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annotate doc/v2_planning/plugin_JB.py @ 1211:e7ac87720fee

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v2planning plugin_JB - added PRINT and POPEN to demonstrate parallel async. control flows
author James Bergstra <bergstrj@iro.umontreal.ca>
date Wed, 22 Sep 2010 00:23:07 -0400
parents cbe1fb32686c
children 478bb1f8215c
rev   line source
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1 """plugin_JB - draft of potential library architecture using iterators
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2
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3 This strategy makes use of a simple imperative language whose statements are python function
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4 calls to create learning algorithms that can be manipulated and executed in several desirable
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5 ways.
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6
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7 The training procedure for a PCA module is easy to express:
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8
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9 # allocate the relevant modules
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10 dataset = Dataset(numpy.random.RandomState(123).randn(13,1))
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11 pca = PCA_Analysis()
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12 pca_batchsize=1000
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13
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14 # define the control-flow of the algorithm
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15 train_pca = SEQ([
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16 BUFFER_REPEAT(pca_batchsize, CALL(dataset.next)),
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17 FILT(pca.analyze)])
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18
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19 # run the program
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20 train_pca.run()
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21
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22 The CALL, SEQ, FILT, and BUFFER_REPEAT are control-flow elements. The control-flow elements I
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23 defined so far are:
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24
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25 - CALL - a basic statement, just calls a python function
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26 - FILT - like call, but passes the return value of the last CALL or FILT to the python function
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27 - SEQ - a sequence of elements to run in order
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28 - REPEAT - do something N times (and return None or maybe the last CALL?)
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29 - BUFFER_REPEAT - do something N times and accumulate the return value from each iter
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30 - LOOP - do something an infinite number of times
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31 - CHOOSE - like a switch statement (should rename to SWITCH)
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32 - WEAVE - interleave execution of multiple control-flow elements
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33 - POPEN - launch a process and return its status when it's complete
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34 - PRINT - a shortcut for CALL(print_obj)
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35
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36
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37 We don't have many requirements per-se for the architecture, but I think this design respects
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38 and realizes all of them.
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39 The advantages of this approach are:
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40
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41 - algorithms (including partially run ones) are COPYABLE, and SERIALIZABLE
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42
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43 - algorithms can be executed without seizing control of the python process (the run()
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44 method does this, but if you look inside it you'll see it's a simple for loop)
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45
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46 - it is easy to execute an algorithm step by step in a main loop that also checks for
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47 network or filesystem events related to e.g. job management.
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48
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49 - the library can provide learning algorithms via control-flow templates, and the user can
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50 edit them (with search/replace calls) to include HOOKS, and DIAGNOSTIC plug-in
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51 functionality
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52
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53 e.g. prog.find(CALL(cd1_update, layer=layer1)).replace_with(
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54 SEQ([CALL(cd1_update, layer=layer1), CALL(my_debugfn)]))
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55
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56 - user can print the 'program code' of an algorithm built from library pieces
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57
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58 - program can be optimized automatically.
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59
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60 - e.g. BUFFER(N, CALL(dataset.next)) could be replaced if dataset.next implements the
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61 right attribute/protocol for 'bufferable' or something.
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62
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63 - e.g. SEQ([a,b,c,d]) could be compiled to a single CALL to a Theano-compiled function
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64 if a, b, c, and d are calls to callable objects that export something like a
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65 'theano_SEQ' interface
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67
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68 """
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69
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70 __license__ = 'TODO'
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71 __copyright__ = 'TODO'
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72
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73 import cPickle, copy, subprocess, sys, time
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74 import numpy
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75
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76 ####################################################
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77 # CONTROL-FLOW CONSTRUCTS
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78
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79 class INCOMPLETE:
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80 """Return value for Element.step"""
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81
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82 class ELEMENT(object):
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83 """
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84 Base class for control flow elements (e.g. CALL, REPEAT, etc.)
