annotate dataset.py @ 268:3f1cd8897fda

reverting dataset
author James Bergstra <bergstrj@iro.umontreal.ca>
date Wed, 04 Jun 2008 18:48:50 -0400
parents 6e69fb91f3c0
children fdce496c3b56
rev   line source
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2 from lookup_list import LookupList
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3 Example = LookupList
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4 from misc import unique_elements_list_intersection
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5 from string import join
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6 from sys import maxint
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7 import numpy, copy
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9 from exceptions import *
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11 class AttributesHolder(object):
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12 def __init__(self): pass
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14 def attributeNames(self):
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15 raise AbstractFunction()
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17 def setAttributes(self,attribute_names,attribute_values,make_copies=False):
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18 """
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19 Allow the attribute_values to not be a list (but a single value) if the attribute_names is of length 1.
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20 """
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21 if len(attribute_names)==1 and not (isinstance(attribute_values,list) or isinstance(attribute_values,tuple) ):
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22 attribute_values = [attribute_values]
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23 if make_copies:
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24 for name,value in zip(attribute_names,attribute_values):
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25 self.__setattr__(name,copy.deepcopy(value))
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26 else:
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27 for name,value in zip(attribute_names,attribute_values):
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28 self.__setattr__(name,value)
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30 def getAttributes(self,attribute_names=None, return_copy=False):
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31 """
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32 Return all (if attribute_names=None, in the order of attributeNames()) or a specified subset of attributes.
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33 """
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34 if attribute_names is None:
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35 attribute_names = self.attributeNames()
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36 if return_copy:
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37 return [copy.copy(self.__getattribute__(name)) for name in attribute_names]
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38 else:
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39 return [self.__getattribute__(name) for name in attribute_names]
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42 class DataSet(AttributesHolder):
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43 """A virtual base class for datasets.
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44
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45 A DataSet can be seen as a generalization of a matrix, meant to be used in conjunction
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46 with learning algorithms (for training and testing them): rows/records are called examples, and
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47 columns/attributes are called fields. The field value for a particular example can be an arbitrary
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48 python object, which depends on the particular dataset.
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49
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50 We call a DataSet a 'stream' when its length is unbounded (in which case its __len__ method
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51 should return sys.maxint).
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52
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53 A DataSet is a generator of iterators; these iterators can run through the
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54 examples or the fields in a variety of ways. A DataSet need not necessarily have a finite
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55 or known length, so this class can be used to interface to a 'stream' which
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56 feeds on-line learning (however, as noted below, some operations are not
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57 feasible or not recommended on streams).
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58
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59 To iterate over examples, there are several possibilities:
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60 - for example in dataset:
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61 - for val1,val2,... in dataset:
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62 - for example in dataset(field1, field2,field3, ...):
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63 - for val1,val2,val3 in dataset(field1, field2,field3):
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64 - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N):
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65 - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N):
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66 Each of these is documented below. All of these iterators are expected
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67 to provide, in addition to the usual 'next()' method, a 'next_index()' method
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68 which returns a non-negative integer pointing to the position of the next
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69 example that will be returned by 'next()' (or of the first example in the
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70 next minibatch returned). This is important because these iterators
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71 can wrap around the dataset in order to do multiple passes through it,
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72 in possibly unregular ways if the minibatch size is not a divisor of the
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73 dataset length.
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75 To iterate over fields, one can do
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76 - for field in dataset.fields():
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77 for field_value in field: # iterate over the values associated to that field for all the dataset examples
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78 - for field in dataset(field1,field2,...).fields() to select a subset of fields
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79 - for field in dataset.fields(field1,field2,...) to select a subset of fields
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80 and each of these fields is iterable over the examples:
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81 - for field_examples in dataset.fields():
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82 for example_value in field_examples:
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83 ...
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84 but when the dataset is a stream (unbounded length), it is not recommended to do
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85 such things because the underlying dataset may refuse to access the different fields in
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86 an unsynchronized ways. Hence the fields() method is illegal for streams, by default.
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87 The result of fields() is a L{DataSetFields} object, which iterates over fields,
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88 and whose elements are iterable over examples. A DataSetFields object can
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89 be turned back into a DataSet with its examples() method::
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90 dataset2 = dataset1.fields().examples()
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91 and dataset2 should behave exactly like dataset1 (in fact by default dataset2==dataset1).
