This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
''' | |
Memory profiling utilities | |
''' | |
import gc | |
import inspect | |
import linecache | |
import os.path | |
import sys | |
import time | |
import threading |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
04379243 table | |
03593526 jar | |
04225987 skateboard | |
02958343 car | |
02876657 bottle | |
04460130 tower | |
03001627 chair | |
02871439 bookshelf | |
02942699 camera | |
02691156 airplane |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from datetime import date | |
from functools import wraps | |
import time | |
import logging | |
import sys | |
from termcolor import colored | |
import os | |
import pprint | |
from tabulate import tabulate |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import os | |
import pickle | |
import torch | |
import torch.nn as nn | |
class EVALscore(nn.Module): | |
""" | |
Classifier is trained to predict the score between two black/white rope images. | |
The score is high if they are within a few steps apart, and low other wise. | |
""" | |
def __init__(self): |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
from matplotlib import pyplot as plt | |
supernet = [0.524, 0.569, 0.588, 0.633, 0.438] | |
retrain = [0.734, 0.562, 0.556, 0.581, 0.373] | |
def make_patch_spines_invisible(ax): | |
ax.set_frame_on(True) | |
ax.patch.set_visible(False) | |
for sp in ax.spines.values(): |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import matplotlib.pyplot as plt | |
import numpy as np | |
import seaborn as sns | |
import pandas as pd | |
from scipy import stats | |
TotalMSELoss = [0.2830, 0.4853, 0.6963, 1.0990, 1.2796, 1.7281, 1.8727, 2.0605, 2.1643, 2.5878, 2.7190, 3.0497, 3.1828, 3.3756, 3.4804, 3.9982, 4.6670] | |
NewLoss = [1.3913, 1.4027, 1.4132, 1.4496, 1.4591, 1.4848, 1.4941, 1.5148, 1.5144, 1.5435, 1.5481, 1.5704, 1.5802, 1.5903, 1.5958, 1.6268, 1.6650] | |
Acc = [75.52 , 75.00 , 74.66 , 74.76 , 74.46 , 74.36 , 74.43 , 74.57 , 74.52 , 74.55 , 74.34 , 73.80 , 74.33 , 74.14 , 73.86 , 73.85 , 73.58] | |
MnasNet = [49.74, 49.22, 48.13, 48.02, 47.76, 46.91, 46.68, 47.74, 47.77, 48.23, 47.61, 46.83, 47.90, 46.80, 47.11, 46.61, 46.11] # lr=0.001 |
NewerOlder