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85
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86 The design is that every element has a driver, that is another element, or the iterator
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87 implementation in the ELEMENT class.
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88
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89 the driver calls start when entering a new control element
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90 - this would be called once per e.g. outer loop iteration
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91
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92 the driver calls step to advance the control element
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93 - which returns INCOMPLETE
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94 - which returns any other object to indicate completion
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95 """
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96
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97 # subclasses should override these methods:
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98 def start(self, arg):
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99 pass
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100 def step(self):
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101 pass
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102
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103 # subclasses should typically not override these:
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104 def run(self, arg=None, n_steps=float('inf')):
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105 self.start(arg)
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106 i = 0
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107 r = self.step()
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108 while r is INCOMPLETE:
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109 i += 1
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110 #TODO make sure there is not an off-by-one error
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111 if i > n_steps:
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112 break
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113 r = self.step()
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114 return r
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115
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116 class BUFFER_REPEAT(ELEMENT):
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117 """
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118 Accumulate a number of return values into one list / array.
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119
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120 The source of return values `src` is a control element that will be restarted repeatedly in
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121 order to fulfil the requiement of gathering N samples.
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122
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123 TODO: support accumulating of tuples of arrays
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124 """
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125 def __init__(self, N, src, storage=None):
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126 """
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127 TODO: use preallocated `storage`
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128 """
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129 self.N = N
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130 self.n = 0
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131 self.src = src
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132 self.storage = storage
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133 self.src.start(None)
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134 if self.storage != None:
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135 raise NotImplementedError()
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136 def start(self, arg):
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137 self.buf = [None] * self.N
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parents:
diff changeset
138 self.n = 0
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parents:
diff changeset
139 self.finished = False
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
140 def step(self):
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parents:
diff changeset
141 assert not self.finished
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parents:
diff changeset
142 r = self.src.step()
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
143 if r is INCOMPLETE:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
144 return r
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
145 self.src.start(None) # restart our stream
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
146 self.buf[self.n] = r
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
147 self.n += 1
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
148 if self.n == self.N:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
149 self.finished = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
150 return self.buf
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
151 else:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
152 return INCOMPLETE
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
153 assert 0
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parents:
diff changeset
154
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
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155 class CALL(ELEMENT):
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parents:
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156 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
157 Control flow terminal - call a python function or method.
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
158
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parents:
diff changeset
159 Returns the return value of the call.
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
160 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
161 def __init__(self, fn, *args, **kwargs):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
162 self.fn = fn
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
163 self.args = args
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
164 self.kwargs=kwargs
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
165 self.use_start_arg = kwargs.pop('use_start_arg', False)
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parents:
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166 def start(self, arg):
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diff changeset
167 self.start_arg = arg
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
168 self.finished = False
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
169 return self
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
170 def step(self):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
171 assert not self.finished
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
172 self.finished = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
173 if self.use_start_arg:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
174 if self.args:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
175 raise TypeError('cant get positional args both ways')
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
176 return self.fn(self.start_arg, **self.kwargs)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
177 else:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
178 return self.fn(*self.args, **self.kwargs)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
179 def __getstate__(self):
1199
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parents: 1198
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180 rval = dict(self.__dict__)
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
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181 if type(self.fn) is type(self.step): #instancemethod
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
182 fn = rval.pop('fn')
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
183 rval['i fn'] = fn.im_func, fn.im_self, fn.im_class
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
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184 return rval
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
185 def __setstate__(self, dct):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
186 if 'i fn' in dct:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
187 dct['fn'] = type(self.step)(*dct.pop('i fn'))
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
188 self.__dict__.update(dct)
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parents:
diff changeset
189
1199
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parents: 1198
diff changeset
190 def FILT(fn, **kwargs):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1198
diff changeset
191 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1198
diff changeset
192 Return a CALL object that uses the return value from the previous CALL as the first and
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1198
diff changeset
193 only positional argument.
