candlewill

import argparse
from collections import OrderedDict
import librosa
import numpy as np
import os


class Segment:
  def __init__(self, start, end):
    self.start = start

candlewill

# -*- coding: utf-8 -*-
"""Example Google style docstrings.

This module demonstrates documentation as specified by the `Google Python
Style Guide`_. Docstrings may extend over multiple lines. Sections are created
with a section header and a colon followed by a block of indented text.

Example:
    Examples can be given using either the ``Example`` or ``Examples``
    sections. Sections support any reStructuredText formatting, including

candlewill

TensorFlow Serving in 10 minutes!

TensorFlow SERVING is Googles' recommended way to deploy TensorFlow models. Without proper computer engineering background, it can be quite intimidating, even for people who feel comfortable with TensorFlow itself. Few things that I've found particularly hard were:

• Tutorial examples have C++ code (which I don't know)
• Tutorials have Kubernetes, gRPG, Bezel (some of which I saw for the first time)
• It needs to be compiled. That process takes forever!

After all, it worked just fine. Here I present an easiest possible way to deploy your models with TensorFlow Serving. You will have your self-built model running inside TF-Serving by the end of this tutorial. It will be scalable, and you will be able to query it via REST.

candlewill

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

candlewill

# redirect output and errors into file output.log:
nohup some_command > output.log 2>&1&

# abbreviated syntax for bash version >= ver.4:
nohup some_command &> output.log

candlewill

Test on ubuntu 16.04. Language: English

Tools: Festival && Merlin

1. download files and copy to merlin/tools

speech_tools

festival