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  1. README.md +2 -2
  2. config.json +23 -14
  3. data_config.yaml +31 -9
  4. pytorch_model.bin +2 -2
README.md CHANGED
@@ -39,10 +39,10 @@ Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [2].
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  ## Results
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  The training logs for the current model can be found here:
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- - [https://wandb.ai/openclimatefix/india/runs/xdlew7ib](https://wandb.ai/openclimatefix/india/runs/xdlew7ib)
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- The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/india).
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  Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
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  ## Results
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  The training logs for the current model can be found here:
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+ - [https://wandb.ai/openclimatefix/pvnet2.1/runs/kgduk9ik](https://wandb.ai/openclimatefix/pvnet2.1/runs/kgduk9ik)
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+ The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
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  Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
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config.json CHANGED
@@ -1,13 +1,9 @@
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  {
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  "_target_": "pvnet.models.multimodal.multimodal.Model",
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  "output_quantiles": [
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- 0.02,
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  0.1,
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- 0.25,
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  0.5,
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- 0.75,
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- 0.9,
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- 0.98
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  ],
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  "interval_minutes": 15,
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  "use_weighted_loss": false,
@@ -15,11 +11,20 @@
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  "ecmwf": {
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  "_target_": "pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2",
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  "_partial_": true,
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- "in_channels": 7,
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  "out_features": 256,
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  "n_res_blocks": 4,
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  "hidden_channels": 256,
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- "image_size_pixels": 84
 
 
 
 
 
 
 
 
 
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  }
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  },
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  "wind_encoder": {
@@ -34,26 +39,30 @@
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  "output_network": {
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  "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
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  "_partial_": true,
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- "fc_hidden_features": 1024,
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  "n_res_blocks": 6,
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  "res_block_layers": 4,
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  "dropout_frac": 0.0
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  },
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- "embedding_dim": 128,
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  "include_sun": false,
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  "include_gsp_yield_history": false,
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  "forecast_minutes": 2880,
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  "history_minutes": 60,
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- "min_sat_delay_minutes": 60,
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- "sat_history_minutes": 90,
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  "nwp_history_minutes": {
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- "ecmwf": 60
 
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  },
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  "nwp_forecast_minutes": {
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- "ecmwf": 2880
 
 
 
 
 
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  },
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  "wind_history_minutes": 60,
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- "sensor_interval_minutes": 15,
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  "target_key": "wind",
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  "optimizer": {
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  "_target_": "pvnet.optimizers.EmbAdamWReduceLROnPlateau",
 
1
  {
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  "_target_": "pvnet.models.multimodal.multimodal.Model",
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  "output_quantiles": [
 
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  0.1,
 
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  0.5,
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+ 0.9
 
 
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  ],
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  "interval_minutes": 15,
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  "use_weighted_loss": false,
 
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  "ecmwf": {
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  "_target_": "pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2",
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  "_partial_": true,
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+ "in_channels": 8,
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  "out_features": 256,
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  "n_res_blocks": 4,
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  "hidden_channels": 256,
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+ "image_size_pixels": 42
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+ },
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+ "gfs": {
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+ "_target_": "pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2",
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+ "_partial_": true,
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+ "in_channels": 6,
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+ "out_features": 256,
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+ "n_res_blocks": 3,
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+ "hidden_channels": 256,
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+ "image_size_pixels": 10
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  }
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  },
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  "wind_encoder": {
 
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  "output_network": {
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  "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
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  "_partial_": true,
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+ "fc_hidden_features": 128,
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  "n_res_blocks": 6,
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  "res_block_layers": 4,
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  "dropout_frac": 0.0
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  },
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+ "embedding_dim": 16,
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  "include_sun": false,
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  "include_gsp_yield_history": false,
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  "forecast_minutes": 2880,
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  "history_minutes": 60,
 
 
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  "nwp_history_minutes": {
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+ "ecmwf": 60,
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+ "gfs": 0
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  },
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  "nwp_forecast_minutes": {
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+ "ecmwf": 2880,
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+ "gfs": 2220
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+ },
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+ "nwp_interval_minutes": {
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+ "ecmwf": 60,
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+ "gfs": 180
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  },
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  "wind_history_minutes": 60,
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+ "wind_interval_minutes": 15,
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  "target_key": "wind",
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  "optimizer": {
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  "_target_": "pvnet.optimizers.EmbAdamWReduceLROnPlateau",
data_config.yaml CHANGED
@@ -2,32 +2,54 @@ general:
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  description: Config for training the saved PVNet model
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  name: PVNet current
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  input_data:
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- data_source_which_defines_geospatial_locations: wind
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  default_forecast_minutes: 2880
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  default_history_minutes: 60
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  nwp:
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  ecmwf:
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- forecast_minutes: 2880
 
 
 
 
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  history_minutes: 60
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  nwp_channels:
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  - t2m
 
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  - u10
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- - u100
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- - u200
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  - v10
 
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  - v100
 
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  - v200
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- nwp_image_size_pixels_height: 84
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- nwp_image_size_pixels_width: 84
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  nwp_provider: ecmwf
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  nwp_zarr_path: PLACEHOLDER.zarr
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  time_resolution_minutes: 60
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- x_dim_name: longitude
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- y_dim_name: latitude
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  wind:
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  get_center: true
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  n_wind_systems_per_example: 1
 
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  wind_files_groups:
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  - label: india
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  wind_filename: /mnt/storage_ssd_4tb/india_wind_data.nc
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- wind_metadata_filename: /mnt/storage_ssd_4tb/india_wind_metadata.csv
 
 
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  description: Config for training the saved PVNet model
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  name: PVNet current
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  input_data:
 
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  default_forecast_minutes: 2880
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  default_history_minutes: 60
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  nwp:
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  ecmwf:
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+ coarsen_to_degrees: 0.2
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+ dropout_fraction: 1.0
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+ dropout_timedeltas_minutes:
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+ - -360
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+ forecast_minutes: 2880.0
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  history_minutes: 60
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  nwp_channels:
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  - t2m
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+ - prate
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  - u10
 
 
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  - v10
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+ - u100
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  - v100
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+ - u200
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  - v200
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+ nwp_image_size_pixels_height: 42
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+ nwp_image_size_pixels_width: 42
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  nwp_provider: ecmwf
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  nwp_zarr_path: PLACEHOLDER.zarr
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  time_resolution_minutes: 60
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+ gfs:
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+ dropout_fraction: 1.0
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+ dropout_timedeltas_minutes:
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+ - -300
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+ forecast_minutes: 2100.0
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+ history_minutes: 60
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+ nwp_channels:
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+ - t
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+ - prate
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+ - u10
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+ - v10
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+ - u100
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+ - v100
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+ nwp_image_size_pixels_height: 10
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+ nwp_image_size_pixels_width: 10
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+ nwp_provider: gfs
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+ nwp_zarr_path: PLACEHOLDER.zarr
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+ time_resolution_minutes: 180
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  wind:
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  get_center: true
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  n_wind_systems_per_example: 1
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+ time_resolution_minutes: 15
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  wind_files_groups:
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  - label: india
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  wind_filename: /mnt/storage_ssd_4tb/india_wind_data.nc
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+ wind_metadata_filename: /mnt/storage_ssd_4tb/india_wind_metadata2.csv
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+ wind_ml_ids: []
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
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- oid sha256:f4857cdf19f63c6b49a59d3a8bf3caecb21b2341cc5ef5091e8b0c85817d6d63
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- size 493586506
 
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