wassname

"""
A weighted version of categorical_crossentropy for keras (2.0.6). This lets you apply a weight to unbalanced classes.
@url: https://gist.github.com/wassname/ce364fddfc8a025bfab4348cf5de852d
@author: wassname
"""
from keras import backend as K
def weighted_categorical_crossentropy(weights):
    """
    A weighted version of keras.objectives.categorical_crossentropy
    

nvgoldin

import signal
import functools
 
async def looping_task(loop, task_num):
    try:
        while True:
            print('{0}:in looping_task'.format(task_num))
            await asyncio.sleep(5.0, loop=loop)
    except asyncio.CancelledError:
        return "{0}: I was cancelled!".format(task_num)