokes_64x64_IN.h5",
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"id_test_file": "NavierStokes_64x64_IN.h5",
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"ood_test_file": "NavierStokes_128x128_OUT.h5",
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"checkpoint": "weight/best_model.pth",
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"results_dir": "results"
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},
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"data": {
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"input_key": "input",
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"output_key": "output",
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"train": {
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"start": 0,
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"stop": 750
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},
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"validation": {
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"start": 768,
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"stop": 896
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},
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"test_id": {
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"start": 896,
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"stop": 1024
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},
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"test_ood": {
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"start": 0,
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"stop": 128
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}
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},
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"normalization": {
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"source": "supplied_64x64_id_benchmark",
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"input_min": -1.4294605255126953,
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"input_max": 1.4294605255126953,
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"output_min": -2.0383081436157227,
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"output_max": 2.0602376461029053,
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"epsilon": 1e-12
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},
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"model": {
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"in_channels": 1,
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"out_channels": 1,
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"base_width": 32,
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"levels": 3,
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"bottleneck_residual_blocks": 8,
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"intermediate_residual_blocks": 1,
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"kernel_size": 3,
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"latent_channels": 64,
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"activation_upsampling_factor": 2,
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"filter_taps": 12,
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"filter_half_width": 0.8,
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"cutoff_denominator": 2.0001,
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"leaky_relu_slope": 0.2
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},
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"training": {
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"epochs": 1000,
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"batch_size": 32,
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"num_workers": 4,
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"optimizer": "Adam",
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"learning_rate": 0.001,
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"weight_decay": 1e-10,
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"scheduler": "StepLR",
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"scheduler_step_size": 1,
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"scheduler_gamma": 0.98,
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"early_stopping_patience": 50,
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"log_interval": 5,
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"device": "auto"
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},
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"inference": {
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"batch_size": 16,
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"num_workers": 2,
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"device": "auto",
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"metric_epsilon": 1e-12
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},
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"paper_reference": {
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"metric": "relative_median_l1_percent",
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"id": 2.76,
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"ood": 7.04
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}
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}
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