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1198
diff changeset
194 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1198
diff changeset
195 return CALL(fn, use_start_arg=True, **kwargs)
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
196
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
197 def CHOOSE(which, options):
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parents:
diff changeset
198 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
199 Execute one out of a number of optional control flow paths
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
200 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
201 raise NotImplementedError()
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
202
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
203 def LOOP(elements):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
204 #TODO: implement a true infinite loop
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
205 try:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
206 iter(elements)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
207 return REPEAT(sys.maxint, elements)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
208 except TypeError:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
209 return REPEAT(sys.maxint, [elements])
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
210
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
211 class REPEAT(ELEMENT):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
212 def __init__(self, N, elements, pass_rvals=False):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
213 self.N = N
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
214 self.elements = elements
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
215 self.pass_rvals = pass_rvals
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1200
diff changeset
216
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
217 #TODO: check for N being callable
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
218 def start(self, arg):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
219 self.n = 0 #loop iteration
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
220 self.idx = 0 #element idx
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
221 self.finished = False
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
222 self.elements[0].start(arg)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
223 def step(self):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
224 assert not self.finished
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
225 r = self.elements[self.idx].step()
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
226 if r is INCOMPLETE:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
227 return INCOMPLETE
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
228 self.idx += 1
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
229 if self.idx < len(self.elements):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
230 self.elements[self.idx].start(r)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
231 return INCOMPLETE
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
232 self.n += 1
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
233 if self.n < self.N:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
234 self.idx = 0
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
235 self.elements[self.idx].start(r)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
236 return INCOMPLETE
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
237 else:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
238 self.finished = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
239 return r
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
240
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
241 def SEQ(elements):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
242 return REPEAT(1, elements)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
243
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
244 class WEAVE(ELEMENT):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
245 """
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
246 Interleave execution of a number of elements.
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
247
1387771296a8 v2planning adding plugin_JB
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
248 TODO: allow a schedule (at least relative frequency) of elements from each program
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
249 """
1210
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
250 def __init__(self, n_required, elements):
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
251 self.elements = elements
1210
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
252 if n_required == -1:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
253 self.n_required = len(elements)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
254 else:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
255 self.n_required = n_required
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
256 def start(self, arg):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
257 for el in self.elements:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
258 el.start(arg)
1210
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
259 self.elem_finished = [0] * len(self.elements)
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
260 self.idx = 0
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
261 self.finished= False
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
262 def step(self):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
263 assert not self.finished # if this is triggered, we have a broken driver
1210
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
264
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
265 #start with this check in case there were no elements
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
266 # it's possible for the number of finished elements to exceed the threshold
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
267 if sum(self.elem_finished) >= self.n_required:
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
268 self.finished = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
269 return None
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
270
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
271 # step the active element
1198
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parents:
diff changeset
272 r = self.elements[self.idx].step()
1210
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
273
1198
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James Bergstra <bergstrj@iro.umontreal.ca>
parents:
diff changeset
274 if r is not INCOMPLETE:
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parents: 1203
diff changeset
275 self.elem_finished[self.idx] = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
276
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
277 # check for completion
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
278 if sum(self.elem_finished) >= self.n_required:
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
279 self.finished = True
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
280 return None
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
281
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
282 # advance to the next un-finished element
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
283 self.idx = (self.idx+1) % len(self.elements)
cbe1fb32686c v2planning plugin_JB - added n_required keyword to WEAVE
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1203
diff changeset
284 while self.elem_finished[self.idx]:
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285 self.idx = (self.idx+1) % len(self.elements)
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286
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287 return INCOMPLETE
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288
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289 class POPEN(ELEMENT):
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290 def __init__(self, args):
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291 self.args = args
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292 def start(self, arg):
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293 self.p = subprocess.Popen(self.args)
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294 def step(self):
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295 r = self.p.poll()
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296 if r is None:
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297 return INCOMPLETE
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298 return r
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299
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300 def PRINT(obj):
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301 return CALL(print_obj, obj)
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302
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303 ####################################################
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304 # [Dummy] Components involved in learning algorithms
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305
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306 class Dataset(object):
