import torch
from torch import cuda
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
#from sklearn.model_selection import train_test_split
import os
from random import shuffle, sample, seed
seed(27)
device = 'cuda' if cuda.is_available() else 'cpu'
torch.set_grad_enabled(False)
exp_path = "C:/Users/migue/Documents/GitHub/Datasets/Experimento"
#exp_path = os.path.join("Users","migue","Documents","GitHub","Datasets","Experimento")
experiments_paths = get_paths_experiment(exp_path)
experiments = {}
for folder, file_paths in experiments_paths.items():
experiments[folder] = Experiment(folder, file_paths)
subjects = experiment_to_subject(experiments)
shuffle_subjets = subjects.copy_list()
tokenizer = Tokenizer(shuffle_subjets, window_size=1024, stride=512)
shuffle(shuffle_subjets)
channel_iters = 80
#print("Se Cargaron los datos")
train_subjets, other_subjets = split_data_by_len(shuffle_subjets, 18)
#validation_subjets, test_subjets = split_data_by_len(other_subjets,3)
def load_dataset(self):
path = get_path(self.data["dataset"]["dataset_path"])
experiments_paths = get_paths_experiment(path)
self.experiments, self.subjects = create_subject_data(
experiments_paths)