start new:
tmux
start new with session name:
tmux new -s myname
People
![]() :bowtie: |
😄 :smile: |
😆 :laughing: |
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😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
n02119789 1 kit_fox | |
n02100735 2 English_setter | |
n02110185 3 Siberian_husky | |
n02096294 4 Australian_terrier | |
n02102040 5 English_springer | |
n02066245 6 grey_whale | |
n02509815 7 lesser_panda | |
n02124075 8 Egyptian_cat | |
n02417914 9 ibex | |
n02123394 10 Persian_cat |
Updated 4/11/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
Matplotlib is a plotting library. It relies on some backend to actually render
the plots. The default backend is the agg
backend. This backend only renders
PNGs. On Jupyter notebooks the matplotlib backends are special as they are
rendered to the browser. Generally you will not need to explicitly set the
backend on a Jupyter notebook. This does introduce a discrepancy between code
that runs in Jupyter and code that runs as a script natively in the Python
interpreter. So you need to understand that the 2 environments are not the same
import torch | |
from torch import nn | |
from torch.autograd import Variable | |
import torch.nn.functional as F | |
import torch.optim as optim | |
# toy feed-forward net | |
class Net(nn.Module): | |
def __init__(self): |
Index: src/main/java/org/alicebot/ab/AIMLProcessor.java | |
=================================================================== | |
--- src/main/java/org/alicebot/ab/AIMLProcessor.java (revision 100) | |
+++ src/main/java/org/alicebot/ab/AIMLProcessor.java (working copy) | |
@@ -18,6 +18,8 @@ | |
Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, | |
Boston, MA 02110-1301, USA. | |
*/ | |
+import java.nio.ByteBuffer; | |
+import java.nio.charset.StandardCharsets; |
# Create definitions for CUB-200 (CUB200 category definition - CUB200 class definition) | |
# All .txt files can be found here: https://www.kaggle.com/datasets/veeralakrishna/200-bird-species-with-11788-images?resource=download&select=CUB_200_2011.tgz | |
import re | |
import numpy as np | |
import pickle | |
# Read the class ID for each image. We have 11788 images, each image has a class ID from 1->200 | |
img2class_file = 'image_class_labels.txt' | |
input_f = open(img2class_file) | |
img2class_dict = {} |