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def istft(stft_matrix, hop_length=None, win_length=None, window='hann',
          center=True, normalized=False, onesided=True, length=None):
    """stft_matrix = (batch, freq, time, complex) 
    
    All based on librosa
        - http://librosa.github.io/librosa/_modules/librosa/core/spectrum.html#istft
    What's missing?
        - normalize by sum of squared window --> do we need it here?
        Actually the result is ok by simply dividing y by 2. 
    """

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import torch
import torch.nn.functional as F
EPS = 1e-7

def _enhance_either_hpss(x_padded, out, kernel_size, power, which, offset):
    """x_padded: one that median filtering can be directly applied
    kernel_size = int
    dim: either 2 (freq-axis) or 3 (time-axis)

    which: str, either "harm" or "perc"

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from __future__ import division
from numpy.fft import rfft
from numpy import argmax, mean, diff, log
from matplotlib.mlab import find
from scipy.signal import blackmanharris, fftconvolve
from time import time
import sys
try:
    import soundfile as sf
except ImportError:

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Autofs on Mac OS X

With autofs you can easily mount network volumes upon first access to the folder where you want to mount the volume. Autofs is available for many OS and is preinstalled on Mac OS X so I show you how I mounted my iTunes library folder using this method.

Prepare autofs to use a separate configuration file

autofs needs to be configured so that it knows where to gets its configuration. Edit the file '/etc/auto_master' and add the last line:

#
# Automounter master map
#

+auto_master # Use directory service

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cat ../kaldi_97_call_WER_results_caller.txt | grep '[a-zA-Z0-9]\-[a-zA-Z0-9]' | xargs -I {} echo /work/luigi-cache/audio/*{}*.wav |  xargs -I@ sh -c "cp @ ."

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 # When installing tensorflow on Ubuntu14.04, do you get a message that says "tensorflow-0.7.1-cp34-none-linux_x86_64.whl is not a supported wheel on this platform."? Run the commands below to download and install manually, from command history:

 
 1056  wget https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl
 1058  mv tensorflow-0.7.1-cp34-none-linux_x86_64.whl Downloads/
 1060  cd Downloads/
 1062  mv tensorflow-0.7.1-cp34-none-linux_x86_64.whl tensorflow-0.7.1-cp35-none-linux_x86_64.whl 
 1063  sudo pip3.5 install --upgrade tensorflow-0.7.1-cp35-none-linux_x86_64.whl 

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To build a Fake Static “embedded” iOS Framework

1. Download and install the beta branch of iOS-Universal-Framework: https://github.com/kstenerud/iOS-Universal-Framework/tree/beta

2. Add a new Fake Static iOS Framework target. Follow the wizard. Choose ARC. Do not include Unit-Tests

3. Change the iOS Deployment Target Build Settings to 5.1