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92
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93 Note: Fields are not mutually exclusive, i.e. two fields can overlap in their actual content.
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94
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95 Note: The content of a field can be of any type. Field values can also be 'missing'
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96 (e.g. to handle semi-supervised learning), and in the case of numeric (numpy array)
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97 fields (i.e. an ArrayFieldsDataSet), NaN plays the role of a missing value.
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98 What about non-numeric values? None.
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99
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100 Dataset elements can be indexed and sub-datasets (with a subset
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101 of examples) can be extracted. These operations are not supported
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102 by default in the case of streams.
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103
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104 - dataset[:n] returns a dataset with the n first examples.
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105
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106 - dataset[i1:i2:s] returns a dataset with the examples i1,i1+s,...i2-s.
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107
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108 - dataset[i] returns an Example.
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109
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110 - dataset[[i1,i2,...in]] returns a dataset with examples i1,i2,...in.
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111
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112 - dataset[fieldname] an iterable over the values of the field fieldname across
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113 the dataset (the iterable is obtained by default by calling valuesVStack
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114 over the values for individual examples).
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115
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116 - dataset.<property> returns the value of a property associated with
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117 the name <property>. The following properties should be supported:
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118 - 'description': a textual description or name for the dataset
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119 - 'fieldtypes': a list of types (one per field)
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120 A DataSet may have other attributes that it makes visible to other objects. These are
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121 used to store information that is not example-wise but global to the dataset.
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122 The list of names of these attributes is given by the attribute_names() method.
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123
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124 Datasets can be concatenated either vertically (increasing the length) or
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125 horizontally (augmenting the set of fields), if they are compatible, using
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126 the following operations (with the same basic semantics as numpy.hstack
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127 and numpy.vstack):
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128
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129 - dataset1 | dataset2 | dataset3 == dataset.hstack([dataset1,dataset2,dataset3])
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130
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131 creates a new dataset whose list of fields is the concatenation of the list of
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132 fields of the argument datasets. This only works if they all have the same length.
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133
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134 - dataset1 & dataset2 & dataset3 == dataset.vstack([dataset1,dataset2,dataset3])
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135
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136 creates a new dataset that concatenates the examples from the argument datasets
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137 (and whose length is the sum of the length of the argument datasets). This only
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138 works if they all have the same fields.
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139
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140 According to the same logic, and viewing a DataSetFields object associated to
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141 a DataSet as a kind of transpose of it, fields1 & fields2 concatenates fields of
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142 a DataSetFields fields1 and fields2, and fields1 | fields2 concatenates their
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143 examples.
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144
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145 A dataset can hold arbitrary key-value pairs that may be used to access meta-data
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146 or other properties of the dataset or associated with the dataset or the result
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147 of a computation stored in a dataset. These can be accessed through the [key] syntax
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148 when key is a string (or more specifically, neither an integer, a slice, nor a list).
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149
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150 A DataSet sub-class should always redefine the following methods:
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151 - __len__ if it is not a stream
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152 - fieldNames
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153 - minibatches_nowrap (called by DataSet.minibatches())
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154 - valuesHStack
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155 - valuesVStack
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156 For efficiency of implementation, a sub-class might also want to redefine
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157 - hasFields
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158 - __getitem__ may not be feasible with some streams
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159 - __iter__
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160 A sub-class should also append attributes to self._attribute_names
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161 (the default value returned by attributeNames()).
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162 By convention, attributes not in attributeNames() should have a name
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163 starting with an underscore.
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164 @todo enforce/test that convention!
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165 """
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166
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167 numpy_vstack = lambda fieldname,values: numpy.vstack(values)
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168 numpy_hstack = lambda fieldnames,values: numpy.hstack(values)
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169
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170 def __init__(self,description=None,fieldtypes=None):
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171 if description is None:
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172 # by default return "<DataSetType>(<SuperClass1>,<SuperClass2>,...)"
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173 description = type(self).__name__ + " ( " + join([x.__name__ for x in type(self).__bases__]) + " )"
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174 self.description=description
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175 self.fieldtypes=fieldtypes
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176 self._attribute_names = ["description"]
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177 if fieldtypes:
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178 self._attribute_names.append("fieldtypes")
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179
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180 def attributeNames(self): return self._attribute_names
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181
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182 class MinibatchToSingleExampleIterator(object):
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183 """
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184 Converts the result of minibatch iterator with minibatch_size==1 into
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185 single-example values in the result. Therefore the result of
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186 iterating on the dataset itself gives a sequence of single examples
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187 (whereas the result of iterating over minibatches gives in each
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188 Example field an iterable object over the individual examples in
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189 the minibatch).
