View custreg.py
import numpy as np
from keras import backend as K
from keras.models import Sequential
from keras.layers import Dense, Activation
def fro_norm(w):
"""Frobenius norm."""
return K.sqrt(K.sum(K.square(K.abs(w))))
View neighbors.py
#!/usr/bin/env python
"""List all hosts with their IP adress of the current network."""
import os
out = os.popen('ip neigh').read().splitlines()
for i, line in enumerate(out, start=1):
ip = line.split(' ')[0]
h = os.popen('host {}'.format(ip)).read()
View fixed-img-dim-ordering.csv
loss acc val_acc
3.9610 0.0952 0.1941
3.3398 0.1956 0.2699
3.0923 0.2422 0.2906
2.9271 0.2720 0.3280
2.8226 0.2959 0.3571
2.7405 0.3105 0.3652
2.6743 0.3225 0.3824
2.6254 0.3334 0.3801
2.5704 0.3458 0.3858
View no-dropout-relu.csv
loss acc val_acc
3.7579 0.1279 0.2220
2.9790 0.2635 0.3115
2.6097 0.3366 0.3714
2.3593 0.3895 0.3927
2.1804 0.4300 0.4065
2.0439 0.4591 0.4234
1.9169 0.4873 0.4327
1.8246 0.5088 0.4444
1.7354 0.5310 0.4356
View cifar-100-relu-hist.csv
loss acc val_acc
4.0523 0.0756 0.1524
3.4600 0.1714 0.2415
3.1931 0.2185 0.2832
3.0300 0.2499 0.3113
2.9233 0.2692 0.3357
2.8342 0.2883 0.3480
2.7621 0.3025 0.3684
2.7050 0.3116 0.3795
2.6410 0.3273 0.3848
View calculate_net_params.py
total_parameters = 0
for variable in tf.trainable_variables():
# shape is an array of tf.Dimension
shape = variable.get_shape()
print(" shape: %s" % str(shape))
variable_parametes = 1
for dim in shape:
variable_parametes *= dim.value
print(" variable_parametes: %i" % variable_parametes)
total_parameters += variable_parametes
View image_filter.py
#!/usr/bin/env python
"""Playing with image filters."""
import scipy.misc
import scipy.ndimage
import numpy as np
# Load an example image
# Use scipy.ndimage.imread(file_name, mode='L') if you have your own
View distrib.py
#!/usr/bin/env python
"""Display information about exams."""
import numpy
import matplotlib.pyplot as plt
def main():
dist = []
View create_mask.py
#!/usr/bin/env python
"""Create a single mask image for the EndoVis Robotic Task."""
import os
import scipy.misc
import scipy.ndimage
import numpy as np
View polyglot.py
#>++++++++++[
# Python code written by Martin Thoma
#>++++++++
#>++++++++++
# Looping
#>+++++++++++
def looping(i):
""">++++++++++++ Do some crazy stuff x Written by Martin Thoma """