- Bash (AKA Bourne Again Shell) is a type of interpreter that processes shell commands.
- A shell interpreter takes commands in plain text format and calls Operating System services to do something.
- Bash is the improved version of Sh (Bourne Shell).
- A shell scripting is writing a program for the shell to execute and a shell script is a file or program that shell will execute.
- Terminal is the interface to the shell interpreter.
- A shell script is a fully-fledged programming language in itself. It can define variables, functions and we can do conditional execution of shell commands as well.
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$ sudo mkdir -p /var/www/test.com/public_html | |
$ sudo mkdir -p /var/www/example.com/public_html | |
$ sudo chown -R $USER:$USER /var/www/example.com/public_html | |
$ sudo chown -R $USER:$USER /var/www/test.com/public_html | |
$ sudo chmod -R 755 /var/www | |
Create the virtual hosts configuration files for our two sites | |
$ sudo cp /etc/apache2/sites-available/000-default.conf /etc/apache2/sites-available/test.com.conf |
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## Save tf model under graph-model | |
saver = tf.train.Saver() # general saver object | |
#saves a model every 2 hours and maximum 4 latest models are saved. | |
saver = tf.train.Saver(max_to_keep=4, keep_checkpoint_every_n_hours=2) | |
saver = tf.train.Saver([w1,w2]) # save a list of variables | |
saver.save(sess, 'my-test-model') / saver.save(sess, 'my_test_model',global_step=1000) | |
saver.save(sess, 'my-model', global_step=step,write_meta_graph=False) # dont save the model graph |
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======================= | |
FLASK module -> | |
from flask import Flask, g, request, redirect, url_for | |
======================= |
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=== Use conda environment to run a python script === | |
SHELL=/bin/bash | |
CONDA_PREFIX=/home/code/packages/miniconda3 | |
CONDA_INIT="/home/code/packages/miniconda3/etc/conda/activate.d/proj4-activate.sh" | |
PYTHON=/home/code/packages/miniconda3/bin/python | |
12 13 * * * . $CONDA_INIT ; $PYTHON <python file> | |
=== Use date utility for naming a log file === | |
DATEVAR="date +%Y%m%d_%H%M" | |
17 * * * * echo "logs_$($DATEVAR).txt" |
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""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
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# load the iris dataset | |
from sklearn.datasets import load_iris | |
iris = load_iris() | |
# store the feature matrix (X) and response vector (y) | |
X = iris.data | |
y = iris.target | |
# splitting X and y into training and testing sets |
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# Ref -> https://colab.research.google.com/notebooks/io.ipynb#scrollTo=BaCkyg5CV5jF | |
# ---------- UPLOAD FROM LOCAL FILE SYSTEM -------------------- | |
# files.upload returns a dictionary of the files which were uploaded. The dictionary is keyed by the file name, the value is the data which was uploaded. | |
# files.download will invoke a browser download of the file to the user's local computer. |