nitinkgp23

absl-py==0.2.2
astor==0.6.2
backcall==0.1.0
bleach==1.5.0
certifi==2018.4.16
cycler==0.10.0
decorator==4.3.0
entrypoints==0.2.3
gast==0.2.0
grpcio==1.12.1

nitinkgp23

 def initialise(self, ser):

        c = drms.Client()
        pkeys = c.pkeys(ser)
        for pkey in pkeys:
            genClass = type(pkey, (_VSOSimpleAttr,), {})
            setattr(attrs, genClass.__name__, genClass)

nitinkgp23

----------------------------------------------------------------------
-- Train a ConvNet on faces.
--
-- original: Clement Farabet
-- new version by: E. Culurciello 
-- Mon Oct 14 14:58:50 EDT 2013
----------------------------------------------------------------------

require 'pl'
require 'trepl'

nitinkgp23

----------------------------------------------------------------------
-- This script demonstrates how to load the Face Detector 
-- training data, and pre-process it to facilitate learning.
--
-- It's a good idea to run this script with the interactive mode:
-- $ torch -i 1_data.lua
-- this will give you a Torch interpreter at the end, that you
-- can use to analyze/visualize the data you've just loaded.
--
-- Clement Farabet, Eugenio Culurciello

nitinkgp23

/**M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
//
//                           License Agreement

nitinkgp23

----------------------------------------------------------------------
-- Create CNN and loss to optimize.
--
-- Clement Farabet
----------------------------------------------------------------------

require 'torch'   -- torch
require 'image'   -- to visualize the dataset
require 'nn'      -- provides all sorts of trainable modules/layers
--require 'Dropout' -- Hinton dropout technique