diff --git a/CMakeLists.txt b/CMakeLists.txt
index 64884e3..2f6ae04 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,10 +1,13 @@
 cmake_minimum_required(VERSION 3.5)
-project(testcpy)
+project(PyWrap)
 
-set( CMAKE_CXX_STANDARD 20)
-set( CMAKE_CXX_STANDARD_REQUIRED ON )
+set(CMAKE_CXX_STANDARD 20)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
 
 find_package(Python3 3.11...3.11.9 COMPONENTS Interpreter Development REQUIRED)
 find_package(Torch REQUIRED)
 
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
+
+add_subdirectory(lib/Files)
 add_subdirectory(src)
\ No newline at end of file
diff --git a/data/glass.arff b/data/glass.arff
new file mode 100755
index 0000000..abd9e3c
--- /dev/null
+++ b/data/glass.arff
@@ -0,0 +1,332 @@
+% 1. Title: Glass Identification Database
+% 
+% 2. Sources:
+%     (a) Creator: B. German
+%         -- Central Research Establishment
+%            Home Office Forensic Science Service
+%            Aldermaston, Reading, Berkshire RG7 4PN
+%     (b) Donor: Vina Spiehler, Ph.D., DABFT
+%                Diagnostic Products Corporation
+%                (213) 776-0180 (ext 3014)
+%     (c) Date: September, 1987
+% 
+% 3. Past Usage:
+%     -- Rule Induction in Forensic Science
+%        -- Ian W. Evett and Ernest J. Spiehler
+%        -- Central Research Establishment
+%           Home Office Forensic Science Service
+%           Aldermaston, Reading, Berkshire RG7 4PN
+%        -- Unknown technical note number (sorry, not listed here)
+%        -- General Results: nearest neighbor held its own with respect to the
+%              rule-based system
+% 
+% 4. Relevant Information:n
+%       Vina conducted a comparison test of her rule-based system, BEAGLE, the
+%       nearest-neighbor algorithm, and discriminant analysis.  BEAGLE is 
+%       a product available through VRS Consulting, Inc.; 4676 Admiralty Way,
+%       Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189.
+%       In determining whether the glass was a type of "float" glass or not,
+%       the following results were obtained (# incorrect answers):
+% 
+%              Type of Sample                            Beagle   NN    DA
+%              Windows that were float processed (87)     10      12    21
+%              Windows that were not:            (76)     19      16    22
+% 
+%       The study of classification of types of glass was motivated by 
+%       criminological investigation.  At the scene of the crime, the glass left
+%       can be used as evidence...if it is correctly identified!
+% 
+% 5. Number of Instances: 214
+% 
+% 6. Number of Attributes: 10 (including an Id#) plus the class attribute
+%    -- all attributes are continuously valued
+% 
+% 7. Attribute Information:
+%    1. Id number: 1 to 214
+%    2. RI: refractive index
+%    3. Na: Sodium (unit measurement: weight percent in corresponding oxide, as 
+%                   are attributes 4-10)
+%    4. Mg: Magnesium
+%    5. Al: Aluminum
+%    6. Si: Silicon
+%    7. K: Potassium
+%    8. Ca: Calcium
+%    9. Ba: Barium
+%   10. Fe: Iron
+%   11. Type of glass: (class attribute)
+%       -- 1 building_windows_float_processed
+%       -- 2 building_windows_non_float_processed
+%       -- 3 vehicle_windows_float_processed
+%       -- 4 vehicle_windows_non_float_processed (none in this database)
+%       -- 5 containers
+%       -- 6 tableware
+%       -- 7 headlamps
+% 
+% 8. Missing Attribute Values: None
+% 
+% Summary Statistics:
+% Attribute:   Min     Max      Mean     SD      Correlation with class
+%  2. RI:       1.5112  1.5339   1.5184  0.0030  -0.1642
+%  3. Na:      10.73   17.38    13.4079  0.8166   0.5030
+%  4. Mg:       0       4.49     2.6845  1.4424  -0.7447
+%  5. Al:       0.29    3.5      1.4449  0.4993   0.5988
+%  6. Si:      69.81   75.41    72.6509  0.7745   0.1515
+%  7. K:        0       6.21     0.4971  0.6522  -0.0100
+%  8. Ca:       5.43   16.19     8.9570  1.4232   0.0007
+%  9. Ba:       0       3.15     0.1750  0.4972   0.5751
+% 10. Fe:       0       0.51     0.0570  0.0974  -0.1879
+% 
+% 9. Class Distribution: (out of 214 total instances)
+%     -- 163 Window glass (building windows and vehicle windows)
+%        -- 87 float processed  
+%           -- 70 building windows
+%           -- 17 vehicle windows
+%        -- 76 non-float processed
+%           -- 76 building windows
+%           -- 0 vehicle windows
+%     -- 51 Non-window glass
+%        -- 13 containers
+%        -- 9 tableware
+%        -- 29 headlamps
+% 
+% 
+% 
+%
+%
+%
+%
+% Relabeled values in attribute 'Type'
+%    From: '1'                     To: 'build wind float'    
+%    From: '2'                     To: 'build wind non-float'
+%    From: '3'                     To: 'vehic wind float'    
+%    From: '4'                     To: 'vehic wind non-float'
+%    From: '5'                     To: containers          
