I hereby claim:
- I am bamos on github.
- I am bamos (https://keybase.io/bamos) on keybase.
- I have a public key whose fingerprint is 9C65 37B9 732B EBAC 744D 8973 E9B7 164C B72D 6B6F
To claim this, I am signing this object:
I hereby claim:
To claim this, I am signing this object:
# Manually running script | |
test1: test Tue Jul 7 09:41:01 EDT 2015 | |
test2: test Tue Jul 7 09:41:01 EDT 2015 | |
email: test Tue Jul 7 09:41:01 EDT 2015 | |
# Running script in cron | |
Entry: * * * * * /home/bamos/tmp/test.sh |
[0m-- ignore option data[0m | |
[0m-- ignore option optimState[0m | |
[0m-- ignore option cache[0m | |
[0m-- ignore option retrain[0m | |
{ | |
testBatchSize : [0;36m12[0m | |
LR : [0;36m0[0m | |
batchSize : [0;36m128[0m | |
data : [1;30m"[0m[0;32m/home/bamos/fbcunn_imagenet/imagenet_raw_images[0m[1;30m"[0m |
[0m-- ignore option data[0m | |
[0mnDonkeys[0m [0;36m0[0m [0;36m2[0m | |
[0m-- ignore option optimState[0m | |
[0m-- ignore option cache[0m | |
[0m-- ignore option retrain[0m | |
{ | |
testBatchSize : [0;36m12[0m | |
LR : [0;36m0[0m | |
batchSize : [0;36m128[0m | |
data : [1;30m"[0m[0;32m/home/bamos/fbcunn_imagenet/imagenet_raw_images[0m[1;30m"[0m |
Mean: 0.21204432748784804 | |
Stdev: 0.24856266429793847 |
$ tree data/mydataset/raw | |
person-1 | |
├── image-1.jpg | |
├── image-2.png | |
... | |
└── image-p.png | |
... | |
person-m |
%22clamp%22 | |
%27chiyaan%27-vikram | |
%27mama%27-cass-elliot | |
%27snub%27-pollard | |
%27superfly%27-jimmy-snuka | |
%27weird-al%27-yankovic | |
%28-estrella-lin-%29-lin-wei-ling | |
%C3%B8yvind-larsen-runestad | |
02:58:54 10244 .DS_Stor | |
12012 |
nan | |
1 nn.Sequential { | |
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> (7) -> (8) -> (9) -> (10) -> (11) -> (12) -> (13) -> (14) -> (15) -> (16) -> (17) -> (18) -> (19) -> (20) -> (21) -> (22) -> (23) -> (24) -> output] | |
(1): nn.SpatialConvolution(3 -> 64, 7x7, 2,2, 3,3) | |
(2): nn.SpatialBatchNormalization | |
(3): nn.ReLU | |
(4): nn.SpatialMaxPooling(3x3, 2,2, 1,1) | |
(5): nn.SpatialCrossMapLRN | |
(6): nn.SpatialConvolution(64 -> 64, 1x1) | |
(7): nn.SpatialBatchNormalization |
#!/usr/bin/env python3 | |
import argparse | |
import matplotlib as mpl | |
mpl.use('Agg') | |
import matplotlib.pyplot as plt | |
plt.style.use('bmh') | |
import numpy as np | |
import pandas as pd |