dniku

# The train/test net protocol buffer definition
net: "lenet_train_test_modified.prototxt"
# test_iter specifies how many forward passes the test should carry out.
# In the case of MNIST, we have test batch size 100 and 100 test iterations,
# covering the full 10,000 testing images.
test_iter: 100
# Carry out testing every 500 training iterations.
test_interval: 500
# The base learning rate, momentum and the weight decay of the network.
base_lr: 0.01

dniku

name: "LeNet"
layers {
  name: "mnist"
  type: IMAGE_DATA
  top: "data"
  top: "label"
  image_data_param {
    source: "mnist_train_index.txt"
    batch_size: 64
    is_color: false

dniku

I0322 23:04:55.893093 32722 caffe.cpp:117] Use CPU.
I0322 23:04:55.894064 32722 caffe.cpp:121] Starting Optimization
I0322 23:04:55.894438 32722 solver.cpp:32] Initializing solver from parameters: 
test_iter: 100
test_interval: 500
base_lr: 0.01
display: 100
max_iter: 10000
lr_policy: "inv"
gamma: 0.0001

dniku

require 'matrix'

class Vector
	public :"[]="#, :set_element, :set_component

	def norm_inf
		return (self.map {|x| x.abs}).max
	end

	def clone

dniku

import cp.

main =>
  N = read_int(),
  X = new_array(N),
  Y = new_array(N),
  foreach(I in 1..N)
    X[I] := read_int(),
    Y[I] := read_int()
  end,

dniku

import cp.

read_list=List =>
 L=[],
 Len=read_int(),
 foreach(I in 1..Len)
   V := read_int(),
   L := [V|L]
 end,
 List=L.

dniku

double svm_predict_probability(
        const svm_model *model, const svm_node *x, double *prob_estimates)
{
        if ((model->param.svm_type == C_SVC || model->param.svm_type == NU_SVC) &&
            model->probA!=NULL && model->probB!=NULL)
        {
                int i;
                int nr_class = model->nr_class;
                double *dec_values = Malloc(double, nr_class*(nr_class-1)/2);
                svm_predict_values(model, x, dec_values);

dniku

PHP Warning:  flock() expects parameter 1 to be resource, boolean given in /var/www/localhost/htdocs/owncloud/lib/private/config.php on line 178
PHP Fatal error:  Call to a member function getValue() on a non-object in /var/www/localhost/htdocs/owncloud/lib/private/legacy/config.php on line 46

dniku

from __future__ import division, print_function

import os

import cv2
import numpy as np

from sklearn.datasets import fetch_mldata
from sklearn.cross_validation import train_test_split

dniku

# The train/test net protocol buffer definition
net: "lenet_train_test.prototxt"
# test_iter specifies how many forward passes the test should carry out.
# In the case of MNIST, we have test batch size 100 and 100 test iterations,
# covering the full 10,000 testing images.
test_iter: 100
# Carry out testing every 20 training iterations.
test_interval: 20
# The base learning rate, momentum and the weight decay of the network.
base_lr: 0.01