+%    From: '6'                     To: tableware           
+%    From: '7'                     To: headlamps           
+%
+@relation Glass
+@attribute 'RI' real
+@attribute 'Na' real
+@attribute 'Mg' real
+@attribute 'Al' real
+@attribute 'Si' real
+@attribute 'K' real
+@attribute 'Ca' real
+@attribute 'Ba' real
+@attribute 'Fe' real
+@attribute 'Type' { 'build wind float', 'build wind non-float', 'vehic wind float', 'vehic wind non-float', containers, tableware, headlamps}
+@data
+1.51793,12.79,3.5,1.12,73.03,0.64,8.77,0,0,'build wind float'
+1.51643,12.16,3.52,1.35,72.89,0.57,8.53,0,0,'vehic wind float'
+1.51793,13.21,3.48,1.41,72.64,0.59,8.43,0,0,'build wind float'
+1.51299,14.4,1.74,1.54,74.55,0,7.59,0,0,tableware
+1.53393,12.3,0,1,70.16,0.12,16.19,0,0.24,'build wind non-float'
+1.51655,12.75,2.85,1.44,73.27,0.57,8.79,0.11,0.22,'build wind non-float'
+1.51779,13.64,3.65,0.65,73,0.06,8.93,0,0,'vehic wind float'
+1.51837,13.14,2.84,1.28,72.85,0.55,9.07,0,0,'build wind float'
+1.51545,14.14,0,2.68,73.39,0.08,9.07,0.61,0.05,headlamps
+1.51789,13.19,3.9,1.3,72.33,0.55,8.44,0,0.28,'build wind non-float'
+1.51625,13.36,3.58,1.49,72.72,0.45,8.21,0,0,'build wind non-float'
+1.51743,12.2,3.25,1.16,73.55,0.62,8.9,0,0.24,'build wind non-float'
+1.52223,13.21,3.77,0.79,71.99,0.13,10.02,0,0,'build wind float'
+1.52121,14.03,3.76,0.58,71.79,0.11,9.65,0,0,'vehic wind float'
+1.51665,13.14,3.45,1.76,72.48,0.6,8.38,0,0.17,'vehic wind float'
+1.51707,13.48,3.48,1.71,72.52,0.62,7.99,0,0,'build wind non-float'
+1.51719,14.75,0,2,73.02,0,8.53,1.59,0.08,headlamps
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+1.51994,13.27,0,1.76,73.03,0.47,11.32,0,0,containers
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+1.51841,12.93,3.74,1.11,72.28,0.64,8.96,0,0.22,'build wind non-float'
+1.51754,13.39,3.66,1.19,72.79,0.57,8.27,0,0.11,'build wind float'
+1.52058,12.85,1.61,2.17,72.18,0.76,9.7,0.24,0.51,containers
+1.51569,13.24,3.49,1.47,73.25,0.38,8.03,0,0,'build wind non-float'
+1.5159,12.82,3.52,1.9,72.86,0.69,7.97,0,0,'build wind non-float'
+1.51683,14.56,0,1.98,73.29,0,8.52,1.57,0.07,headlamps
+1.51687,13.23,3.54,1.48,72.84,0.56,8.1,0,0,'build wind non-float'
+1.5161,13.33,3.53,1.34,72.67,0.56,8.33,0,0,'vehic wind float'
+1.51674,12.87,3.56,1.64,73.14,0.65,7.99,0,0,'build wind non-float'
+1.51832,13.33,3.34,1.54,72.14,0.56,8.99,0,0,'vehic wind float'
+1.51115,17.38,0,0.34,75.41,0,6.65,0,0,tableware
+1.51645,13.44,3.61,1.54,72.39,0.66,8.03,0,0,'build wind non-float'
+1.51755,13,3.6,1.36,72.99,0.57,8.4,0,0.11,'build wind float'
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+1.51627,13,3.58,1.54,72.83,0.61,8.04,0,0,'build wind non-float'
+1.5159,13.24,3.34,1.47,73.1,0.39,8.22,0,0,'build wind non-float'
+1.51934,13.64,3.54,0.75,72.65,0.16,8.89,0.15,0.24,'vehic wind float'
+1.51755,12.71,3.42,1.2,73.2,0.59,8.64,0,0,'build wind float'
+1.51514,14.01,2.68,3.5,69.89,1.68,5.87,2.2,0,containers
+1.51766,13.21,3.69,1.29,72.61,0.57,8.22,0,0,'build wind float'
+1.51784,13.08,3.49,1.28,72.86,0.6,8.49,0,0,'build wind float'
+1.52177,13.2,3.68,1.15,72.75,0.54,8.52,0,0,'build wind non-float'
+1.51753,12.57,3.47,1.38,73.39,0.6,8.55,0,0.06,'build wind float'
+1.51851,13.2,3.63,1.07,72.83,0.57,8.41,0.09,0.17,'build wind non-float'
+1.51743,13.3,3.6,1.14,73.09,0.58,8.17,0,0,'build wind float'
+1.51593,13.09,3.59,1.52,73.1,0.67,7.83,0,0,'build wind non-float'
+1.5164,14.37,0,2.74,72.85,0,9.45,0.54,0,headlamps
+1.51735,13.02,3.54,1.69,72.73,0.54,8.44,0,0.07,'build wind float'
+1.52247,14.86,2.2,2.06,70.26,0.76,9.76,0,0,headlamps
+1.52099,13.69,3.59,1.12,71.96,0.09,9.4,0,0,'build wind float'
+1.51769,13.65,3.66,1.11,72.77,0.11,8.6,0,0,'vehic wind float'
+1.51846,13.41,3.89,1.33,72.38,0.51,8.28,0,0,'build wind non-float'
+1.51848,13.64,3.87,1.27,71.96,0.54,8.32,0,0.32,'build wind non-float'
+1.51905,13.6,3.62,1.11,72.64,0.14,8.76,0,0,'build wind float'
+1.51567,13.29,3.45,1.21,72.74,0.56,8.57,0,0,'build wind float'
+1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float'
+1.5232,13.72,3.72,0.51,71.75,0.09,10.06,0,0.16,'build wind float'
+1.51556,13.87,0,2.54,73.23,0.14,9.41,0.81,0.01,headlamps
+1.51926,13.2,3.33,1.28,72.36,0.6,9.14,0,0.11,'build wind float'
+1.52211,14.19,3.78,0.91,71.36,0.23,9.14,0,0.37,'vehic wind float'
+1.53125,10.73,0,2.1,69.81,0.58,13.3,3.15,0.28,'build wind non-float'
+1.52152,13.05,3.65,0.87,72.32,0.19,9.85,0,0.17,'build wind float'
+1.51829,14.46,2.24,1.62,72.38,0,9.26,0,0,tableware
+1.51892,13.46,3.83,1.26,72.55,0.57,8.21,0,0.14,'build wind non-float'
+1.51888,14.99,0.78,1.74,72.5,0,9.95,0,0,tableware
+1.51829,13.24,3.9,1.41,72.33,0.55,8.31,0,0.1,'build wind non-float'
+1.523,13.31,3.58,0.82,71.99,0.12,10.17,0,0.03,'build wind float'
+1.51652,13.56,3.57,1.47,72.45,0.64,7.96,0,0,'build wind non-float'
+1.51768,12.56,3.52,1.43,73.15,0.57,8.54,0,0,'build wind float'
+1.51215,12.99,3.47,1.12,72.98,0.62,8.35,0,0.31,'build wind float'
