(C-x means ctrl+x, M-x means alt+x)
The default prefix is C-b. If you (or your muscle memory) prefer C-a, you need to add this to ~/.tmux.conf
:
# INSTALL INSTRUCTIONS: save as ~/.gdbinit | |
# | |
# DESCRIPTION: A user-friendly gdb configuration file. | |
# | |
# REVISION : 7.3 (16/04/2010) | |
# | |
# CONTRIBUTORS: mammon_, elaine, pusillus, mong, zhang le, l0kit, | |
# truthix the cyberpunk, fG!, gln | |
# | |
# FEEDBACK: https://www.reverse-engineering.net |
'''This script goes along the blog post | |
"Building powerful image classification models using very little data" | |
from blog.keras.io. | |
It uses data that can be downloaded at: | |
https://www.kaggle.com/c/dogs-vs-cats/data | |
In our setup, we: | |
- created a data/ folder | |
- created train/ and validation/ subfolders inside data/ | |
- created cats/ and dogs/ subfolders inside train/ and validation/ | |
- put the cat pictures index 0-999 in data/train/cats |
{ | |
"segments": { | |
"left": [ | |
{ | |
"function": "powerline.segments.shell.mode" | |
}, | |
{ | |
"function": "powerline.segments.common.net.hostname", | |
"priority": 10, | |
"args": { |
import numpy as np | |
import tensorflow as tf | |
from tensorflow.keras.datasets import mnist | |
from tensorflow.keras.utils import to_categorical | |
from tensorflow.keras.models import Sequential | |
from tensorflow.keras.layers import Dense, Activation, Conv2D, Flatten | |
from tensorflow.keras.optimizers import RMSprop | |
# download the mnist to the path '~/.keras/datasets/' if it is the first time to be called | |
# X shape (60,000 28x28), y shape (10,000, ) |