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190 """
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191 def __init__(self, minibatch_iterator):
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192 self.minibatch_iterator = minibatch_iterator
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193 self.minibatch = None
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194 def __iter__(self): #makes for loop work
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195 return self
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196 def next(self):
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197 size1_minibatch = self.minibatch_iterator.next()
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198 if not self.minibatch:
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199 self.minibatch = Example(size1_minibatch.keys(),[value[0] for value in size1_minibatch.values()])
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200 else:
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201 self.minibatch._values = [value[0] for value in size1_minibatch.values()]
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202 return self.minibatch
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203
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204 def next_index(self):
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205 return self.minibatch_iterator.next_index()
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206
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207 def __iter__(self):
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208 """Supports the syntax "for i in dataset: ..."
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209
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210 Using this syntax, "i" will be an Example instance (or equivalent) with
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211 all the fields of DataSet self. Every field of "i" will give access to
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212 a field of a single example. Fields should be accessible via
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213 i["fielname"] or i[3] (in the order defined by the elements of the
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214 Example returned by this iterator), but the derived class is free
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215 to accept any type of identifier, and add extra functionality to the iterator.
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216
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217 The default implementation calls the minibatches iterator and extracts the first example of each field.
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218 """
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219 return DataSet.MinibatchToSingleExampleIterator(self.minibatches(None, minibatch_size = 1))
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220
188
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221 def __contains__(self, fieldname):
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222 return (fieldname in self.fieldNames()) \
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223 or (fieldname in self.attributeNames())
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224
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225 class MinibatchWrapAroundIterator(object):
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226 """
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227 An iterator for minibatches that handles the case where we need to wrap around the
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228 dataset because n_batches*minibatch_size > len(dataset). It is constructed from
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229 a dataset that provides a minibatch iterator that does not need to handle that problem.
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230 This class is a utility for dataset subclass writers, so that they do not have to handle
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231 this issue multiple times, nor check that fieldnames are valid, nor handle the
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232 empty fieldnames (meaning 'use all the fields').
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233 """
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234 def __init__(self,dataset,fieldnames,minibatch_size,n_batches,offset):
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235 self.dataset=dataset
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236 self.fieldnames=fieldnames
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237 self.minibatch_size=minibatch_size
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238 self.n_batches=n_batches
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239 self.n_batches_done=0
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240 self.next_row=offset
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241 self.offset=offset
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242 self.L=len(dataset)
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243 assert offset+minibatch_size<=self.L
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244 ds_nbatches = (self.L-self.next_row)/self.minibatch_size
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245 if n_batches is not None:
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246 ds_nbatches = min(n_batches,ds_nbatches)
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247 if fieldnames:
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248 assert dataset.hasFields(*fieldnames)
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249 else:
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250 self.fieldnames=dataset.fieldNames()
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251 self.iterator = self.dataset.minibatches_nowrap(self.fieldnames,self.minibatch_size,
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252 ds_nbatches,self.next_row)
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253
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254 def __iter__(self):
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255 return self
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256
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257 def next_index(self):
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258 return self.next_row
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259
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260 def next(self):
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261 if self.n_batches and self.n_batches_done==self.n_batches:
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262 raise StopIteration
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263 elif not self.n_batches and self.next_row ==self.L:
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264 raise StopIteration
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265 upper = self.next_row+self.minibatch_size
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266 if upper <=self.L:
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267 minibatch = self.iterator.next()
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268 else:
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diff changeset
269 if not self.n_batches:
101
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270 upper=min(upper, self.L)
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271 # if their is not a fixed number of batch, we continue to the end of the dataset.
