amiasato

import torch
import torch.nn as nn
import torch.nn.functional as F


def lengths_to_mask(lengths, max_len=None, dtype=None):
    """
    Converts a "lengths" tensor to its binary mask representation.
    
    Based on: https://discuss.pytorch.org/t/how-to-generate-variable-length-mask/23397

hissinger

package main

import (
	"log"
	"os"

	gst "github.com/spreadspace/go-gstreamer"
	"github.com/ziutek/glib"
)

soumith

conda uninstall --force pillow -y

# install libjpeg-turbo to $HOME/turbojpeg
git clone https://github.com/libjpeg-turbo/libjpeg-turbo
pushd libjpeg-turbo
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX:PATH=$HOME/turbojpeg
make
make install

mrbar42

running:

bash create-vod-hls.sh beach.mkv

will produce:

    beach/
      |- playlist.m3u8
 |- 360p.m3u8

awni

"""
Author: Awni Hannun

This is an example CTC decoder written in Python. The code is
intended to be a simple example and is not designed to be
especially efficient.

The algorithm is a prefix beam search for a model trained
with the CTC loss function.

kastnerkyle

# variation to https://github.com/ryankiros/skip-thoughts/blob/master/decoding/search.py

def keras_rnn_predict(samples, empty=empty, rnn_model=model, maxlen=maxlen):
    """for every sample, calculate probability for every possible label
    you need to supply your RNN model and maxlen - the length of sequences it can handle
    """
    data = sequence.pad_sequences(samples, maxlen=maxlen, value=empty)
    return rnn_model.predict(data, verbose=0)

def beamsearch(predict=keras_rnn_predict,

jannecederberg

<form id="contact-form" action="//formspree.io/your@email.com" method="post">
	<input type="text" name="Name" placeholder="Name" required>
	<input type="email" name="Email" placeholder="Email" required>
	<textarea name="Message" cols="30" rows="6" placeholder="Message" required></textarea>
	<!-- CONFIG -->
	<input class="is-hidden" type="text" name="_gotcha">
	<input type="hidden" name="_subject" value="Subject">
	<input type="hidden" name="_cc" value="email@cc.com">
	<!-- /CONFIG -->
	<input class="submit" type="submit" value="Send">

nils-werner

def sliding_window(data, size, stepsize=1, padded=False, axis=-1, copy=True):
    """
    Calculate a sliding window over a signal

    Parameters
    ----------
    data : numpy array
        The array to be slided over.
    size : int
        The sliding window size

johnantoni

This is my take on how to get up and running with NGINX, PHP-FPM, MySQL and phpMyAdmin on OSX Yosemite.

This article is adapted from the original by Jonas Friedmann. Who I just discovered is from Würzburg in Germany. A stonesthrow from where I was born ;)

Xcode

Make sure you have the latest version of XCode installed. Available from the Mac App Store.

Install the Xcode Command Line Tools:

xcode-select --install

danijar

# Example for my blog post at:
# http://danijar.com/introduction-to-recurrent-networks-in-tensorflow/
import functools
import sets
import tensorflow as tf


def lazy_property(function):
    attribute = '_' + function.__name__