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Create config.yaml

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