from VideoClassification.utils.Logger import Logger
import math
log = Logger("/tmp/runs/r3")
for step in range(100):
v1 = math.sin(step)
v2 = math.cos(step)
v3 = 2000*step
log.scalar_summary('model2/v1',v1,step)
log.scalar_summary('model2/v2',v2,step)
log.scalar_summary('model2/v3',v3,step)
from VideoClassification.utils.toolkits import accuracy, try_to_load_state_dict
from VideoClassification.utils.DataSetLoader.PictureQueue import PictureQueue, GenVariables_Spatial, \
GenVariables_Temporal
'''
VGG TWO Stram 测试:
1. Spatial 输入单张图片, SGD 10个 epoch 每个迭代4000次
初始学习率0.001, 每个epoch学习率*0.1
2. Temporal 输入连续多20张光流, SGD 20个 epoch 每个迭代5000次
初始学习率0.05 每个epoch学习率*0.5
'''
############ Config
logger = Logger(Config.LOGSpace + Config.EX_ID)
savepath = Config.ExWorkSpace + Config.EX_ID + '/'
import os.path
if os.path.isdir(savepath) == False:
os.mkdir(savepath)
batchsize = 86
############
def VGG_Temporal_Net_Run():
epochs = 80
loops = 2000