OneForecast / conf /config.yaml
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model:
name: OneForecast
input_channels: 69
output_channels: 69
# Native ERA5 721x1440 is sampled every sixth point to 121x240, then cropped to 120x240.
grid_height: 120
grid_width: 240
dt_hours: 6
mesh_level: 5
processor_layers: 16
hidden_layers: 1
hidden_dim: 512
num_heads_edge: 4
num_heads_node: 4
weight_init: scratch
official_checkpoint_path: /root/private_data/workspaces/yangzt01/OneForecast/best_ckpt.tar
runtime:
seed: 42
device: dcu
output_dir: ./outputs
distributed_backend: nccl
training:
start_epoch: 0
max_epoch: 5
learning_rate: 0.00025
weight_decay: 0.0
checkpoint_dir: ./data/checkpoint
model_name: model_bak
save_every_epoch: 1
max_batches: 1
finetuning:
steps: 2
max_epoch: 2
learning_rate: 0.00025
max_batches: 1
model_source: trained
trained_model_path: ./data/checkpoint/model_bak.tar
official_checkpoint_path: /root/private_data/workspaces/yangzt01/OneForecast/best_ckpt.tar
output_path: ./data/checkpoint/model_finetuned.tar
datapipe:
name: ERA5
task: global_weather_forecasting
dataset_dir: ./data
train_years: [2000]
valid_years: [2001]
test_years: [2002]
input_steps: 1
output_steps: 1
normalize: true
batch_size: 1
num_workers: 0
# Runtime distribution is enabled automatically when launched with torchrun.
distributed: false
# This exact order matches the official OneForecast global dataset.
variables:
- Z50
- Z100
- Z150
- Z200
- Z250
- Z300
- Z400
- Z500
- Z600
- Z700
- Z850
- Z925
- Z1000
- Q50
- Q100
- Q150
- Q200
- Q250
- Q300
- Q400
- Q500
- Q600
- Q700
- Q850
- Q925
- Q1000
- T50
- T100
- T150
- T200
- T250
- T300
- T400
- T500
- T600
- T700
- T850
- T925
- T1000
- U50
- U100
- U150
- U200
- U250
- U300
- U400
- U500
- U600
- U700
- U850
- U925
- U1000
- V50
- V100
- V150
- V200
- V250
- V300
- V400
- V500
- V600
- V700
- V850
- V925
- V1000
- U10M
- V10M
- T2M
- MSLP
inference:
model_source: trained
trained_model_path: ./data/checkpoint/model_bak.tar
official_checkpoint_path: /root/private_data/workspaces/yangzt01/OneForecast/best_ckpt.tar
output_dir: ./outputs/predictions
max_batches: 1
visualization:
input_dir: ./outputs/predictions
output_dir: ./outputs/visualizations
channels: [0, 18, 36, 54, 67, 68]