# set http proxy
export http_proxy=http://PROXYHOST:PROXYPORT
# set http proxy with user and password
export http_proxy=http://USERNAME:PASSWORD@PROXYHOST:PROXYPORT
# set http proxy with user and password (with special characters)
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from __future__ import division | |
from numpy.fft import rfft | |
from numpy import argmax, mean, diff, log, nonzero | |
from scipy.signal import blackmanharris, correlate | |
from time import time | |
import sys | |
try: | |
import soundfile as sf | |
except ImportError: | |
from scikits.audiolab import flacread |

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#!/usr/bin/python | |
# coding: utf-8 | |
import numpy as np | |
from numpy import linalg | |
from sklearn.mixture import GMM | |
import scipy.linalg | |
import scipy.sparse | |
import scipy.sparse.linalg |
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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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""" | |
wGAN implemented on top of tensorflow as described in: [Wasserstein GAN](https://arxiv.org/pdf/1701.07875.pdf) | |
with improvements as described in: [Improved Training of Wasserstein GANs](https://arxiv.org/pdf/1704.00028.pdf). | |
""" | |
import tensorflow as tf | |
# |
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"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3""" | |
import tensorflow as tf | |
from tensorflow.examples.tutorials.mnist import input_data as mnist_data | |
from tensorflow.contrib import slim | |
from tensorflow.contrib.learn import ModeKeys | |
from tensorflow.contrib.learn import learn_runner | |
# Show debugging output |
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"""Helper functions for working with audio files in NumPy.""" | |
"""some code borrowed from https://github.com/mgeier/python-audio/blob/master/audio-files/utility.py""" | |
import numpy as np | |
import contextlib | |
import librosa | |
import struct | |
import soundfile | |
def float_to_byte(sig): |