def algorytm(self):
try:
response = self.client.chat_postMessage(channel=channel_id, text="Zaczynamy, LECYMY DuRRrrR")
except Exception as e:
print(e)
self.koniec = 2002
self.skip = 0
self.czaaas = time.time()
CzyIstnieje("")
self.sheet = wb.active
self.n = 2
while self.sheet.cell(row=self.n, column=1).value != None:
self.n += 1
self.zapisywacz = 0
while self.ilosc != self.koniec:
#self.pruba4Z() vs
self.pruba4ALGTEST()
print(time.time() - self.czaaas)
sandesh.send("KONIEC",
webhook=)
print("PROLOGJEJOJ")
mp3File = "JD.mp3"
playsound(mp3File)
keyboard.wait("HOME")
print("KONEIC")
def __init__(self, monitor, patience=5, mode="min", delta=0.001, webhook=None, initial_msg="Hello, this is sandesh! Your model is training...", es_notifications=False):
self.monitor = monitor
self.patience = patience
# sends early stopping notifications if es_notifications = True
self.es_notifications = es_notifications
self.counter = 0
self.mode = mode
self.best_score = None
self.early_stop = False
self.delta = delta
if self.mode == "min":
self.val_score = np.Inf
else:
self.val_score = -np.Inf
if self.monitor.startswith("train_"):
self.model_state = "train"
self.monitor_value = self.monitor[len("train_") :]
elif self.monitor.startswith("valid_"):
self.model_state = "valid"
self.monitor_value = self.monitor[len("valid_") :]
else:
raise Exception("monitor must start with train_ or valid_")
# webhook required to send messages to slack
self.webhook = webhook
# welcome message
try:
sandesh.send(initial_msg, webhook=self.webhook)
except:
raise Exception("please follow the correct syntax: sandesh.send(msg, webhook='XXXX')")
def send_log(self, **kwargs):
log = {'model': self.name}
log.update(kwargs)
try:
sandesh.send(log)
except:
print(log)
def send_log(self, **kwargs):
log = {'model': self.name}
log.update(kwargs)
if 'sandesh' in sys.modules:
sandesh.send(log)
else:
print('log not sent - no sandesh module')
def on_epoch_end(self, epoch, logs={}):
loss = logs.get('loss')
acc = logs.get('acc')
msg = f"Training accuracy was {acc} Training loss was {loss}"
sandesh.send(
msg,
webhook=
"https://hooks.slack.com/services/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"
)
def on_epoch_end(self, model):
epoch_score = model.metrics[self.model_state][self.monitor_value]
if self.mode == "min":
score = -1.0 * epoch_score
else:
score = np.copy(epoch_score)
if self.best_score is None:
self.best_score = score
# send initial score
msg = f"Epoch score: {self.best_score}"
sandesh.send(msg, webhook=self.webhook)
self.save_checkpoint(epoch_score, model)
# early stopping notifications
elif score < self.best_score + self.delta and self.es_notifications == True:
self.counter += 1
msg = "EarlyStopping counter: {} out of {}".format(self.counter, self.patience)
sandesh.send(msg, webhook=self.webhook)
else:
self.best_score = score
msg = f"Epoch score: {self.best_score}"
sandesh.send(msg, webhook=self.webhook)
self.save_checkpoint(epoch_score, model)
self.counter = 0
if save:
utils.dump_pickle(tmp, utils.FEATURE_DIR / 'price_feature.pkl')
ret_df = pd.concat([ret_df, tmp], axis=1)
tmp = date_feature(data)
if save:
utils.dump_pickle(tmp, utils.FEATURE_DIR / 'date_feature.pkl')
ret_df = pd.concat([ret_df, tmp], axis=1)
return ret_df
if __name__ == '__main__':
output_path = utils.FEATURE_DIR / 'baseline_features.pkl'
encoder_path = utils.FEATURE_DIR / 'encoder.pkl'
melted_path = utils.FEATURE_DIR / 'melted.pkl'
fold_indices_path = utils.FEATURE_DIR / 'fold_indices.pkl'
sandesh.send(f'start generating feature')
try:
print('generating features...')
# dataset = M5Dataset()
# data = preprocessing.melt_and_merge(
# dataset.calendar, dataset.sell_prices, dataset.main_df, dataset.submission,
# merge=True)
# data = preprocessing.add_separated_item_id(data)
# utils.dump_pickle(data, melted_path)
data = utils.load_pickle(melted_path)
data['date'] = pd.to_datetime(data['date'])
data['all_id'] = 'all'
# label encoding
cat = [
'item_id', 'item_id_1', 'item_id_2', 'item_id_3', 'dept_id',
'cat_id', 'store_id', 'state_id', 'event_name_1', 'event_type_1',
args = parser.parse_args()
utils.seed_everything()
print(f'on kaggle: {utils.ON_KAGGLE}')
print(utils.DATA_DIR)
print(utils.RESULTS_BASE_DIR)
TARGET_COL = 'demand'
try:
exp_name = utils.make_experiment_name(args.debug)
result_dir = utils.RESULTS_BASE_DIR / exp_name
os.mkdir(result_dir)
logger = mylogger.get_mylogger(filename=result_dir / 'log')
sandesh.send(f'start: {exp_name}')
logger.debug(f'created: {result_dir}')
logger.debug('loading data ...')
train_feat_path = utils.FEATURE_DIR / 'baseline_features.pkl'
X = utils.load_pickle(train_feat_path)
print(X.columns)
features_list = utils.load_yaml(args.feature)
utils.dump_yaml(features_list, result_dir / 'features_list.yml')
all_features = features_list['features']['original'] + \
features_list['features']['generated']
categorical_feat = features_list['categorical_features']
logger.debug(all_features)
logger.debug(f'features num: {len(all_features)}')
#formato de fecha para bases oga
diasOGA = [
dia.strftime("%Y") + '-' + dia.strftime("%m") + '-' + dia.strftime("%d")
for dia in dias
]
#formato de fecha para el resto de las bases
dias = [
dia.strftime("%Y") + dia.strftime("%m") + dia.strftime("%d")
for dia in dias
]
#print(dfOGA)
#print(dfs)
msg = ''
for i in range(dfOGA.shape[0]):
if ((str(dfOGA.created_at.iloc[1].date()) in diasOGA) == False):
msg += f"La base {dfOGA.base.iloc[i]} no está actualizada, último movimiento: {dfOGA.created_at.iloc[i]} "
for i in range(dfs.shape[0]):
if ((dfs.febo.iloc[i] in dias or dfs.fepf.iloc[i] in dias
or dfs.fefi.iloc[i] in dias) == False):
msg += f"La base {dfs.base.iloc[i]} no está actualizada, último movimiento: febo: {dfs.febo.iloc[i]} ,fepf: {dfs.fepf.iloc[i]}, fefi: {dfs.fefi.iloc[i]} "
if msg == '':
msg = 'Todas las bases estan actualizadas'
sandesh.send(
msg,
webhook=
"https://hooks.slack.com/services/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"
)
#print(msg)
def save_checkpoint(self, epoch_score, model):
if epoch_score not in [-np.inf, np.inf, -np.nan, np.nan]:
msg = "Validation score improved ({} --> {}). Saving model!".format(self.val_score, epoch_score)
sandesh.send(msg, webhook=self.webhook)
self.val_score = epoch_score
