stevenguh

# Import TCN library from https://github.com/locuslab/TCN

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import weight_norm

def conv1d_same_padding(input, weight, bias=None, stride=1, dilation=1, groups=1):
    input_length = input.size(2)
    filter_length = weight.size(2)

santisbon

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willfurnass

Random Grid Engine tips and tricks

The following work with Son of Grid Engine (SGE) 8.1.9 as configured on the University of Sheffield's ShARC and Iceberg clusters.

Jobs with dependancies

You can use the -hold_jid <<job-name or job-name>> option to make jobs run only when other jobs have finished, rather than having jobs start and sit waiting for other tasks to complete.

mjdietzx

"""
Clean and simple Keras implementation of network architectures described in:
    - (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
    - (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).
    
Python 3.
"""

from keras import layers
from keras import models

hadware

import numpy as np
from subprocess import PIPE, run
from scipy.io.wavfile import read, write

## This is in case you have a numpy nd array of your sound, and the sampling rate
## isn't the same as another ndarray. This resamples the array by piping in and out of Sox
## This is a simple example with wav files encoded in float32, with only one channel (mono)
## These parameters can however be adjusted by tweaking -t and -c options in the sox command

with open("sample_48k.wav", "rb") as file_48k, open("sample_16k.wav", "rb") as file_16k:

asadharis

Setting up a SGE cluster on a single Amazon EC2 machine

The gist here provides a script to automate the process of installing Sun Grid Engine (SGE) on a single EC2 machine.

Motivation

SGE is a job scheduler for a computing cluster. This usually involves a cluster of multiple machines. However for many applications we don't need a massive computing cluster and a cluster of 8-30 nodes would be sufficient. In this tutorial we set-up SGE on a single amazon EC2 machine. The reasons for doing so are as follows:

1. Automation: Setting-up a cluster with SGE is fairly involved as it requires multiple machines communicating with each other and having some shared memory. A single machine with multiple cores is already a simple cluster where the memory is shared across cores.
2. Moderate Size: Amazon EC2 instances provide a variety of computing options with the number of cores ranging from 1 to 128.
3. Cost: The On-Demand price structure of AWS makes this a relatively cheap option. Further cost redu

esromneb

% This is a modified version of matlab's building rref which calculates
% row-reduced echelon form in gf(2).  Useful for linear codes.
% Tolerance was removed because yolo, and because all values
% should only be 0 or 1.  @benathon

function [A] = g2rref(A)
%G2RREF   Reduced row echelon form in gf(2).
%   R = RREF(A) produces the reduced row echelon form of A in gf(2).
%
%   Class support for input A:

dan-blanchard

I recently needed a way to run unit tests on Travis for a project that uses Sun Grid Engine, Grid Map. Unfortunately, it seemed like no one had figured out how to set that up on Travis before (or simply create a single-machine installation without any user interaction). After hours of trial-and-error, I now know the secrets to making a single-machine installation of SGE that runs on Travis, and I'm sharing my script to prevent other people from going through the same frustrating experience.

To use the install_sge.sh script below, you just need to copy all of the files in this gist to a travis sub-directory directly under the root of your GitHub project, and add the following lines to your .travis.yml

before_install:
  - travis/install_sge.sh
  - export SGE_ROOT=/var/lib/gridengine
  - export SGE_CELL=default
  - export DRMAA_LIBRARY_PATH=/usr/lib/libdrmaa.so.1.0

aldro61

#  Copyright (c) 2013 Alexandre Drouin. All rights reserved.
#
#  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:
#
#  The above copyright notice and this permission notice shall be included in all

aluchies

""" Zoom FFT function"""

import numpy as np
from time import time
from scipy.fftpack import fft, ifft
from numpy import swapaxes

def chirpz(x, A=None, W=None, M=None):
    """chirpz(x, A, W, M) - Chirp z-transform of variable x