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307 def __init__(self, data):
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308 self.pos = 0
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309 self.data = data
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310 def next(self):
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311 rval = self.data[self.pos]
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312 self.pos += 1
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313 if self.pos == len(self.data):
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314 self.pos = 0
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315 return rval
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316 def seek(self, pos):
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317 self.pos = pos
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318
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319 class KFold(object):
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320 def __init__(self, data, K):
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321 self.data = data
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322 self.k = -1
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323 self.scores = [None]*K
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324 self.K = K
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325 def next_fold(self):
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326 self.k += 1
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327 self.data.seek(0) # restart the stream
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328 def next(self):
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329 #TODO: skip the examples that are ommitted in this split
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330 return self.data.next()
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331 def init_test(self):
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332 pass
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333 def next_test(self):
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334 return self.data.next()
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335 def test_size(self):
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336 return 5
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337 def store_scores(self, scores):
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338 self.scores[self.k] = scores
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339
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340 def prog(self, clear, train, test):
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341 return REPEAT(self.K, [
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342 CALL(self.next_fold),
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343 clear,
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344 train,
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345 CALL(self.init_test),
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346 BUFFER_REPEAT(self.test_size(),
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347 SEQ([ CALL(self.next_test), test])),
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348 FILT(self.store_scores) ])
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349
1198
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350 class PCA_Analysis(object):
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351 def __init__(self):
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352 self.clear()
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353
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354 def clear(self):
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355 self.mean = 0
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356 self.eigvecs=0
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357 self.eigvals=0
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358 def analyze(self, X):
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359 self.mean = numpy.mean(X, axis=0)
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360 self.eigvecs=1
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361 self.eigvals=1
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362 def filt(self, X):
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363 return (X - self.mean) * self.eigvecs #TODO: divide by root eigvals?
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364 def pseudo_inverse(self, Y):
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365 return Y
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366
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367 class Layer(object):
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368 def __init__(self, w):
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369 self.w = w
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370 def filt(self, x):
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371 return self.w*x
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372 def clear(self):
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373 self.w =0
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374
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375 def print_obj(obj):
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376 print obj
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377 def print_obj_attr(obj, attr):
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378 print getattr(obj, attr)
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379 def no_op(*args, **kwargs):
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parents:
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380 pass
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381
1199
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382 def cd1_update(X, layer, lr):
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diff changeset
383 # update self.layer from observation X
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diff changeset
384 layer.w += X.mean() * lr #TODO: not exactly correct math!
1198
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385
1211
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diff changeset
386
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387 ###############################################################
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388 # Example algorithms written in this control flow mini-language
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389
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diff changeset
390 def main_weave():
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391 # Uses weave to demonstrate the interleaving of two bufferings of a single stream
1198
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parents:
diff changeset
392
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parents:
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393 l = [0]
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parents:
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394 def f(a):
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parents:
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395 print l
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parents:
diff changeset
396 l[0] += a
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parents:
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397 return l[0]
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diff changeset
398
1210
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diff changeset
399 print WEAVE(1, [
1198
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parents:
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400 BUFFER_REPEAT(3,CALL(f,1)),
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parents:
diff changeset
401 BUFFER_REPEAT(5,CALL(f,1)),
1203
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diff changeset
402 ]).run()
1198
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parents:
diff changeset
403
1211
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diff changeset
404 def main_weave_popen():
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parents: 1210
diff changeset
405 # Uses weave and Popen to demonstrate the control of a program with some asynchronous
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diff changeset
406 # parallelism
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parents: 1210
diff changeset
407
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parents: 1210
diff changeset
408 p = WEAVE(2,[
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diff changeset
409 SEQ([POPEN(['sleep', '5']), PRINT('done 1')]),
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parents: 1210
diff changeset
410 SEQ([POPEN(['sleep', '10']), PRINT('done 2')]),
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diff changeset
411 LOOP([
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diff changeset
412 CALL(print_obj, 'polling...'),
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parents: 1210
diff changeset
413 CALL(time.sleep, 1)])])
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parents: 1210
diff changeset
414 # The LOOP would forever if the WEAVE were not configured to stop after 2 of its elements
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parents: 1210
diff changeset
415 # complete.
