Update config.yaml

config.yaml

@@ -1,110 +1,18 @@
-data:
-  type: merra2
-
-  # Input variables definition
-  input_surface_vars:
-    - EFLUX
-    - GWETROOT
-    - HFLUX
-    - LAI
-    - LWGAB # surface absorbed longwave radiation
-    - LWGEM # longwave flux emitted from surface
-    - LWTUP # upwelling longwave flux at toa
-    - PS # surface pressure
-    - QV2M # 2-meter specific humidity
-    - SLP # sea level pressure
-    - SWGNT # surface net downward shortwave flux
-    - SWTNT # toa net downward shortwave flux
-    - T2M # near surface temperature
-    - TQI # total precipitable ice water
-    - TQL # total precipitable liquid water
-    - TQV # total precipitable water vapor
-    - TS # surface skin temperature
-    - U10M # 10m eastward wind
-    - V10M # 10m northward wind
-    - Z0M # surface roughness
-  input_static_surface_vars: [FRACI, FRLAND, FROCEAN, PHIS]
-  input_vertical_vars:
-    - CLOUD # cloud feraction for radiation
-    - H # geopotential/ mid layer heights
-    - OMEGA # vertical pressure velocity
-    - PL # mid level pressure
-    - QI # mass fraction of clous ice water
-    - QL # mass fraction of cloud liquid water
-    - QV # specific humidity
-    - T # tempertaure
-    - U # eastward wind
-    - V # northward wind
-  # (model level/ml ~ pressure level/hPa)
-  # 52ml ~ 562.5hPa, 56ml ~ 700hPa, 63 ml ~ 850hPa
-  input_levels: [34.0, 39.0, 41.0, 43.0, 44.0, 45.0, 48.0, 53.0, 56.0, 63.0, 68.0, 72.0]
-  ## remove: n_input_timestamps: 1
-  # Output variables definition
-  output_vars:
-    - T2M # near surface temperature
-
-  n_input_timestamps: 2
-
-  # Data transformations
-  # Initial crop before any other processing
-  crop_lat: [0, 1]
-  # crop_lon: [0, 0]
-  # coarsening of target -- applied after crop
-  input_size_lat: 60 # 6x coarsening 
-  input_size_lon: 96 # 6x coarsening 
-  apply_smoothen: True
-
-model:
-
-  # Platform independent config
-  num_static_channels: 7
+params:
+  input_size_time: 2
+  patch_size_px: [2, 2]
+  mask_unit_size_px: [30, 32]
+  n_lats_px: 360
+  n_lons_px: 576
   embed_dim: 2560
-  token_size:
-    - 1
-    - 1
   n_blocks_encoder: 12
+  n_blocks_decoder: 2
   mlp_multiplier: 4
   n_heads: 16
-  dropout_rate: 0.0
-  drop_path: 0.05
-  
-  # Accepted values: temporal, climate, none
-  residual: climate
-  
-  residual_connection: True
-  encoder_shift: False
-
-  downscaling_patch_size: [2, 2]
-  downscaling_embed_dim: 256
-  encoder_decoder_type: 'conv' # ['conv', 'transformer']
-  encoder_decoder_upsampling_mode: pixel_shuffle # ['nearest', 'bilinear', 'pixel_shuffle', 'conv_transpose']
-  encoder_decoder_kernel_size_per_stage: [[3], [3]] # Optional, default = 3 for conv_tanspose [[3], [2]]
-  encoder_decoder_scale_per_stage: [[2], [3]] # First list determines before/after backbone
-  encoder_decoder_conv_channels: 128
-
-
-
-job_id: inference-test
-batch_size: 1
-num_epochs: 400
-dl_num_workers: 2
-dl_prefetch_size: 1
-learning_rate: 0.0001
-limit_steps_train: 250
-limit_steps_valid: 25
-min_lr: 0.00001
-max_lr: 0.0002
-warm_up_steps: 0
-mask_unit_size:
-  - 15
-  - 16
-mask_ratio_inputs: 0.0
-mask_ratio_targets: 0.0
-max_batch_size: 16
-
-path_experiment: experiment
-
-backbone_freeze: True
-backbone_prefix: encoder.
-finetune_w_static: True
-strict_matching: true
+  dropout: 0.0
+  drop_path: 0.0
+  parameter_dropout: 0.0
+  residual: True  # Or False, depending on your needs
+  masking_mode: 'random'  # Or 'fixed'
+  decoder_shifting: True  # Or False
+  positional_encoding: True  # Or False