training_generator = data.DataLoader(training_set, **dataloader_params_train)
test_set = Dataset(test_dt)
test_generator = data.DataLoader(test_set, **dataloader_params_test)
network_params = {
'input_dim': 1, # As many as there are of columns in data
'hidden_dim': h,
'batch_size':
dataloader_params_train['batch_size'], # From dataloader_parameters
'output_dim': 1,
'dropout': 0,
'num_layers': 1
}
epochs = 150
folder_name = 'Training_best_one_on_GSPC'
new_folder = create_folder(path + '/results', folder_name)
Nice_model = Model(**network_params)
Nice_loss = torch.nn.MSELoss()
Nice_optimiser = torch.optim.Adam(Nice_model.parameters(),
lr=0.0007255273517151122)
#Nice_scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(Nice_optimiser, epochs)
Nice_model_trained, loss_train_mtrx, loss_test_mtrx, error = train_model(
Nice_model, Nice_loss, Nice_optimiser, None, epochs, training_generator,
test_generator, timesteps, dataloader_params_train['batch_size'],
new_folder, False)
for model in ['checkpoint', "last_model"]:
path_to_checkpoint = new_folder + '/' + model + '.pth.tar'
cuda = torch.cuda.is_available()
if cuda:
checkpoint = torch.load(path_to_checkpoint)
else:
if command == 'list':
get_list()
elif command == 'create_file':
try:
name = sys.argv[2]
except IndexError:
print('Отсутствует название файла')
else:
create_file(name)
elif command == 'create_folder':
try:
name = sys.argv[2]
except IndexError:
print('Отсутствует название папки')
else:
create_folder(name)
elif command == 'delete':
try:
name = sys.argv[2]
except IndexError:
print('Отсутствует название файла')
else:
delete_file(name)
elif command == 'copy':
try:
name = sys.argv[2]
new_name = sys.argv[3]
except IndexError:
print('Нужно ввести имя файла и название копии')
else:
copy_file(name, new_name)
get_list(active_dir, True) if len(
sys.argv) > 2 and sys.argv[2] == 'folders' else get_list(
active_dir)
elif command == 'create_file':
name = sys.argv[2]
try:
text = sys.argv[3]
except IndexError:
create_file(os.path.join(active_dir, name))
else:
create_file(os.path.join(active_dir, name), text)
elif command == 'create_folder':
name = sys.argv[2]
create_folder(os.path.join(active_dir, name))
elif command == 'delete':
name = sys.argv[2]
delete_f(os.path.join(active_dir, name))
elif command == 'chdir':
name = sys.argv[2]
print('Рабочая папки изменена. Содержимое:')
get_list(ch_dir(os.path.join(active_dir, name), def_fld))
elif command == 'copy':
name = sys.argv[2]
new_name = sys.argv[3]
copy_f(os.path.join(active_dir, name),
os.path.join(active_dir, new_name))
'del': 'Delete object',
'change-dir': 'Change folder',
'game': 'Play the game'
}
try:
action = sys.argv[1]
except IndexError:
print('Enter command')
c.save_log(f'{IndexError} {sys.argv}')
else:
if action == 'list':
c.get_list()
elif action == 'create-folder':
try:
c.create_folder(sys.argv[2])
except IndexError:
print('Please, specify folder name')
elif action == 'create-file':
try:
if len(sys.argv) == 4:
c.create_file(sys.argv[2], sys.argv[3])
else:
c.create_file(sys.argv[2])
except IndexError:
print('Please, specify file name')
elif action == 'copy':
try:
if len(sys.argv) == 4:
c.copy_obj(sys.argv[2], sys.argv[3])
else:
path = sys.argv[3] if len(sys.argv) >= 4 else None
text = sys.argv[4] if len(sys.argv) >= 5 else None
except Exception as ex:
print(f'Ошибка - {ex}')
else:
create_file(name, path, text)
elif command == 'create_folder':
save_info('command create_folder')