+1.51646,13.04,3.4,1.26,73.01,0.52,8.58,0,0,'vehic wind float'
+1.51721,12.87,3.48,1.33,73.04,0.56,8.43,0,0,'build wind float'
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+1.51742,13.27,3.62,1.24,73.08,0.55,8.07,0,0,'build wind float'
+1.52127,14.32,3.9,0.83,71.5,0,9.49,0,0,'vehic wind float'
+1.51779,13.21,3.39,1.33,72.76,0.59,8.59,0,0,'build wind float'
+1.52171,11.56,1.88,1.56,72.86,0.47,11.41,0,0,containers
+1.518,13.71,3.93,1.54,71.81,0.54,8.21,0,0.15,'build wind non-float'
+1.52777,12.64,0,0.67,72.02,0.06,14.4,0,0,'build wind non-float'
+1.5175,12.82,3.55,1.49,72.75,0.54,8.52,0,0.19,'build wind float'
+1.51764,12.98,3.54,1.21,73,0.65,8.53,0,0,'build wind float'
+1.52177,13.75,1.01,1.36,72.19,0.33,11.14,0,0,'build wind non-float'
+1.51645,14.94,0,1.87,73.11,0,8.67,1.38,0,headlamps
+1.51786,12.73,3.43,1.19,72.95,0.62,8.76,0,0.3,'build wind float'
+1.52152,13.12,3.58,0.9,72.2,0.23,9.82,0,0.16,'build wind float'
+1.51937,13.79,2.41,1.19,72.76,0,9.77,0,0,tableware
+1.51514,14.85,0,2.42,73.72,0,8.39,0.56,0,headlamps
+1.52172,13.48,3.74,0.9,72.01,0.18,9.61,0,0.07,'build wind float'
+1.51732,14.95,0,1.8,72.99,0,8.61,1.55,0,headlamps
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+1.51605,12.9,3.44,1.45,73.06,0.44,8.27,0,0,'build wind non-float'
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+1.51673,13.3,3.64,1.53,72.53,0.65,8.03,0,0.29,'build wind non-float'
+1.52365,15.79,1.83,1.31,70.43,0.31,8.61,1.68,0,headlamps
+1.51685,14.92,0,1.99,73.06,0,8.4,1.59,0,headlamps
+1.51658,14.8,0,1.99,73.11,0,8.28,1.71,0,headlamps
+1.51316,13.02,0,3.04,70.48,6.21,6.96,0,0,containers
+1.51709,13,3.47,1.79,72.72,0.66,8.18,0,0,'build wind non-float'
+1.51727,14.7,0,2.34,73.28,0,8.95,0.66,0,headlamps
+1.51898,13.58,3.35,1.23,72.08,0.59,8.91,0,0,'build wind float'
+1.51969,12.64,0,1.65,73.75,0.38,11.53,0,0,containers
+1.5182,12.62,2.76,0.83,73.81,0.35,9.42,0,0.2,'build wind non-float'
+1.51617,14.95,0,2.27,73.3,0,8.71,0.67,0,headlamps
+1.51911,13.9,3.73,1.18,72.12,0.06,8.89,0,0,'build wind float'
+1.51651,14.38,0,1.94,73.61,0,8.48,1.57,0,headlamps
+1.51694,12.86,3.58,1.31,72.61,0.61,8.79,0,0,'vehic wind float'
+1.52315,13.44,3.34,1.23,72.38,0.6,8.83,0,0,headlamps
+1.52068,13.55,2.09,1.67,72.18,0.53,9.57,0.27,0.17,'build wind non-float'
+1.51838,14.32,3.26,2.22,71.25,1.46,5.79,1.63,0,headlamps
+1.51818,13.72,0,0.56,74.45,0,10.99,0,0,'build wind non-float'
+1.51769,12.45,2.71,1.29,73.7,0.56,9.06,0,0.24,'build wind float'
+1.5166,12.99,3.18,1.23,72.97,0.58,8.81,0,0.24,'build wind non-float'
+1.51589,12.88,3.43,1.4,73.28,0.69,8.05,0,0.24,'build wind float'
+1.5241,13.83,2.9,1.17,71.15,0.08,10.79,0,0,'build wind non-float'
+1.52725,13.8,3.15,0.66,70.57,0.08,11.64,0,0,'build wind non-float'
+1.52119,12.97,0.33,1.51,73.39,0.13,11.27,0,0.28,containers
+1.51748,12.86,3.56,1.27,73.21,0.54,8.38,0,0.17,'build wind float'
+1.51653,11.95,0,1.19,75.18,2.7,8.93,0,0,headlamps
+1.51623,14.14,0,2.88,72.61,0.08,9.18,1.06,0,headlamps
+1.52101,13.64,4.49,1.1,71.78,0.06,8.75,0,0,'build wind float'
+1.51763,12.61,3.59,1.31,73.29,0.58,8.5,0,0,'build wind float'
+1.51596,13.02,3.56,1.54,73.11,0.72,7.9,0,0,'build wind non-float'
+1.51674,12.79,3.52,1.54,73.36,0.66,7.9,0,0,'build wind non-float'
+1.52065,14.36,0,2.02,73.42,0,8.44,1.64,0,headlamps
+1.51768,12.65,3.56,1.3,73.08,0.61,8.69,0,0.14,'build wind float'
+1.52369,13.44,0,1.58,72.22,0.32,12.24,0,0,containers
+1.51756,13.15,3.61,1.05,73.24,0.57,8.24,0,0,'build wind float'
+1.51754,13.48,3.74,1.17,72.99,0.59,8.03,0,0,'build wind float'
+1.51711,12.89,3.62,1.57,72.96,0.61,8.11,0,0,'build wind non-float'
+1.5221,13.73,3.84,0.72,71.76,0.17,9.74,0,0,'build wind float'
+1.51594,13.09,3.52,1.55,72.87,0.68,8.05,0,0.09,'build wind non-float'
+1.51784,12.68,3.67,1.16,73.11,0.61,8.7,0,0,'build wind float'
+1.51909,13.89,3.53,1.32,71.81,0.51,8.78,0.11,0,'build wind float'
+1.51977,13.81,3.58,1.32,71.72,0.12,8.67,0.69,0,'build wind float'
+1.51666,12.86,0,1.83,73.88,0.97,10.17,0,0,containers
+1.51631,13.34,3.57,1.57,72.87,0.61,7.89,0,0,'build wind non-float'
+1.51872,12.93,3.66,1.56,72.51,0.58,8.55,0,0.12,'build wind non-float'
+1.51708,13.72,3.68,1.81,72.06,0.64,7.88,0,0,'build wind non-float'
+1.52081,13.78,2.28,1.43,71.99,0.49,9.85,0,0.17,'build wind non-float'
+1.51574,14.86,3.67,1.74,71.87,0.16,7.36,0,0.12,'build wind non-float'
+1.51813,13.43,3.98,1.18,72.49,0.58,8.15,0,0,'build wind non-float'
+1.51131,13.69,3.2,1.81,72.81,1.76,5.43,1.19,0,headlamps
+1.52227,14.17,3.81,0.78,71.35,0,9.69,0,0,'build wind float'
+1.52614,13.7,0,1.36,71.24,0.19,13.44,0,0.1,'build wind non-float'
+1.51811,13.33,3.85,1.25,72.78,0.52,8.12,0,0,'build wind non-float'
+1.51655,13.41,3.39,1.28,72.64,0.52,8.65,0,0,'vehic wind float'
+1.51751,12.81,3.57,1.35,73.02,0.62,8.59,0,0,'build wind float'
+1.51508,15.15,0,2.25,73.5,0,8.34,0.63,0,headlamps
+1.51915,12.73,1.85,1.86,72.69,0.6,10.09,0,0,containers
+1.51966,14.77,3.75,0.29,72.02,0.03,9,0,0,'build wind float'
