ilyaivensky

from lasagne import *
from lasagne.layers import *
from lasagne.random import get_rng
from lasagne.utils import *
import numpy as np
import theano.tensor as T
from theano.tensor.shared_randomstreams import RandomStreams


class DropoutLSTMLayer(MergeLayer):

ilyaivensky

import os
import numpy as np
from matplotlib import pyplot as plt
from time import time

from foxhound import activations
from foxhound import updates
from foxhound import inits
from foxhound.theano_utils import floatX, sharedX

ilyaivensky

def adam(loss, all_params, learning_rate=0.001, b1=0.9, b2=0.999, e=1e-8,
         gamma=1-1e-8):
    """
    ADAM update rules
    Default values are taken from [Kingma2014]

    References:
    [Kingma2014] Kingma, Diederik, and Jimmy Ba.
    "Adam: A Method for Stochastic Optimization."
    arXiv preprint arXiv:1412.6980 (2014).