christopher-beckham

<lasagne.layers.input.InputLayer object at 0x7fa6e38a95d0> (None, 3, 32, 32)
<lasagne.layers.conv.Conv2DLayer object at 0x7fa6e38a9950> (None, 64, 15, 15)
<lasagne.layers.normalization.BatchNormLayer object at 0x7fa6e38a9c50> (None, 64, 15, 15)
<lasagne.layers.special.NonlinearityLayer object at 0x7fa6e38b59d0> (None, 64, 15, 15)
<lasagne.layers.conv.Conv2DLayer object at 0x7fa6e38b5bd0> (None, 128, 7, 7)
<lasagne.layers.normalization.BatchNormLayer object at 0x7fa6e38b5ed0> (None, 128, 7, 7)
<lasagne.layers.special.NonlinearityLayer object at 0x7fa6e38404d0> (None, 128, 7, 7)
<lasagne.layers.conv.Conv2DLayer object at 0x7fa6e38406d0> (None, 192, 3, 3)
<lasagne.layers.normalization.BatchNormLayer object at 0x7fa6e38409d0> (None, 192, 3, 3)
<lasagne.layers.special.NonlinearityLayer object at 0x7fa6e3840f90> (None, 192, 3, 3)

christopher-beckham

import theano
from theano import tensor as T
from theano import OpFromGraph
import lasagne
from lasagne.layers import *
from lasagne.init import *
from lasagne.nonlinearities import *
from lasagne.objectives import *
from lasagne.updates import *
from lasagne.regularization import *

christopher-beckham

import theano
from theano import OpFromGraph
from theano import tensor as T
import numpy as np
import lasagne
from lasagne.layers import *

# suppose we have the network architecture:
# input -> conv1 -> conv2 -> dense
# and we want to make (conv1 -> conv2) a block

christopher-beckham

from lasagne.nonlinearities import *
from lasagne.layers import Layer

class SpatialSoftmaxLayer(Layer):
    """
    Softmax layer that computes the softmax over pixels in the same location,
    i.e., over the channel axis. This layer will automatically use the CuDNN
    version of this softmax if it is available.
    
    Parameters

christopher-beckham

Testing $x^2$

christopher-beckham

Dirs:

• ssh - Contains scripts/data/etc. that should be scped onto remote machines such as Chris's cluster.
• 22 - blah

christopher-beckham

digraph unix {
	node [color=lightblue2, style=filled];
	"node1" -> "node2"
	"node3" -> "node2"
	"node4" -> "node1"
}

christopher-beckham

from sys import stdin
import sys

N = 10 # number of sequences

body = stdin.read()
body = body.split('\n')
body = body[3:len(body)-2]
final_body = []
for elem in body:

christopher-beckham

What is the difference between ${var}, "$var", and "${var}" in the Bash shell?

http://stackoverflow.com/questions/18135451/what-is-the-difference-between-var-var-and-var-in-the-bash-shell

tl;dr - curly braces are used to disambiguate, quotes are used to form a "single word".

SSH keys

christopher-beckham

def quicksort(arr):
  if arr == []:
    return []
  if len(arr) == 1:
    return arr
  m = len(arr) / 2
  pivot = arr[m]
  less = [ arr[x] for x in range(0, len(arr)) if arr[x] <= pivot and x != m ]
  greater = [ arr[x] for x in range(0, len(arr)) if arr[x] > pivot and x != m ]
  return quicksort(less) + [pivot] + quicksort(greater)