+1.51844,13.25,3.76,1.32,72.4,0.58,8.42,0,0,'build wind non-float'
+1.52664,11.23,0,0.77,73.21,0,14.68,0,0,'build wind non-float'
+1.52172,13.51,3.86,0.88,71.79,0.23,9.54,0,0.11,'build wind float'
+1.51602,14.85,0,2.38,73.28,0,8.76,0.64,0.09,headlamps
+1.51321,13,0,3.02,70.7,6.21,6.93,0,0,containers
+1.52739,11.02,0,0.75,73.08,0,14.96,0,0,'build wind non-float'
+1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float'
+1.51747,12.84,3.5,1.14,73.27,0.56,8.55,0,0,'build wind float'
+1.51839,12.85,3.67,1.24,72.57,0.62,8.68,0,0.35,'build wind non-float'
+1.51646,13.41,3.55,1.25,72.81,0.68,8.1,0,0,'build wind non-float'
+1.51609,15.01,0,2.51,73.05,0.05,8.83,0.53,0,headlamps
+1.51667,12.94,3.61,1.26,72.75,0.56,8.6,0,0,'build wind non-float'
+1.51588,13.12,3.41,1.58,73.26,0.07,8.39,0,0.19,'build wind non-float'
+1.52667,13.99,3.7,0.71,71.57,0.02,9.82,0,0.1,'build wind float'
+1.51831,14.39,0,1.82,72.86,1.41,6.47,2.88,0,headlamps
+1.51918,14.04,3.58,1.37,72.08,0.56,8.3,0,0,'build wind float'
+1.51613,13.88,1.78,1.79,73.1,0,8.67,0.76,0,headlamps
+1.52196,14.36,3.85,0.89,71.36,0.15,9.15,0,0,'build wind float'
+1.51824,12.87,3.48,1.29,72.95,0.6,8.43,0,0,'build wind float'
+1.52151,11.03,1.71,1.56,73.44,0.58,11.62,0,0,containers
+1.51969,14.56,0,0.56,73.48,0,11.22,0,0,tableware
+1.51618,13.01,3.5,1.48,72.89,0.6,8.12,0,0,'build wind non-float'
+1.51645,13.4,3.49,1.52,72.65,0.67,8.08,0,0.1,'build wind non-float'
+1.51796,13.5,3.36,1.63,71.94,0.57,8.81,0,0.09,'vehic wind float'
+1.52222,14.43,0,1,72.67,0.1,11.52,0,0.08,'build wind non-float'
+1.51783,12.69,3.54,1.34,72.95,0.57,8.75,0,0,'build wind float'
+1.51711,14.23,0,2.08,73.36,0,8.62,1.67,0,headlamps
+1.51736,12.78,3.62,1.29,72.79,0.59,8.7,0,0,'build wind float'
+1.51808,13.43,2.87,1.19,72.84,0.55,9.03,0,0,'build wind float'
+1.5167,13.24,3.57,1.38,72.7,0.56,8.44,0,0.1,'vehic wind float'
+1.52043,13.38,0,1.4,72.25,0.33,12.5,0,0,containers
+1.519,13.49,3.48,1.35,71.95,0.55,9,0,0,'build wind float'
+1.51778,13.21,2.81,1.29,72.98,0.51,9.02,0,0.09,'build wind float'
+1.51905,14,2.39,1.56,72.37,0,9.57,0,0,tableware
+1.51531,14.38,0,2.66,73.1,0.04,9.08,0.64,0,headlamps
+1.51916,14.15,0,2.09,72.74,0,10.88,0,0,tableware
+1.51841,13.02,3.62,1.06,72.34,0.64,9.13,0,0.15,'build wind non-float'
+1.5159,13.02,3.58,1.51,73.12,0.69,7.96,0,0,'build wind non-float'
+1.51593,13.25,3.45,1.43,73.17,0.61,7.86,0,0,'build wind non-float'
+1.5164,12.55,3.48,1.87,73.23,0.63,8.08,0,0.09,'build wind non-float'
+1.51663,12.93,3.54,1.62,72.96,0.64,8.03,0,0.21,'build wind non-float'
+1.5169,13.33,3.54,1.61,72.54,0.68,8.11,0,0,'build wind non-float'
+1.51869,13.19,3.37,1.18,72.72,0.57,8.83,0,0.16,'build wind float'
+1.51776,13.53,3.41,1.52,72.04,0.58,8.79,0,0,'vehic wind float'
+1.51775,12.85,3.48,1.23,72.97,0.61,8.56,0.09,0.22,'build wind float'
+1.5186,13.36,3.43,1.43,72.26,0.51,8.6,0,0,'build wind non-float'
+1.5172,13.38,3.5,1.15,72.85,0.5,8.43,0,0,'build wind float'
+1.51623,14.2,0,2.79,73.46,0.04,9.04,0.4,0.09,headlamps
+1.51618,13.53,3.55,1.54,72.99,0.39,7.78,0,0,'build wind float'
+1.51761,12.81,3.54,1.23,73.24,0.58,8.39,0,0,'build wind float'
+1.5161,13.42,3.4,1.22,72.69,0.59,8.32,0,0,'vehic wind float'
+1.51592,12.86,3.52,2.12,72.66,0.69,7.97,0,0,'build wind non-float'
+1.51613,13.92,3.52,1.25,72.88,0.37,7.94,0,0.14,'build wind non-float'
+1.51689,12.67,2.88,1.71,73.21,0.73,8.54,0,0,'build wind non-float'
+1.51852,14.09,2.19,1.66,72.67,0,9.32,0,0,tableware
diff --git a/data/iris.arff b/data/iris.arff
new file mode 100755
index 0000000..780480c
--- /dev/null
+++ b/data/iris.arff
@@ -0,0 +1,225 @@
+% 1. Title: Iris Plants Database
+% 
+% 2. Sources:
+%      (a) Creator: R.A. Fisher
+%      (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)
+%      (c) Date: July, 1988
+% 
+% 3. Past Usage:
+%    - Publications: too many to mention!!!  Here are a few.
+%    1. Fisher,R.A. "The use of multiple measurements in taxonomic problems"
+%       Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions
+%       to Mathematical Statistics" (John Wiley, NY, 1950).
+%    2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis.
+%       (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.
+%    3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System
+%       Structure and Classification Rule for Recognition in Partially Exposed
+%       Environments".  IEEE Transactions on Pattern Analysis and Machine
+%       Intelligence, Vol. PAMI-2, No. 1, 67-71.
+%       -- Results:
+%          -- very low misclassification rates (0% for the setosa class)
+%    4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule".  IEEE 
+%       Transactions on Information Theory, May 1972, 431-433.
+%       -- Results:
+%          -- very low misclassification rates again
+%    5. See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al's AUTOCLASS II
+%       conceptual clustering system finds 3 classes in the data.