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272 # this can create a minibatch that is smaller then the minibatch_size
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273 assert (self.L-self.next_row)<=self.minibatch_size
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274 minibatch = self.dataset.minibatches_nowrap(self.fieldnames,self.L-self.next_row,1,self.next_row).next()
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275 else:
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276 # we must concatenate (vstack) the bottom and top parts of our minibatch
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277 # first get the beginning of our minibatch (top of dataset)
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278 first_part = self.dataset.minibatches_nowrap(self.fieldnames,self.L-self.next_row,1,self.next_row).next()
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279 second_part = self.dataset.minibatches_nowrap(self.fieldnames,upper-self.L,1,0).next()
268
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280 minibatch = Example(self.fieldnames,
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281 [self.dataset.valuesVStack(name,[first_part[name],second_part[name]])
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282 for name in self.fieldnames])
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283 self.next_row=upper
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284 self.n_batches_done+=1
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285 if upper >= self.L and self.n_batches:
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286 self.next_row -= self.L
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287 ds_nbatches = (self.L-self.next_row)/self.minibatch_size
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288 if self.n_batches is not None:
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289 ds_nbatches = min(self.n_batches,ds_nbatches)
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290 self.iterator = self.dataset.minibatches_nowrap(self.fieldnames,self.minibatch_size,
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291 ds_nbatches,self.next_row)
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292 return DataSetFields(MinibatchDataSet(minibatch,self.dataset.valuesVStack,
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293 self.dataset.valuesHStack),
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294 minibatch.keys())
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295
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296
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297 minibatches_fieldnames = None
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298 minibatches_minibatch_size = 1
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299 minibatches_n_batches = None
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300 def minibatches(self,
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301 fieldnames = minibatches_fieldnames,
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302 minibatch_size = minibatches_minibatch_size,
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303 n_batches = minibatches_n_batches,
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304 offset = 0):
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305 """
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306 Return an iterator that supports three forms of syntax:
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307
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308 for i in dataset.minibatches(None,**kwargs): ...
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309
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310 for i in dataset.minibatches([f1, f2, f3],**kwargs): ...
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311
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312 for i1, i2, i3 in dataset.minibatches([f1, f2, f3],**kwargs): ...
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313
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314 Using the first two syntaxes, "i" will be an indexable object, such as a list,
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315 tuple, or Example instance. In both cases, i[k] is a list-like container
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316 of a batch of current examples. In the second case, i[0] is
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317 list-like container of the f1 field of a batch current examples, i[1] is
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318 a list-like container of the f2 field, etc.
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319
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320 Using the first syntax, all the fields will be returned in "i".
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321 Using the third syntax, i1, i2, i3 will be list-like containers of the
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322 f1, f2, and f3 fields of a batch of examples on each loop iteration.
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323
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324 The minibatches iterator is expected to return upon each call to next()
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325 a DataSetFields object, which is a LookupList (indexed by the field names) whose
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326 elements are iterable and indexable over the minibatch examples, and which keeps a pointer to
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327 a sub-dataset that can be used to iterate over the individual examples
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328 in the minibatch. Hence a minibatch can be converted back to a regular
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329 dataset or its fields can be looked at individually (and possibly iterated over).
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330
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331 PARAMETERS
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332 - fieldnames (list of any type, default None):
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333 The loop variables i1, i2, i3 (in the example above) should contain the
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334 f1, f2, and f3 fields of the current batch of examples. If None, the
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335 derived class can choose a default, e.g. all fields.
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336
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337 - minibatch_size (integer, default 1)
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338 On every iteration, the variables i1, i2, i3 will have
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339 exactly minibatch_size elements. e.g. len(i1) == minibatch_size
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340
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341 - n_batches (integer, default None)
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342 The iterator will loop exactly this many times, and then stop. If None,
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343 the derived class can choose a default. If (-1), then the returned
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344 iterator should support looping indefinitely.
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345
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346 - offset (integer, default 0)
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347 The iterator will start at example 'offset' in the dataset, rather than the default.
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348
17
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349 Note: A list-like container is something like a tuple, list, numpy.ndarray or
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350 any other object that supports integer indexing and slicing.
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351
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352 """
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353 return DataSet.MinibatchWrapAroundIterator(self,fieldnames,minibatch_size,n_batches,offset)
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354
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355 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
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356 """
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357 This is the minibatches iterator generator that sub-classes must define.
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358 It does not need to worry about wrapping around multiple times across the dataset,
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359 as this is handled by MinibatchWrapAroundIterator when DataSet.minibatches() is called.
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360 The next() method of the returned iterator does not even need to worry about
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361 the termination condition (as StopIteration will be raised by DataSet.minibatches
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362 before an improper call to minibatches_nowrap's next() is made).
