Some changes

src/notebooks/training.py

@@ -1,63 +0,0 @@
-from src.data import DataProcessor, DataConfig
-from src.trainers.quantile_trainer import AutoRegressiveQuantileTrainer, NonAutoRegressiveQuantileRegression
-from src.trainers.probabilistic_baseline import ProbabilisticBaselineTrainer
-from src.trainers.autoregressive_trainer import AutoRegressiveTrainer
-from src.trainers.trainer import Trainer
-from src.utils.clearml import ClearMLHelper
-from src.models import *
-from src.losses import *
-import torch
-import numpy as np
-from torch.nn import MSELoss, L1Loss
-from datetime import datetime
-import pytz
-import torch.nn as nn
-
-#### ClearML ####
-clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast")
-
-#### Data Processor ####
-data_config = DataConfig()
-data_config.NRV_HISTORY = True
-data_config.LOAD_HISTORY = False
-data_config.LOAD_FORECAST = False
-
-data_config.WIND_FORECAST = False
-data_config.WIND_HISTORY = False
-
-data_processor = DataProcessor(data_config)
-data_processor.set_batch_size(1024)
-data_processor.set_full_day_skip(False)
-
-#### Hyperparameters ####
-data_processor.set_output_size(1)
-inputDim = data_processor.get_input_size()
-learningRate = 0.0001
-epochs = 100
-
-# quantiles = torch.tensor([0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99]).to("cuda")
-quantiles = torch.tensor(
-    [0.01, 0.05, 0.1, 0.15, 0.3, 0.4, 0.5, 0.6, 0.7, 0.85, 0.9, 0.95, 0.99]
-).to("cuda")
-
-# model = LinearRegression(inputDim, len(quantiles))
-model = NonLinearRegression(inputDim, len(quantiles), hiddenSize=1024, numLayers=5)
-optimizer = torch.optim.Adam(model.parameters(), lr=learningRate)
-
-#### Trainer ####
-trainer = AutoRegressiveQuantileTrainer(
-    model,
-    optimizer,
-    data_processor,
-    quantiles,
-    "cuda",
-    debug=True,
-    clearml_helper=clearml_helper,
-)
-trainer.add_metrics_to_track(
-    [PinballLoss(quantiles), MSELoss(), L1Loss(), CRPSLoss(quantiles)]
-)
-trainer.early_stopping(patience=10)
-trainer.plot_every(5)
-
-trainer.train(epochs=epochs, remotely=True)

src/utils/clearml.py

@@ -5,7 +5,6 @@ class ClearMLHelper:
         self.project_name = project_name
 
     def get_task(self, task_name: str = "Model Training"):
-        Task.add_requirements("requirements.txt")
         Task.ignore_requirements("torch")
         Task.ignore_requirements("torchvision")
         Task.ignore_requirements("tensorboard")