start new:
tmux
start new with session name:
tmux new -s myname
for word in nlp.vocab: | |
if nlp.vocab[word.orth_].is_stop: | |
print(word.orth_) |
#!/bin/bash | |
##################################################### | |
# Name: Bash CheatSheet for Mac OSX | |
# | |
# A little overlook of the Bash basics | |
# | |
# Usage: | |
# | |
# Author: J. Le Coupanec | |
# Date: 2014/11/04 |
"""Downsized version of Xception, without residual connections. | |
""" | |
from __future__ import print_function | |
from __future__ import absolute_import | |
from keras.models import Model | |
from keras.layers import Dense | |
from keras.layers import Input | |
from keras.layers import BatchNormalization | |
from keras.layers import Activation |
from keras import applications | |
from keras.preprocessing.image import ImageDataGenerator | |
from keras import optimizers | |
from keras.models import Sequential, Model | |
from keras.layers import Dropout, Flatten, Dense, GlobalAveragePooling2D | |
from keras import backend as k | |
from keras.callbacks import ModelCheckpoint, LearningRateScheduler, TensorBoard, EarlyStopping | |
img_width, img_height = 256, 256 |
import warnings | |
warnings.filterwarnings("ignore") | |
import os | |
from shutil import copy | |
from flask import jsonify | |
from time import time | |
import numpy as np | |
from flask import Flask, request, render_template, send_from_directory | |
from keras.models import load_model |
# jupyterlab-code-formatter | |
conda install -c conda-forge black | |
jupyter labextension install @ryantam626/jupyterlab_code_formatter | |
conda install -c conda-forge jupyterlab_code_formatter | |
jupyter serverextension enable --py jupyterlab_code_formatter |
gcloud compute disks \ | |
create disk1 \ | |
--image-project ubuntu-os-cloud \ | |
--image-family ubuntu-1804-lts \ | |
--zone us-central1-b | |
gcloud compute images \ | |
create nested-vm-image \ | |
--source-disk disk1 \ |