benanne

import theano
import theano.tensor as T
from theano.tensor.opt import register_canonicalize

class ConsiderConstant(theano.compile.ViewOp):
    def grad(self, args, g_outs):
        return [T.zeros_like(g_out) for g_out in g_outs]

consider_constant = ConsiderConstant()
register_canonicalize(theano.gof.OpRemove(consider_constant), name='remove_consider_constant')

benanne

import threading
import Queue
import time

def buffered_gen(source_gen, buffer_size=2, sleep_time=1):
    """
    Generator that runs a slow source generator in a separate thread.
    buffer_size: the maximal number of items to pre-generate (length of the buffer)
    """
    buffer = Queue.Queue(maxsize=buffer_size)

benanne

import numpy as np


def freq2mel(freq):
    return 1127.01048 * np.log(1 + freq / 700.0)

def mel2freq(mel):
    return (np.exp(mel / 1127.01048) - 1) * 700

def mel_binning_matrix(specgram_window_size, sample_frequency, num_mel_bands):

benanne

import theano
import theano.tensor as T


def one_hot(t, r=None):
    """
    given a tensor t of dimension d with integer values from range(r), return a
    new tensor of dimension d + 1 with values 0/1, where the last dimension
    gives a one-hot representation of the values in t.
    

benanne

import lasagne as nn
Conv2DLayer = nn.layers.Conv2DDNNLayer

def inception_module(l_in, num_1x1, reduce_3x3, num_3x3, reduce_5x5, num_5x5, gain=1.0, bias=0.1):
    """
    inception module (without the 3x3s1 pooling and projection because that's difficult in Theano right now)
    """
    shape = l_in.get_output_shape()
    out_layers = []

benanne

import numpy as np
import theano
import theano.tensor as T

def log_gamma_windschitl(z):
    return 0.5 * (T.log(2*np.pi) - T.log(z)  + z * (2 * T.log(z) - 2 + T.log(z * T.sinh(1/z) + 1 / (810*(z**6)))))

benanne

[ 96%] Building NVCC (Device) object extra/cuda/lib/THC/CMakeFiles/THC.dir//./THC_generated_THC.cu.o
/usr/lib/gcc/x86_64-unknown-linux-gnu/4.7.0/../../../../include/c++/4.7.0/ext/atomicity.h(48): error: identifier "__atomic_fetch_add" is undefined

/usr/lib/gcc/x86_64-unknown-linux-gnu/4.7.0/../../../../include/c++/4.7.0/ext/atomicity.h(52): error: identifier "__atomic_fetch_add" is undefined

/usr/lib/gcc/x86_64-unknown-linux-gnu/4.7.0/../../../../include/c++/4.7.0/limits(1405): error: identifier "__int128" is undefined

/usr/lib/gcc/x86_64-unknown-linux-gnu/4.7.0/../../../../include/c++/4.7.0/limits(1409): error: identifier "__int128" is undefined

/usr/lib/gcc/x86_64-unknown-linux-gnu/4.7.0/../../../../include/c++/4.7.0/limits(1412): error: identifier "__int128" is undefined

benanne

s = set()

with open("kaggle_visible_evaluation_triplets.txt", 'r') as f:
    for line in f:
        user, _, _ = line.strip().split('\t')
        s.add(user)
        
print "%d users" % len(s)

benanne

import theano
import theano.tensor as T
import numpy as np

def local_feature_extractor(x, W, b, shape_info=None):
    xr = x.dimshuffle(0, 2, 'x', 1) # in: (num_examples, num_input_features, 1, num_timesteps)
    Wr = W.dimshuffle(0, 1, 'x', 2) # filters: (num_output_features, num_input_features, 1, width)

    # the output of the convolution should be equal in length to the input
    len_left = (Wr.shape[3] - 1) / 2

benanne

Error freeing device pointer 0x200800000 (the launch timed out and was terminated).
!!!! error freeing device memory 0x200800000 (self=0xa64f270)
Error freeing device pointer 0x200302400 (the launch timed out and was terminated).
!!!! error freeing dev_structure memory 0x200302400 (self=0xa64f270)
---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
/usr/lib/python2.7/site-packages/IPython/utils/py3compat.pyc in execfile(fname, *where)
    173             else:
    174                 filename = fname
--> 175             __builtin__.execfile(filename, *where)