nlinear.json

{                  
    "model_name": "NLinear",
    "use_decoder": true,
    "model_type": "PyTorch",
    "model_params": {
      "forecast_history":20,
      "forecast_length": 10,
      "enc_in": 3,
      "individual": true
      
   },
   "dataset_params":
   {  "class": "default",
      "training_path": "tests/test_data/keag_small.csv",
      "validation_path": "tests/test_data/keag_small.csv",
      "test_path": "tests/test_data/keag_small.csv",
      "batch_size":10,
      "forecast_history":20,
      "forecast_length":10,
      "train_start": 1,
      "train_end": 300,
      "valid_start":302,
      "valid_end": 401,
      "test_start":50,
      "test_end": 450,
      "target_col": ["cfs"],
      "relevant_cols": ["cfs", "precip", "temp"],
      "scaler": "StandardScaler", 
      "interpolate": false
   },
   "training_params":
   {
      "criterion":"MSE",
      "optimizer": "Adam",
      "optim_params":
      {

      },
      "lr": 0.03,
      "epochs": 1
   
   },
   "GCS": false,
   
   "wandb": {
      "name": "flood_forecast_circleci",
      "tags": ["dummy_run", "circleci"],
      "project": "repo-flood_forecast"
   },
   "forward_params":{},
  "metrics":["MSE"],
  "inference_params":
  {     
        "datetime_start":"2016-05-31",
         "hours_to_forecast":334, 
         "test_csv_path":"tests/test_data/keag_small.csv",
         "decoder_params":{
           "decoder_function": "simple_decode", 
           "unsqueeze_dim": 1}
        ,
         "dataset_params":{
            "file_path": "tests/test_data/keag_small.csv",
            "forecast_history":20,
            "forecast_length":10,
            "relevant_cols": ["cfs", "precip", "temp"],
            "target_col": ["cfs"],
            "scaling": "StandardScaler",
            "interpolate_param": false
         }
  }
}