File size: 2,557 Bytes
04fe5fd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
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]