+% 
+% 4. Relevant Information:
+%    --- This is perhaps the best known database to be found in the pattern
+%        recognition literature.  Fisher's paper is a classic in the field
+%        and is referenced frequently to this day.  (See Duda & Hart, for
+%        example.)  The data set contains 3 classes of 50 instances each,
+%        where each class refers to a type of iris plant.  One class is
+%        linearly separable from the other 2; the latter are NOT linearly
+%        separable from each other.
+%    --- Predicted attribute: class of iris plant.
+%    --- This is an exceedingly simple domain.
+% 
+% 5. Number of Instances: 150 (50 in each of three classes)
+% 
+% 6. Number of Attributes: 4 numeric, predictive attributes and the class
+% 
+% 7. Attribute Information:
+%    1. sepal length in cm
+%    2. sepal width in cm
+%    3. petal length in cm
+%    4. petal width in cm
+%    5. class: 
+%       -- Iris Setosa
+%       -- Iris Versicolour
+%       -- Iris Virginica
+% 
+% 8. Missing Attribute Values: None
+% 
+% Summary Statistics:
+%  	           Min  Max   Mean    SD   Class Correlation
+%    sepal length: 4.3  7.9   5.84  0.83    0.7826   
+%     sepal width: 2.0  4.4   3.05  0.43   -0.4194
+%    petal length: 1.0  6.9   3.76  1.76    0.9490  (high!)
+%     petal width: 0.1  2.5   1.20  0.76    0.9565  (high!)
+% 
+% 9. Class Distribution: 33.3% for each of 3 classes.
+
+@RELATION iris
+
+@ATTRIBUTE sepallength	REAL
+@ATTRIBUTE sepalwidth 	REAL
+@ATTRIBUTE petallength 	REAL
+@ATTRIBUTE petalwidth	REAL
+@ATTRIBUTE class 	{Iris-setosa,Iris-versicolor,Iris-virginica}
+
+@DATA
+5.1,3.5,1.4,0.2,Iris-setosa
+4.9,3.0,1.4,0.2,Iris-setosa
+4.7,3.2,1.3,0.2,Iris-setosa
+4.6,3.1,1.5,0.2,Iris-setosa
+5.0,3.6,1.4,0.2,Iris-setosa
+5.4,3.9,1.7,0.4,Iris-setosa
+4.6,3.4,1.4,0.3,Iris-setosa
+5.0,3.4,1.5,0.2,Iris-setosa
+4.4,2.9,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5.4,3.7,1.5,0.2,Iris-setosa
+4.8,3.4,1.6,0.2,Iris-setosa
+4.8,3.0,1.4,0.1,Iris-setosa
+4.3,3.0,1.1,0.1,Iris-setosa
+5.8,4.0,1.2,0.2,Iris-setosa
+5.7,4.4,1.5,0.4,Iris-setosa
+5.4,3.9,1.3,0.4,Iris-setosa
+5.1,3.5,1.4,0.3,Iris-setosa
+5.7,3.8,1.7,0.3,Iris-setosa
+5.1,3.8,1.5,0.3,Iris-setosa
+5.4,3.4,1.7,0.2,Iris-setosa
+5.1,3.7,1.5,0.4,Iris-setosa
+4.6,3.6,1.0,0.2,Iris-setosa
+5.1,3.3,1.7,0.5,Iris-setosa
+4.8,3.4,1.9,0.2,Iris-setosa
+5.0,3.0,1.6,0.2,Iris-setosa
+5.0,3.4,1.6,0.4,Iris-setosa
+5.2,3.5,1.5,0.2,Iris-setosa
+5.2,3.4,1.4,0.2,Iris-setosa
+4.7,3.2,1.6,0.2,Iris-setosa
+4.8,3.1,1.6,0.2,Iris-setosa
+5.4,3.4,1.5,0.4,Iris-setosa
+5.2,4.1,1.5,0.1,Iris-setosa
+5.5,4.2,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5.0,3.2,1.2,0.2,Iris-setosa
+5.5,3.5,1.3,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+4.4,3.0,1.3,0.2,Iris-setosa
+5.1,3.4,1.5,0.2,Iris-setosa
+5.0,3.5,1.3,0.3,Iris-setosa
+4.5,2.3,1.3,0.3,Iris-setosa
+4.4,3.2,1.3,0.2,Iris-setosa
+5.0,3.5,1.6,0.6,Iris-setosa
+5.1,3.8,1.9,0.4,Iris-setosa
+4.8,3.0,1.4,0.3,Iris-setosa
+5.1,3.8,1.6,0.2,Iris-setosa
+4.6,3.2,1.4,0.2,Iris-setosa
+5.3,3.7,1.5,0.2,Iris-setosa
+5.0,3.3,1.4,0.2,Iris-setosa
+7.0,3.2,4.7,1.4,Iris-versicolor
+6.4,3.2,4.5,1.5,Iris-versicolor
+6.9,3.1,4.9,1.5,Iris-versicolor
+5.5,2.3,4.0,1.3,Iris-versicolor
+6.5,2.8,4.6,1.5,Iris-versicolor
+5.7,2.8,4.5,1.3,Iris-versicolor
+6.3,3.3,4.7,1.6,Iris-versicolor
+4.9,2.4,3.3,1.0,Iris-versicolor
+6.6,2.9,4.6,1.3,Iris-versicolor
+5.2,2.7,3.9,1.4,Iris-versicolor
+5.0,2.0,3.5,1.0,Iris-versicolor
+5.9,3.0,4.2,1.5,Iris-versicolor
+6.0,2.2,4.0,1.0,Iris-versicolor
+6.1,2.9,4.7,1.4,Iris-versicolor
+5.6,2.9,3.6,1.3,Iris-versicolor
+6.7,3.1,4.4,1.4,Iris-versicolor
+5.6,3.0,4.5,1.5,Iris-versicolor
+5.8,2.7,4.1,1.0,Iris-versicolor
+6.2,2.2,4.5,1.5,Iris-versicolor
+5.6,2.5,3.9,1.1,Iris-versicolor
+5.9,3.2,4.8,1.8,Iris-versicolor
+6.1,2.8,4.0,1.3,Iris-versicolor
+6.3,2.5,4.9,1.5,Iris-versicolor
+6.1,2.8,4.7,1.2,Iris-versicolor
+6.4,2.9,4.3,1.3,Iris-versicolor
+6.6,3.0,4.4,1.4,Iris-versicolor
+6.8,2.8,4.8,1.4,Iris-versicolor
+6.7,3.0,5.0,1.7,Iris-versicolor
+6.0,2.9,4.5,1.5,Iris-versicolor
+5.7,2.6,3.5,1.0,Iris-versicolor
+5.5,2.4,3.8,1.1,Iris-versicolor
+5.5,2.4,3.7,1.0,Iris-versicolor
+5.8,2.7,3.9,1.2,Iris-versicolor
+6.0,2.7,5.1,1.6,Iris-versicolor
+5.4,3.0,4.5,1.5,Iris-versicolor
+6.0,3.4,4.5,1.6,Iris-versicolor
+6.7,3.1,4.7,1.5,Iris-versicolor
+6.3,2.3,4.4,1.3,Iris-versicolor
+5.6,3.0,4.1,1.3,Iris-versicolor
+5.5,2.5,4.0,1.3,Iris-versicolor
+5.5,2.6,4.4,1.2,Iris-versicolor
+6.1,3.0,4.6,1.4,Iris-versicolor
+5.8,2.6,4.0,1.2,Iris-versicolor
+5.0,2.3,3.3,1.0,Iris-versicolor
+5.6,2.7,4.2,1.3,Iris-versicolor
+5.7,3.0,4.2,1.2,Iris-versicolor
+5.7,2.9,4.2,1.3,Iris-versicolor
+6.2,2.9,4.3,1.3,Iris-versicolor
+5.1,2.5,3.0,1.1,Iris-versicolor
+5.7,2.8,4.1,1.3,Iris-versicolor
+6.3,3.3,6.0,2.5,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+7.1,3.0,5.9,2.1,Iris-virginica
+6.3,2.9,5.6,1.8,Iris-virginica
+6.5,3.0,5.8,2.2,Iris-virginica
+7.6,3.0,6.6,2.1,Iris-virginica
+4.9,2.5,4.5,1.7,Iris-virginica
+7.3,2.9,6.3,1.8,Iris-virginica
+6.7,2.5,5.8,1.8,Iris-virginica
+7.2,3.6,6.1,2.5,Iris-virginica
+6.5,3.2,5.1,2.0,Iris-virginica
+6.4,2.7,5.3,1.9,Iris-virginica
+6.8,3.0,5.5,2.1,Iris-virginica
+5.7,2.5,5.0,2.0,Iris-virginica
+5.8,2.8,5.1,2.4,Iris-virginica
+6.4,3.2,5.3,2.3,Iris-virginica
+6.5,3.0,5.5,1.8,Iris-virginica
+7.7,3.8,6.7,2.2,Iris-virginica
+7.7,2.6,6.9,2.3,Iris-virginica
+6.0,2.2,5.0,1.5,Iris-virginica
+6.9,3.2,5.7,2.3,Iris-virginica
+5.6,2.8,4.9,2.0,Iris-virginica
