First of all install update and upgrade your system:
$ sudo apt update
$ sudo apt upgrade
Then, install required libraries:
import gym | |
from gym.envs.registration import register | |
from gym import error, spaces, utils | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import pandas as pd | |
import pandas_datareader.data as web | |
import arrow | |
import random | |
import sys |
jq — https://jqlang.github.io/jq/ — "like sed for JSON data"
There are several options available for installing jq.
I prefer to use Homebrew: brew install jq
# Step - Submit Predictions | |
# We have finished training and ready to run predictions on the test set. | |
log_test_preds = learn.predict(is_test=True) | |
# Convert log predictions to just probabilities (predictions). | |
test_preds = np.exp(log_test_preds) | |
# Create the submission file using the probabilities | |
# Get a list of image file names from the test data loader | |
im_fnames = data.test_dl.dataset.fnames |
from model import Net | |
from trainer import Trainer | |
import torch | |
from torch import nn | |
from matplotlib import pyplot as plt | |
model = Net() | |
ckpt = torch.load('path_to_checkpoint') | |
model.load_state_dict(ckpt['state_dict']) | |
filter = model.conv1.weight.data.numpy() |
""" | |
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) |
#!flask/bin/python | |
from flask import Flask, jsonify, abort, request, make_response, url_for | |
from flask_httpauth import HTTPBasicAuth | |
app = Flask(__name__, static_url_path = "") | |
auth = HTTPBasicAuth() | |
@auth.get_password | |
def get_password(username): | |
if username == 'miguel': |
Simplest intro to git by github and codeschool - Try Git
[Intro to github]