FuXi-Ocean / conf /config.yaml
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Publish FuXi-Ocean engineering reproduction
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seed: 2026
data:
path: data/fuxi_ocean_tiles.npz
format_version: fuxi_ocean_sampled_tiles_v2
input_shape: [4, 105, 2160, 4320]
atmosphere_shape: [5, 2160, 4320]
output_shape: [105, 2160, 4320]
global_height: 2160
global_width: 4320
history_steps: 4
ocean_channels: 105
atmosphere_channels: 5
time_step_hours: 6
tile_height: 16
tile_width: 16
tile_overlap: 4
train_samples: 4
test_samples: 2
depth_levels_m: [0, 2, 4, 6, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 200, 300, 400, 500, 600, 800, 1000, 1250, 1500]
model:
embed_dim: 24
patch_size: 2
encoder_levels: 2
attention_layers: 2
attention_heads: 4
epsilon: 0.000001
training:
epochs: 1
batch_size: 1
learning_rate: 0.0005
weight_decay: 0.00001
multistep_rollout: 2
runtime:
device: auto
ddp_backend: gloo
num_threads: 2
inference:
rollout_steps: 3
paper_model:
paper_determined:
input_shape: [4, 105, 2160, 4320]
atmosphere_shape: [5, 2160, 4320]
output_shape: [105, 2160, 4320]
ocean_channel_groups: {S: 26, T: 26, U: 26, V: 26, SSH: 1}
atmosphere_variables: [U10M, V10M, MSL, T2M, D2M]
shared_convolutional_patch_encoder: true
spatiotemporal_prior_network: true
history_fusion: four encodings concatenated then 1x1 convolution
low_resolution_attention: stacked attention with AdaLN and FFN
shared_transposed_convolution_decoder: true
skip_connections: true
depth_dependent_land_sea_mask: true
loss: latitude-weighted Charbonnier
training_stages: single-step pretraining then multi-step fine-tuning
metrics: [latitude-weighted RMSE, MBE, persistence]
missing_architecture:
patch_size: MISSING
hidden_width: MISSING
attention_layer_count: MISSING
attention_head_count: MISSING
exact_prior_network: MISSING
normalization_statistics: MISSING
optimizer_and_schedule: MISSING
batch_size_and_epochs: MISSING
multistep_finetuning_horizon: MISSING
rollout_steps: 40
time_step_hours: 6
paths:
checkpoint: result/checkpoints/fuxi_ocean.pt
training_metrics: result/training/metrics.json
inference: result/output/predictions.npz
inference_metadata: result/output/metadata.json
evaluation_metrics: result/evaluation/metrics.json
evaluation_plot: result/evaluation/lead_metrics.png