akshaychawla

"""
Useful learning rate schedulers
Warmup
CosineAnnealingLRWarmup
"""
import torch
import math
import functools

def _cosine_decay_warmup(iteration, warmup_iterations, total_iterations):

akshaychawla

if [ "${CUDA_VISIBLE_DEVICES}" = "auto" ]
then
    # number of gpus 
    NUMGPUS=`nvidia-smi -q -d MEMORY | grep "Attached GPU" | grep -P -o "\d"`
    echo "NUMGPUS: $NUMGPUS"
    
    # extract free-memory for each gpu
    MEMLIST="ID FREEMEM"
    for (( DEVICE=0; DEVICE<${NUMGPUS}; DEVICE++ ))
    do

akshaychawla

import numpy as np
from keras.models import Model
from keras.layers import Dense, Activation, Lambda, Input 
import keras.backend as K 
from keras.utils import to_categorical

# Model definition 
def foo(ip):
    a = ip[1]
    x = ip[0]