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363 That next() method can assert that its next row will always be within [0,len(dataset)).
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364 The iterator returned by minibatches_nowrap does not need to implement
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365 a next_index() method either, as this will be provided by MinibatchWrapAroundIterator.
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366 """
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367 raise AbstractFunction()
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368
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369 def __len__(self):
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370 """
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371 len(dataset) returns the number of examples in the dataset.
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372 By default, a DataSet is a 'stream', i.e. it has an unbounded length (sys.maxint).
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373 Sub-classes which implement finite-length datasets should redefine this method.
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374 Some methods only make sense for finite-length datasets.
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375 """
123
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376 return maxint
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377
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378 def is_unbounded(self):
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379 """
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380 Tests whether a dataset is unbounded (e.g. a stream).
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381 """
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382 return len(self)==maxint
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383
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384 def hasFields(self,*fieldnames):
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385 """
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386 Return true if the given field name (or field names, if multiple arguments are
b6b36f65664f Created virtual sub-classes of DataSet: {Finite{Length,Width},Sliceable}DataSet,
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parents: 20
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387 given) is recognized by the DataSet (i.e. can be used as a field name in one
b6b36f65664f Created virtual sub-classes of DataSet: {Finite{Length,Width},Sliceable}DataSet,
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388 of the iterators).
29
46c5c90019c2 Changed apply_function so that it propagates methods of the source.
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parents: 28
diff changeset
389
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390 The default implementation may be inefficient (O(# fields in dataset)), as it calls the fieldNames()
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391 method. Many datasets may store their field names in a dictionary, which would allow more efficiency.
11
be128b9127c8 Debugged (to the extent of my tests) the new version of dataset
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parents: 9
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392 """
36
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393 return len(unique_elements_list_intersection(fieldnames,self.fieldNames()))>0
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394
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395 def fieldNames(self):
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396 """
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397 Return the list of field names that are supported by the iterators,
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398 and for which hasFields(fieldname) would return True.
11
be128b9127c8 Debugged (to the extent of my tests) the new version of dataset
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parents: 9
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399 """
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
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parents: 16 12
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400 raise AbstractFunction()
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parents: 16 12
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401
36
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402 def __call__(self,*fieldnames):
23
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
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parents: 22
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403 """
36
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404 Return a dataset that sees only the fields whose name are specified.
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
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405 """
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
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406 assert self.hasFields(*fieldnames)
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parents: 41
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407 return self.fields(*fieldnames).examples()
20
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parents: 19
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408
36
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409 def fields(self,*fieldnames):
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parents: 28
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410 """
36
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411 Return a DataSetFields object associated with this dataset.
17
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parents: 16 12
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412 """
74
b4159cbdc06b Fixed errors raised by test_dataset
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413 return DataSetFields(self,fieldnames)
11
be128b9127c8 Debugged (to the extent of my tests) the new version of dataset
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parents: 9
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414
2
3fddb1c8f955 Rewrote DataSet interface and created FiniteDataSet interface.
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parents: 1
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415 def __getitem__(self,i):
28
541a273bc89f Removed __array__ method from dataset, whose
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416 """
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parents: 26
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417 dataset[i] returns the (i+1)-th example of the dataset.
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parents: 26
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418 dataset[i:j] returns the subdataset with examples i,i+1,...,j-1.
541a273bc89f Removed __array__ method from dataset, whose
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parents: 26
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419 dataset[i:j:s] returns the subdataset with examples i,i+2,i+4...,j-2.
541a273bc89f Removed __array__ method from dataset, whose
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parents: 26
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420 dataset[[i1,i2,..,in]] returns the subdataset with examples i1,i2,...,in.
41
283e95c15b47 Added ArrayDataSet
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parents: 40
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421 dataset['key'] returns a property associated with the given 'key' string.
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parents: 40
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422 If 'key' is a fieldname, then the VStacked field values (iterable over
283e95c15b47 Added ArrayDataSet
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parents: 40
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423 field values) for that field is returned. Other keys may be supported
283e95c15b47 Added ArrayDataSet
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parents: 40
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424 by different dataset subclasses. The following key names are encouraged:
283e95c15b47 Added ArrayDataSet
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parents: 40
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425 - 'description': a textual description or name for the dataset
283e95c15b47 Added ArrayDataSet
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426 - '<fieldname>.type': a type name or value for a given <fieldname>
1
2cd82666b9a7 Added statscollector and started writing dataset and learner.
