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diff --git a/contrib/torch/decisiontree/init.lua b/contrib/torch/decisiontree/init.lua
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+++ b/contrib/torch/decisiontree/init.lua
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+require 'paths'
+require 'xlua'
+require 'string'
+require 'os'
+require 'sys'
+require 'image'
+require 'lfs'
+require 'nn'
+
+-- these actually return local variables but we will re-require them
+-- when needed. This is just to make sure they are loaded.
+require 'moses'
+
+unpack = unpack or table.unpack
+
+local dt = require 'decisiontree._env'
+
+-- c lib:
+require "paths"
+paths.require 'libdecisiontree'
+
+dt.HashMap = torch.getmetatable("dt.HashMap").new
+
+dt.EPSILON = 1e-6
+
+-- experimental Tensor-like container
+require 'decisiontree.SparseTensor'
+
+-- functions
+require 'decisiontree.math'
+require 'decisiontree.utils'
+
+-- for multi-threading
+require 'decisiontree.WorkPool'
+
+-- abstract classes
+require 'decisiontree.DecisionTree'
+require 'decisiontree.DecisionForest'
+require 'decisiontree.DecisionForestTrainer'
+require 'decisiontree.TreeState'
+
+-- for CaRTree inference
+require 'decisiontree.CartNode'
+require 'decisiontree.CartTree'
+
+-- Criterions (extended with updateHessInput and backward2)
+require 'decisiontree.MSECriterion'
+require 'decisiontree.LogitBoostCriterion'
+
+-- Used by both RandomForestTrainer and GradientBoostTrainer
+require 'decisiontree.CartTrainer'
+
+-- Used by CartTrainer
+require 'decisiontree.DataSet'
+
+-- Random Forest Training
+require 'decisiontree.RandomForestTrainer'
+require 'decisiontree.GiniState' -- TreeState subclass
+
+-- Gradient Boosted Decision Tree Training
+require 'decisiontree.GradientBoostTrainer'
+require 'decisiontree.GradientBoostState' -- TreeState subclass
+
+-- unit tests and benchmarks
+require 'decisiontree.test'
+require 'decisiontree.benchmark'
+
+-- nn.Module
+require 'decisiontree.DFD'
+require 'decisiontree.Sparse2Dense'
+
+return dt