keithmcnulty

import pandas as pd
from scipy import stats
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import RandomizedSearchCV, KFold
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from xgboost import XGBClassifier

# spit data into train test
def split_data(df: pd.DataFrame, parameters: dict) -> dict:

Rub21

import os
import glob
import tensorflow as tf
save_path = 'tf_serving_warmup_requests'
tfrecords_path = glob.glob('*_human_activities_*.tfrecords')
dataset = tf.data.TFRecordDataset(tfrecords_path)
writer = tf.data.experimental.TFRecordWriter(save_path)
writer.write(dataset)

ihoromi4

def seed_everything(seed: int):
    import random, os
    import numpy as np
    import torch
    
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)

korakot

# reset all จนกว่าจะได้ ดีกว่า K80
from IPython.display import HTML
from subprocess import getoutput
s = getoutput('nvidia-smi')
if 'K80' in s:
  gpu = 'K80'
elif 'T4' in s:
  gpu = 'T4'
elif 'P100' in s:
  gpu = 'P100'