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ee35332f58
* feat: Added base functions for Neural Net. * feat: Added function to handle Neural Nets. * fix: Fixed fit loop * feat: Neural Net trains now, need to test it. * feat: Prediction now works on the neural net. * fix: Put back config and run_pipeline.py * fix: Took out import from run_pipeline. * fix(Models): added get_name(), adjusted pytorch model output size * fix(Tests): fixed tests Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
26 lines
681 B
Python
26 lines
681 B
Python
import os
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import pandas as pd
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import torch
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from torch.utils.data import Dataset
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from torch.utils.data import DataLoader
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import numpy as np
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class TimeSeriesDataset(Dataset):
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def __init__(self, X: np.ndarray, y: np.ndarray):
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self.X = X
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self.y = y
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def __len__(self):
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return len(self.X)
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def __getitem__(self, idx):
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return self.X[idx].astype(float), self.y[idx].astype(float)
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def get_dataloader(X: np.ndarray, y: np.ndarray, batch_size: int = 32, shuffle: bool = True):
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training_data = TimeSeriesDataset(X, y)
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train_dataloader = DataLoader(training_data, batch_size=batch_size, shuffle=shuffle)
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return train_dataloader |