+7.7,2.8,6.7,2.0,Iris-virginica
+6.3,2.7,4.9,1.8,Iris-virginica
+6.7,3.3,5.7,2.1,Iris-virginica
+7.2,3.2,6.0,1.8,Iris-virginica
+6.2,2.8,4.8,1.8,Iris-virginica
+6.1,3.0,4.9,1.8,Iris-virginica
+6.4,2.8,5.6,2.1,Iris-virginica
+7.2,3.0,5.8,1.6,Iris-virginica
+7.4,2.8,6.1,1.9,Iris-virginica
+7.9,3.8,6.4,2.0,Iris-virginica
+6.4,2.8,5.6,2.2,Iris-virginica
+6.3,2.8,5.1,1.5,Iris-virginica
+6.1,2.6,5.6,1.4,Iris-virginica
+7.7,3.0,6.1,2.3,Iris-virginica
+6.3,3.4,5.6,2.4,Iris-virginica
+6.4,3.1,5.5,1.8,Iris-virginica
+6.0,3.0,4.8,1.8,Iris-virginica
+6.9,3.1,5.4,2.1,Iris-virginica
+6.7,3.1,5.6,2.4,Iris-virginica
+6.9,3.1,5.1,2.3,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+6.8,3.2,5.9,2.3,Iris-virginica
+6.7,3.3,5.7,2.5,Iris-virginica
+6.7,3.0,5.2,2.3,Iris-virginica
+6.3,2.5,5.0,1.9,Iris-virginica
+6.5,3.0,5.2,2.0,Iris-virginica
+6.2,3.4,5.4,2.3,Iris-virginica
+5.9,3.0,5.1,1.8,Iris-virginica
+%
+%
+%
diff --git a/lib/Files/ArffFiles.cc b/lib/Files/ArffFiles.cc
new file mode 100644
index 0000000..4039b0b
--- /dev/null
+++ b/lib/Files/ArffFiles.cc
@@ -0,0 +1,170 @@
+#include "ArffFiles.h"
+#include <fstream>
+#include <sstream>
+#include <map>
+#include <iostream>
+
+using namespace std;
+
+ArffFiles::ArffFiles() = default;
+
+vector<string> ArffFiles::getLines() const
+{
+    return lines;
+}
+
+unsigned long int ArffFiles::getSize() const
+{
+    return lines.size();
+}
+
+vector<pair<string, string>> ArffFiles::getAttributes() const
+{
+    return attributes;
+}
+
+string ArffFiles::getClassName() const
+{
+    return className;
+}
+
+string ArffFiles::getClassType() const
+{
+    return classType;
+}
+
+vector<vector<float>>& ArffFiles::getX()
+{
+    return X;
+}
+
+vector<int>& ArffFiles::getY()
+{
+    return y;
+}
+
+void ArffFiles::loadCommon(string fileName)
+{
+    ifstream file(fileName);
+    if (!file.is_open()) {
+        throw invalid_argument("Unable to open file");
+    }
+    string line;
+    string keyword;
+    string attribute;
+    string type;
+    string type_w;
+    while (getline(file, line)) {
+        if (line.empty() || line[0] == '%' || line == "\r" || line == " ") {
+            continue;
+        }
+        if (line.find("@attribute") != string::npos || line.find("@ATTRIBUTE") != string::npos) {
+            stringstream ss(line);
+            ss >> keyword >> attribute;
+            type = "";
+            while (ss >> type_w)
+                type += type_w + " ";
+            attributes.emplace_back(trim(attribute), trim(type));
+            continue;
+        }
+        if (line[0] == '@') {
+            continue;
+        }
+        lines.push_back(line);
+    }
+    file.close();
+    if (attributes.empty())
+        throw invalid_argument("No attributes found");
+}
+
+void ArffFiles::load(const string& fileName, bool classLast)
+{
+    int labelIndex;
+    loadCommon(fileName);
+    if (classLast) {
+        className = get<0>(attributes.back());
+        classType = get<1>(attributes.back());
+        attributes.pop_back();
+        labelIndex = static_cast<int>(attributes.size());
+    } else {
+        className = get<0>(attributes.front());
+        classType = get<1>(attributes.front());
+        attributes.erase(attributes.begin());
+        labelIndex = 0;
+    }
+    generateDataset(labelIndex);
+}
+void ArffFiles::load(const string& fileName, const string& name)
+{
+    int labelIndex;
+    loadCommon(fileName);
+    bool found = false;
+    for (int i = 0; i < attributes.size(); ++i) {
+        if (attributes[i].first == name) {
+            className = get<0>(attributes[i]);
+            classType = get<1>(attributes[i]);
+            attributes.erase(attributes.begin() + i);
+            labelIndex = i;
+            found = true;
+            break;
+        }
+    }
+    if (!found) {
+        throw invalid_argument("Class name not found");
+    }
+    generateDataset(labelIndex);
+}
+
+void ArffFiles::generateDataset(int labelIndex)
+{
+    X = vector<vector<float>>(attributes.size(), vector<float>(lines.size()));
+    auto yy = vector<string>(lines.size(), "");
+    auto removeLines = vector<int>(); // Lines with missing values
+    for (size_t i = 0; i < lines.size(); i++) {
+        stringstream ss(lines[i]);
+        string value;
+        int pos = 0;
+        int xIndex = 0;
+        while (getline(ss, value, ',')) {
+            if (pos++ == labelIndex) {
+                yy[i] = value;
+            } else {
+                if (value == "?") {
+                    X[xIndex++][i] = -1;
+                    removeLines.push_back(i);
+                } else
+                    X[xIndex++][i] = stof(value);
+            }
+        }
+    }
+    for (auto i : removeLines) {
+        yy.erase(yy.begin() + i);
+        for (auto& x : X) {
+            x.erase(x.begin() + i);
+        }
+    }
+    y = factorize(yy);
+}
+
+string ArffFiles::trim(const string& source)
+{
+    string s(source);
+    s.erase(0, s.find_first_not_of(" '\n\r\t"));
+    s.erase(s.find_last_not_of(" '\n\r\t") + 1);
+    return s;
+}
+
+vector<int> ArffFiles::factorize(const vector<string>& labels_t)
+{
+    vector<int> yy;
+    yy.reserve(labels_t.size());
+    map<string, int> labelMap;
+    int i = 0;
+    for (const string& label : labels_t) {
+        if (labelMap.find(label) == labelMap.end()) {
+            labelMap[label] = i++;
+        }
+        yy.push_back(labelMap[label]);
+    }
+    return yy;
