thomwolf

def init_weights(self):
    """
    Here we reproduce Keras default initialization weights to initialize Embeddings/LSTM weights
    """
    ih = (param.data for name, param in self.named_parameters() if 'weight_ih' in name)
    hh = (param.data for name, param in self.named_parameters() if 'weight_hh' in name)
    b = (param.data for name, param in self.named_parameters() if 'bias' in name)
    nn.init.uniform(self.embed.weight.data, a=-0.5, b=0.5)
    for t in ih:
        nn.init.xavier_uniform(t)

fukatani

try:
    import matplotlib
    matplotlib.use('Agg')
except ImportError:
    pass

import chainer
import chainer.functions as F
import chainer.links as L
from chainer import training

rmdort

class AttentionWithContext(Layer):
    """
        Attention operation, with a context/query vector, for temporal data.
        Supports Masking.
        Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf]
        "Hierarchical Attention Networks for Document Classification"
        by using a context vector to assist the attention
        # Input shape
            3D tensor with shape: `(samples, steps, features)`.
        # Output shape

zlargon

Speed up mp3 by FFmpeg on Mac

http://ffmpeg.org/

Install FFmpeg

$ brew install ffmpeg

cbaziotis

def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

xccds

xccds

graphific

#!/usr/bin/env bash
# Installation script for Deep Learning Libraries on Ubuntu 14.04, by Roelof Pieters (@graphific)
# BSD License

orig_executor="$(whoami)"
if [ "$(whoami)" == "root" ]; then
  echo "running as root, please run as user you want to have stuff installed as"
  exit 1
fi
###################################

graphific

#!/usr/bin/env bash
# Installation script for Cuda and drivers on Ubuntu 14.04, by Roelof Pieters (@graphific)
# BSD License
if [ "$(whoami)" == "root" ]; then
  echo "running as root, please run as user you want to have stuff installed as"
  exit 1
fi
###################################
#   Ubuntu 14.04 Install script for:
# - Nvidia graphic drivers for Titan X: 352

Smerity

from __future__ import absolute_import
from __future__ import print_function
from functools import reduce
import re
import tarfile

import numpy as np
np.random.seed(1337)  # for reproducibility

bAs such, I agree strongly with you that this won't make a good test dataset for testing various RNN architectures.from keras.callbacks import EarlyStopping