liangfu

ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:

liangfu

#!/usr/bin/python

# Copyright 2015-2016 Nervana Systems Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#

liangfu

MobileNet_v1

MobileNets are small, low-latency, low-power models parameterized to meet the resource constraints of a variety of use cases. They can be built upon for classification, detection, embeddings and segmentation similar to how other popular large scale models, such as Inception, are used. MobileNets can be run efficiently on mobile devices with TensorFlow Mobile.

MobileNets trade off between latency, size and accuracy while comparing favorably with popular models from the literature.

Pre-trained Models

liangfu

/*
* one.c -- Lua core, libraries, and interpreter in a single file (Lua 5.3)
*/

/* default is to build the full interpreter */
#ifndef MAKE_LIB
#ifndef MAKE_LUAC
#ifndef MAKE_LUA
#define MAKE_LUA
#endif

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#!/usr/bin/env python3

import os, sys
out = ""
with open(sys.argv[1], 'r') as fp:
  lines = fp.readlines()
  for idx, line in enumerate(lines):
    end = line.find(" // @[")
    line = line[:end] + '\n'
    out += line

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{
    creator: "Yosys 0.5+220 (git sha1 94fbaff, emcc  -Os)",
    modules: {
        VTAShell: {
            ports: {
                io_host_r: {
                    direction: "output",
                    bits: [
                        0
                    ]

liangfu

import random
random.seed(111)


def bosonnlp_to_bio2(origfile, trainfile, valfile):
    val_ratio = 0.2

    traindata = []
    valdata = []
    with open(origfile, 'rt') as fp:

liangfu

import boto3

def recursive_copy(src_bucket, src_prefix, dst_bucket, dst_prefix):
    def get_partition():
        if boto3.session.Session().region_name in ["cn-northwest-1", "cn-north-1"]:
            return "aws-cn"
        else:
            return "aws"
    partition = get_partition()
    region_name = boto3.session.Session().region_name

liangfu

# Inspired by https://keon.io/deep-q-learning/

# python3 -m pip install keras==2.3.1 tensorflow-gpu==1.15 gym==0.18.3
# python3 -m pip install 'h5py==2.10.0' --force-reinstall

import random
import gym
import math
import numpy as np
import keras

liangfu

#include <stdio.h>
#include <inttypes.h>

static const uint32_t kSingleSignMask = 0x80000000;
static const uint32_t kSingleExpMask = 0x7f800000;
static const uint32_t kSingleMantMask = 0x007fffff;

static const uint32_t kHalfSignMask = 0x8000;
static const uint32_t kHalfExpMask = 0x7c00;
static const uint32_t kHalfMantMask = 0x03ff;