+}
\ No newline at end of file
diff --git a/lib/Files/ArffFiles.h b/lib/Files/ArffFiles.h
new file mode 100644
index 0000000..5cacb27
--- /dev/null
+++ b/lib/Files/ArffFiles.h
@@ -0,0 +1,34 @@
+#ifndef ARFFFILES_H
+#define ARFFFILES_H
+
+#include <string>
+#include <vector>
+
+using namespace std;
+
+class ArffFiles {
+private:
+    vector<string> lines;
+    vector<pair<string, string>> attributes;
+    string className;
+    string classType;
+    vector<vector<float>> X;
+    vector<int> y;
+    void generateDataset(int);
+    void loadCommon(string);
+public:
+    ArffFiles();
+    void load(const string&, bool = true);
+    void load(const string&, const string&);
+    vector<string> getLines() const;
+    unsigned long int getSize() const;
+    string getClassName() const;
+    string getClassType() const;
+    static string trim(const string&);
+    vector<vector<float>>& getX();
+    vector<int>& getY();
+    vector<pair<string, string>> getAttributes() const;
+    static vector<int> factorize(const vector<string>& labels_t);
+};
+
+#endif
\ No newline at end of file
diff --git a/lib/Files/CMakeLists.txt b/lib/Files/CMakeLists.txt
new file mode 100644
index 0000000..fce5b8f
--- /dev/null
+++ b/lib/Files/CMakeLists.txt
@@ -0,0 +1 @@
+add_library(ArffFiles ArffFiles.cc)
\ No newline at end of file
diff --git a/pspp.jnl b/pspp.jnl
new file mode 100644
index 0000000..cf047f4
--- /dev/null
+++ b/pspp.jnl
@@ -0,0 +1 @@
+GET FILE="/home/rmontanana/Code/covbench/data/covid_v9_20220630.sav".
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index c93ed54..f02df68 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -1,6 +1,8 @@
-
+include_directories(${PyWrap_SOURCE_DIR}/lib/Files)
 include_directories(${Python3_INCLUDE_DIRS})
 
 add_executable(main main.cc STree.cc SVC.cc PyClassifier.cc PyWrap.cc)
+add_executable(example example.cpp)
 
-target_link_libraries(main ${Python3_LIBRARIES} "${TORCH_LIBRARIES}")
+target_link_libraries(main ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ArffFiles)
+target_link_libraries(example "${TORCH_LIBRARIES}" ArffFiles)
diff --git a/src/PyClassifier.cc b/src/PyClassifier.cc
index 36cc41a..043ea5f 100644
--- a/src/PyClassifier.cc
+++ b/src/PyClassifier.cc
@@ -13,10 +13,13 @@ namespace pywrap {
         pyWrap->clean(module, className);
     }
 
-    template<typename T>
-    T PyClassifier::callMethod(const std::string& method)
+    std::string PyClassifier::callMethod(const std::string& method)
     {
-        return pyWrap->callMethod<T>(module, className, method);
+        return pyWrap->callMethodString(module, className, method);
+    }
+    PyClassifier& PyClassifier::fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states)
+    {
+
     }
 
 } /* namespace PyWrap */
\ No newline at end of file
diff --git a/src/PyClassifier.h b/src/PyClassifier.h
index a057664..13337ed 100644
--- a/src/PyClassifier.h
+++ b/src/PyClassifier.h
@@ -12,8 +12,7 @@ namespace pywrap {
         PyClassifier(const std::string& module, const std::string& className);
         virtual ~PyClassifier();
         PyClassifier& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states);
-        template <typename T>
-        T callMethod(const std::string& method);
+        std::string callMethod(const std::string& method);
     private:
         PyWrap* pyWrap;
         std::string module;
diff --git a/src/PyWrap.cc b/src/PyWrap.cc
index d711705..5cc51ed 100644
--- a/src/PyWrap.cc
+++ b/src/PyWrap.cc
@@ -102,6 +102,24 @@ namespace pywrap {
         Py_DECREF(result);
         return value;
     }
+    std::string PyWrap::callMethodString(const std::string& moduleName, const std::string& className, const std::string& method)
+    {
+        std::cout << "Llamando método" << std::endl;
+        auto item = moduleClassMap.find({ moduleName, className });
+        if (item == moduleClassMap.end()) {
+            errorAbort("Module " + moduleName + " and class " + className + " not found");
+        }
+        std::cout << "Clase encontrada" << std::endl;
+        PyObject* instance = std::get<2>(item->second);
+        PyObject* result;
+        if (!(result = PyObject_CallMethod(instance, method.c_str(), NULL)))
+            errorAbort("Couldn't call method " + method);
+
+        std::string value = PyUnicode_AsUTF8(result);
+        std::cout << "Result: " << value << std::endl;
+        Py_DECREF(result);
+        return value;
+    }
     // void PyWrap::doCommand2()
     // {
     //     PyObject* list = Py_BuildValue("[s]", "Stree");
diff --git a/src/PyWrap.h b/src/PyWrap.h
index c5d4537..82b9ce9 100644
--- a/src/PyWrap.h
+++ b/src/PyWrap.h
@@ -18,16 +18,17 @@ namespace pywrap {
         ~PyWrap();
         template<typename T>
         T callMethod(const std::string& moduleName, const std::string& className, const std::string& method);
-        template<typename T> T returnMethod(PyObject* result);
-        template<std::string> std::string returnMethod(PyObject* result);
-        template<int> int returnMethod(PyObject* result);
-        template<bool> bool returnMethod(PyObject* result);
-        template<torch::Tensor> torch::Tensor returnMethod(PyObject* result)
-        {
-            // PyObject* THPVariable_Wrap(at::Tensor t);
-            // at::Tensor& THPVariable_Unpack(PyObject * obj);
-            return THPVariable_Unpack(result);
-        };
