Wei Zhang razhangwei

Make base class an abc.ABC and specify methods as abstractmethod or staticmethod as much as possible.
Interface function, specify the known/shared arguments as much as possible. Keep the special argument as **kwargs.

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Download:
- Downloader: spotify-downloader.com; too good to be true.

Some simple (yet not most efficient) solutions:

torchvision.datasets.ImageFolder/torchvision.datasets.DatasetFolder + data.DataLoader
lmdb (Lightning Memory-mapped database manager)

Key technologies:

lapack for process the data
Magma suuport: MAGMA is a collection of next generation linear algebra (LA) GPU accelerated libraries designed and implemented by the team that developed LAPACK and ScaLAPACK.

	"""
	This file uses cross validation to tune the parameters.
	"""
	import multiprocessing
	import sys

	import numpy as np
	import pandas as pd
	import seaborn as sns
	import matplotlib.pyplot as plt

	def plot_graph(weights, labels, ax=None):
	import networkx as nx

	G = nx.Graph()
	for i in range(weights.shape[0]):
	for j in range(weights.shape[1]):
	if weights[i][j] != 0:
	G.add_edge(labels[i], labels[j], weight=weights[i][j])

	e_pos = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] > 0]

	import matplotlib.dates as mdates

	plot.hist(mdates.date2num(dts), 100) # plot the histogram

	ax = plt.gca()
	ax.xaxis.set_major_locator(mdates.AutoDateLocator()) # set the major ticker, use AutoDateLocator
	ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d')) # show the label
	ax.xaxis.set_minor_locator(mdates.DayLocator()) # set the minor ticker, use DayLocator

	"""
	The default tf.Print op goes to STDERR
	Use the function below to direct the output to stdout instead
	Usage:
	> x=tf.ones([1, 2])
	> y=tf.zeros([1, 3])
	> p = x*x
	> p = tf_print(p, [x, y], "hello")
	> p.eval()
	hello [[ 0. 0.]]

	from abc import ABC, abstractmethod

	class Foo(ABC, object):

	@property
	@abstractmethod
	def f(self):
	pass

	@abstractmethod

	# the better practice would be always export your data along with the graph
	# maybe in the future when mpld3.fig_to_json() has been greately improved,
	# one can simply use this function.

	fig = ...
	ax = fig.axes[0]
	# line
	line = ax.lines[0]
	line.set_ydata(line.get_ydata() + 1)