try:
name = sys.argv[2] if len(sys.argv) >= 3 else 'Temp'
path = sys.argv[3] if len(sys.argv) >= 4 else None
except Exception as ex:
print(f'Ошибка - {ex}')
else:
create_folder(name, path)
elif command == 'delete':
save_info('command delete')
try:
name = sys.argv[2]
path = sys.argv[3] if len(sys.argv) >= 4 else None
except IndexError:
print('Отсутствует название файла')
except Exception as ex:
print(f'Ошибка - {ex}')
else:
delete_file_or_folder(name, path)
elif command == 'copy':
save_info('command copy')
def train_hypopt(config):
dataset = DataLoader(path=config["filename"], split=0.80,
cols=['log_ret'], start_from= "1985-01-01", end = "1995-01-01",
label_col='log_ret', MinMax=False)
timesteps = config["timesteps"]
train_dt = dataset.get_train_data(timesteps, config["window_normalisation"], config["num_forward"])
test_dt = dataset.get_test_data(timesteps, config["window_normalisation"], config["num_forward"])
# Parameters
dataloader_params_train = {'batch_size': 1,
'shuffle': True,
'drop_last': True,
'num_workers': 0}
# Parameters
dataloader_params_test = {'batch_size': 1,
'shuffle': False,
'drop_last': True,
'num_workers': 0}
# Generators
training_set = Dataset(train_dt)
training_generator = data.DataLoader(training_set, **dataloader_params_train)
test_set = Dataset(test_dt)
test_generator = data.DataLoader(test_set, **dataloader_params_test)
### Saving:
folder_name = str(config["num_forward"])+'_forward_usng_' + str(config["timesteps"]) + '_timesteps_' + str(config["hidden_dim"]) + '_hiddenDim_' + str(
config["num_layers"]) + '_layers_'+str(config["lr"]) + "_LR"
new_folder = create_folder(config["path"], folder_name)
# Model:
network_params = {'input_dim': 1,
'hidden_dim': config["hidden_dim"],
'batch_size': 1,
'output_dim': 1,
'dropout': config["dropout"],
'num_layers': config["num_layers"]
}
model = Model(**network_params)
loss = torch.nn.MSELoss()
optimiser = torch.optim.Adam(model.parameters(), lr=config['lr'])
scheduler = None
# CUDA for PyTorch
use_cuda = torch.cuda.is_available()
device = torch.device("cuda:0" if use_cuda else "cpu")
cudnn.benchmark = True
model = model
if torch.cuda.is_available():
# print("We're running on GPU")
model.cuda()
#######
lwst_error = 1000
while True:
error, model = one_epoch_training(model, loss, optimiser,
scheduler, device,
training_generator,
test_generator, timesteps,
1)
is_best = bool(error < lwst_error)
print(
"error of the epoch: " + str(error) + " best accuracy before : " + str(lwst_error))
print("Best accuracy currently is: " + str(min(error, lwst_error)))
lwst_error = min(error, lwst_error)
save_checkpoint({
'epoch': 'tuning',
'state_dict': model.state_dict(),
'best_accuracy': lwst_error
}, is_best, new_folder)
track.log(error=-error)
game()
elif command == 'list_folder_only':
get_list(True)
elif command == 'create_file':
try:
name = sys.argv[2]
text = sys.argv[3]
path = sys.argv[4]
create_file(name, text, path)
except IndexError:
print('Не заданно название файла')
elif command == 'create_folder':
try:
name = sys.argv[2]
dir = sys.argv[3]
create_folder(name, dir)
except IndexError:
print('Не заданно название папки')
elif command == 'delete':
try:
name = sys.argv[2]
delete_file(name)
except IndexError:
print('Не заданно имя файла для удаления')
elif command == 'copy':
try:
name = sys.argv[2]
new_name = sys.argv[3]
copy_file(name, new_name)
except:
print('Введите имя копируемого файла и создайте новое имя')