+        std::string callMethodString(const std::string& moduleName, const std::string& className, const std::string& method);
+        // template<typename T> T returnMethod(PyObject* result);
+        // template<std::string> std::string returnMethod(PyObject* result);
+        // template<int> int returnMethod(PyObject* result);
+        // template<bool> bool returnMethod(PyObject* result);
+        // template<torch::Tensor> torch::Tensor returnMethod(PyObject* result)
+        // {
+        //     // PyObject* THPVariable_Wrap(at::Tensor t);
+        //     // at::Tensor& THPVariable_Unpack(PyObject * obj);
+        //     return THPVariable_Unpack(result);
+        // };
         void importClass(const std::string& moduleName, const std::string& className);
         void clean(const std::string& moduleName, const std::string& className);
         // void doCommand2();
diff --git a/src/STree.cc b/src/STree.cc
index 669b15f..e138601 100644
--- a/src/STree.cc
+++ b/src/STree.cc
@@ -5,7 +5,7 @@ namespace pywrap {
 
     void STree::version()
     {
-        std::cout << "Version: " << callMethod<std::string>("version") << std::endl;
+        std::cout << "Version: " << callMethod("version") << std::endl;
     }
 
 } /* namespace pywrap */
\ No newline at end of file
diff --git a/src/SVC.cc b/src/SVC.cc
index d247c06..2d432c6 100644
--- a/src/SVC.cc
+++ b/src/SVC.cc
@@ -5,7 +5,7 @@ namespace pywrap {
 
     void SVC::version()
     {
-        //std::cout << "repr_html: " << callMethod<std::string>("_repr_html_") << std::endl;
+        std::cout << "repr_html: " << callMethod("_repr_html_") << std::endl;
     }
 
 } /* namespace pywrap */
\ No newline at end of file
diff --git a/src/example.cpp b/src/example.cpp
index e738315..eb4803f 100644
--- a/src/example.cpp
+++ b/src/example.cpp
@@ -1,7 +1,10 @@
+#include <torch/torch.h>
+#include "ArffFiles.h"
 #include<string>
 #include<iostream>
 
 using namespace std;
+using namespace torch;
 class Test {
 public:
     Test(const string& c) : c(c) {};
@@ -13,18 +16,45 @@ public:
         std::cout << "Llamando a metodo" << std::endl;
         return parameter;
     }
-
-
 private:
     string c;
-
 };
 
+tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(const string& name, bool class_last)
+{
+    auto handler = ArffFiles();
+    handler.load(static_cast<string>(name) + ".arff", class_last);
+    // Get Dataset X, y
+    vector<vector<float>> X = handler.getX();
+    vector<int> y = handler.getY();
+    // // Get className & Features
+    auto className = handler.getClassName();
+    vector<string> features;
+    auto attributes = handler.getAttributes();
+    transform(attributes.begin(), attributes.end(), back_inserter(features), [](const auto& pair) { return pair.first; });
+    torch::Tensor Xd;
+    auto states = map<string, vector<int>>();
+    auto yt = torch::tensor(y, torch::kInt32);
+    Xd = torch::zeros({ static_cast<int>(X.size()), static_cast<int>(X[0].size()) }, torch::kFloat32);
+    for (int i = 0; i < features.size(); ++i) {
+        Xd.index_put_({ i, "..." }, torch::tensor(X[i], torch::kFloat32));
+    }
+    return make_tuple(Xd, yt, features, className, states);
+}
+
 int main()
 {
     Test t("hola");
     cout << t.callMethod<string>("hola") << endl;
     cout << t.callMethod<int>(1) << endl;
     cout << t.callMethod<double>(7.3) << endl;
+    vector<vector<float>> X;
+    vector<int> y = { 1, 2, 3 };
+    X.push_back({ 1.1, 2.2, 3.3 });
+    vector<float> v = { 1.1, 2.2, 3.3 };
+    torch::Tensor matrix = torch::tensor(X[0], torch::kFloat32);
+    cout << "X:" << matrix << endl;
+    cout << "y:" << torch::tensor(y, torch::kInt32) << endl;
+
     return 0;
 }
\ No newline at end of file
diff --git a/src/main.cc b/src/main.cc
index 37e33a1..cc7283a 100644
--- a/src/main.cc
+++ b/src/main.cc
@@ -1,10 +1,48 @@
+#include <torch/torch.h>
+#include "ArffFiles.h"
+#include <vector>
+#include <string>
+#include <iostream>
+#include <map>
+#include <tuple>
 #include "STree.h"
 #include "SVC.h"
 
+using namespace std;
+using namespace torch;
+
+class Paths {
+public:
+    static string datasets()
+    {
+        return "/home/rmontanana/Code/discretizbench/datasets/";
+    }
+};
+
+tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(const string& name, bool class_last)
+{
+    auto handler = ArffFiles();
+    handler.load(Paths::datasets() + static_cast<string>(name) + ".arff", class_last);
+    // Get Dataset X, y
+    vector<vector<float>> X = handler.getX();
+    vector<int> y = handler.getY();
+    // Get className & Features
+    auto className = handler.getClassName();
+    vector<string> features;
+    auto attributes = handler.getAttributes();
+    transform(attributes.begin(), attributes.end(), back_inserter(features), [](const auto& pair) { return pair.first; });
+    Tensor Xd;
+    auto states = map<string, vector<int>>();
+    Xd = torch::zeros({ static_cast<int>(X.size()), static_cast<int>(X[0].size()) }, torch::kFloat32);
+    for (int i = 0; i < features.size(); ++i) {
+        Xd.index_put_({ i, "..." }, torch::tensor(X[i], torch::kFloat32));
+    }
+    return { Xd, torch::tensor(y, torch::kInt32), features, className, states };
+}
+
 int main(int argc, char* argv[])
 {
-    // auto wrap = pywrap::PyWrap("stree", "Stree");
-    // wrap.callMethod("version");
+    auto [X, y, features, className, states] = loadDataset("iris", true);
     auto stree = pywrap::STree();
     stree.version();
     auto svc = pywrap::SVC();