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#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Encodes or decodes an audio file with the descript audio codec.
Compared to the included "python3 -m dac encode" and "python3 -m dac decode"
of descript-audio-codec 1.0.0, this implementation differs in the following:
- chunked encoding produces the same codes as unchunked encoding,
  except at the beginning and end of the file
- encoded files are in .npz format, so the codes can be accessed as a memory

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Merges and deduplicates one or more .ics / ical files.

For usage information, call with --help.

Author: Jan Schlüter
"""

f0k

# -*- coding: utf-8 -*-

"""
PCEN Layer for Lasagne.

Author: Jan Schlüter, OFAI
"""

import numpy as np
import theano

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#!/bin/bash
# Sets each CUDA device to persistence mode and sets the application clock
# and power limit to the device's maximum supported values.
# When run with "--dry-run" as first command line argument or not as superuser,
# will display the commands, otherwise it will execute them.
#
# Hint: To run this at boot time, place this script in /root and create a file
# /etc/cron.d/nvidia_boost with the following single line:
# @reboot root /root/nvidia_boost.sh >/dev/null
#

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MIT License

Copyright (c) 2017 Jan Schlüter

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Outputs some information on CUDA-enabled devices on your computer,
including current memory usage.

It's a port of https://gist.github.com/f0k/0d6431e3faa60bffc788f8b4daa029b1
from C to Python with ctypes, so it can run without compiling anything. Note
that this is a direct translation with no attempt to make the code Pythonic.

f0k

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Example employing Lasagne for digit generation using the MNIST dataset and
Least Squares Generative Adversarial Networks
(LSGANs, see https://arxiv.org/abs/1611.04076 for the paper).

It is based on a WGAN example:
https://gist.github.com/f0k/f3190ebba6c53887d598d03119ca2066

f0k

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Example employing Lasagne for digit generation using the MNIST dataset and
Wasserstein Generative Adversarial Networks
(WGANs, see https://arxiv.org/abs/1701.07875 for the paper and
https://github.com/martinarjovsky/WassersteinGAN for the "official" code).

It is based on a DCGAN example:

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Example employing Lasagne for digit generation using the MNIST dataset and
Deep Convolutional Generative Adversarial Networks
(DCGANs, see http://arxiv.org/abs/1511.06434).

It is based on the MNIST example in Lasagne:
http://lasagne.readthedocs.org/en/latest/user/tutorial.html

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#include <stdio.h>
#include <cuda.h>
#include <cuda_runtime_api.h>

/* Outputs some information on CUDA-enabled devices on your computer,
 * including compute capability and current memory usage.
 *
 * On Linux, compile with: nvcc -o cuda_check cuda_check.c -lcuda
 * On Windows, compile with: nvcc -o cuda_check.exe cuda_check.c -lcuda
 *