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annotate test_mlp.py @ 183:25d0a0c713da

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did some debugging of test_mlp
author Olivier Breuleux <breuleuo@iro.umontreal.ca>
date Tue, 13 May 2008 18:30:08 -0400
parents 2698c0feeb54
children 562f308873f0
rev   line source
121
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1
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2 from mlp import *
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3 import dataset
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4
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5
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6 from functools import partial
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7 def separator(debugger, i, node, *ths):
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8 print "==================="
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9
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10 def what(debugger, i, node, *ths):
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11 print "#%i" % i, node
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12
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13 def parents(debugger, i, node, *ths):
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14 print [input.step for input in node.inputs]
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15
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16 def input_shapes(debugger, i, node, *ths):
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17 print "input shapes: ",
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18 for r in node.inputs:
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19 if hasattr(r.value, 'shape'):
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20 print r.value.shape,
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21 else:
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22 print "no_shape",
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23 print
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24
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25 def input_types(debugger, i, node, *ths):
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26 print "input types: ",
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27 for r in node.inputs:
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28 print r.type,
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29 print
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30
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31 def output_shapes(debugger, i, node, *ths):
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32 print "output shapes:",
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33 for r in node.outputs:
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34 if hasattr(r.value, 'shape'):
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35 print r.value.shape,
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36 else:
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37 print "no_shape",
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38 print
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39
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40 def output_types(debugger, i, node, *ths):
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41 print "output types:",
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42 for r in node.outputs:
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43 print r.type,
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44 print
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45
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46
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47 def test0():
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48 linker = 'c|py'
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49 #linker = partial(theano.gof.DebugLinker, linkers = [theano.gof.OpWiseCLinker],
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50 # debug_pre = [separator, what, parents, input_types, input_shapes],
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51 # debug_post = [output_shapes, output_types],
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52 # compare_fn = lambda x, y: numpy.all(x == y))
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53
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54 nnet = OneHiddenLayerNNetClassifier(10,2,.001,1000, linker = linker)
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55 training_set = dataset.ArrayDataSet(numpy.array([[0, 0, 0],
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56 [0, 1, 1],
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57 [1, 0, 1],
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58 [1, 1, 1]]),
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59 {'input':slice(2),'target':2})
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60 fprop=nnet(training_set)
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62 output_ds = fprop(training_set)
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64 for fieldname in output_ds.fieldNames():
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65 print fieldname+"=",output_ds[fieldname]
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67 test0()
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68