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parents: 1210
diff changeset
416
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1210
diff changeset
417 p.run()
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parents: 1210
diff changeset
418 # Note that the program can be run multiple times...
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parents: 1210
diff changeset
419 p.run()
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parents: 1210
diff changeset
420
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 1210
diff changeset
421 main = main_weave_popen
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parents: 1210
diff changeset
422 def main_kfold_dbn():
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parents: 1210
diff changeset
423 # Uses many of the control-flow elements to define the k-fold evaluation of a dbn
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424 # The algorithm is not quite right, but the example shows off all of the required
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425 # control-flow elements I think.
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426
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427 # create components
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428 dataset = Dataset(numpy.random.RandomState(123).randn(13,1))
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429 pca = PCA_Analysis()
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430 layer1 = Layer(w=4)
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431 layer2 = Layer(w=3)
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432 kf = KFold(dataset, K=10)
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433
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434 pca_batchsize=1000
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435 cd_batchsize = 5
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436 n_cd_updates_layer1 = 10
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437 n_cd_updates_layer2 = 10
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438
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439 # create algorithm
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440
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441 train_pca = SEQ([
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442 BUFFER_REPEAT(pca_batchsize, CALL(kf.next)),
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443 FILT(pca.analyze)])
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444
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445 train_layer1 = REPEAT(n_cd_updates_layer1, [
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446 BUFFER_REPEAT(cd_batchsize, CALL(kf.next)),
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447 FILT(pca.filt),
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448 FILT(cd1_update, layer=layer1, lr=.01)])
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449
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450 train_layer2 = REPEAT(n_cd_updates_layer2, [
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451 BUFFER_REPEAT(cd_batchsize, CALL(kf.next)),
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452 FILT(pca.filt),
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453 FILT(layer1.filt),
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454 FILT(cd1_update, layer=layer2, lr=.01)])
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455
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456 kfold_prog = kf.prog(
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457 clear = SEQ([ # FRAGMENT 1: this bit is the reset/clear stage
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458 CALL(pca.clear),
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459 CALL(layer1.clear),
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460 CALL(layer2.clear),
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461 ]),
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462 train = SEQ([
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463 train_pca,
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464 WEAVE(1, [ # Silly example of how to do debugging / loggin with WEAVE
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465 train_layer1,
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466 LOOP(CALL(print_obj_attr, layer1, 'w'))]),
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467 train_layer2,
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468 ]),
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469 test=SEQ([
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470 FILT(pca.filt), # may want to allow this SEQ to be
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471 FILT(layer1.filt), # optimized into a shorter one that
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472 FILT(layer2.filt), # compiles these calls together with
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473 FILT(numpy.mean)])) # Theano
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474
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475 pkg1 = dict(prog=kfold_prog, kf=kf)
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476 pkg2 = copy.deepcopy(pkg1) # programs can be copied
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477
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478 try:
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479 pkg3 = cPickle.loads(cPickle.dumps(pkg1))
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480 except:
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481 print >> sys.stderr, "pickling doesnt work, but it can be fixed I think"
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482
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483 pkg = pkg2
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484
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485 # running a program updates the variables in its package, but not the other package
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486 pkg['prog'].run()
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487 print pkg['kf'].scores
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488
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489
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490 if __name__ == '__main__':
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491 sys.exit(main())
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492