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parents: 0
diff changeset
427
39
c682c6e9bf93 Minor edits
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parents: 38
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428 Note that some stream datasets may be unable to implement random access, i.e.
c682c6e9bf93 Minor edits
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parents: 38
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429 arbitrary slicing/indexing
36
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430 because they can only iterate through examples one or a minibatch at a time
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431 and do not actually store or keep past (or future) examples.
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
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432
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
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433 The default implementation of getitem uses the minibatches iterator
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434 to obtain one example, one slice, or a list of examples. It may not
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parents: 39
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435 always be the most efficient way to obtain the result, especially if
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parents: 39
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436 the data are actually stored in a memory array.
28
541a273bc89f Removed __array__ method from dataset, whose
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parents: 26
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437 """
41
283e95c15b47 Added ArrayDataSet
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438 # check for an index
40
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439 if type(i) is int:
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440 return DataSet.MinibatchToSingleExampleIterator(
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441 self.minibatches(minibatch_size=1,n_batches=1,offset=i)).next()
41
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442 rows=None
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443 # or a slice
40
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444 if type(i) is slice:
211
bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 203
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445 #print 'i=',i
135
0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 134
diff changeset
446 if not i.start: i=slice(0,i.stop,i.step)
211
bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 203
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447 if not i.stop: i=slice(i.start,len(self),i.step)
135
0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work
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parents: 134
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448 if not i.step: i=slice(i.start,i.stop,1)
40
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parents: 39
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449 if i.step is 1:
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450 return self.minibatches(minibatch_size=i.stop-i.start,n_batches=1,offset=i.start).next().examples()
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451 rows = range(i.start,i.stop,i.step)
41
283e95c15b47 Added ArrayDataSet
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parents: 40
diff changeset
452 # or a list of indices
283e95c15b47 Added ArrayDataSet
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parents: 40
diff changeset
453 elif type(i) is list:
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
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parents: 39
diff changeset
454 rows = i
41
283e95c15b47 Added ArrayDataSet
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parents: 40
diff changeset
455 if rows is not None:
48
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
456 examples = [self[row] for row in rows]
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
457 fields_values = zip(*examples)
45
a5c70dc42972 Test functions for dataset.py
bengioy@grenat.iro.umontreal.ca
parents: 44
diff changeset
458 return MinibatchDataSet(
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
459 Example(self.fieldNames(),[ self.valuesVStack(fieldname,field_values)
283e95c15b47 Added ArrayDataSet
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parents: 40
diff changeset
460 for fieldname,field_values
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
461 in zip(self.fieldNames(),fields_values)]),
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
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462 self.valuesVStack,self.valuesHStack)
268
3f1cd8897fda reverting dataset
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463 # else check for a fieldname
3f1cd8897fda reverting dataset
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464 if self.hasFields(i):
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465 return self.minibatches(fieldnames=[i],minibatch_size=len(self),n_batches=1,offset=0).next()[0]
3f1cd8897fda reverting dataset
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466 # else we are trying to access a property of the dataset
3f1cd8897fda reverting dataset
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467 assert i in self.__dict__ # else it means we are trying to access a non-existing property
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468 return self.__dict__[i]
22
b6b36f65664f Created virtual sub-classes of DataSet: {Finite{Length,Width},Sliceable}DataSet,
bengioy@esprit.iro.umontreal.ca
parents: 20
diff changeset
469
36
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470 def valuesHStack(self,fieldnames,fieldvalues):
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471 """
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472 Return a value that corresponds to concatenating (horizontally) several field values.
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473 This can be useful to merge some fields. The implementation of this operation is likely
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parents: 29
diff changeset
474 to involve a copy of the original values. When the values are numpy arrays, the
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diff changeset
475 result should be numpy.hstack(values). If it makes sense, this operation should
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476 work as well when each value corresponds to multiple examples in a minibatch
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diff changeset
477 e.g. if each value is a Ni-vector and a minibatch of length L is a LxNi matrix,
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parents: 29
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478 then the result should be a Lx(N1+N2+..) matrix equal to numpy.hstack(values).
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479 The default is to use numpy.hstack for numpy.ndarray values, and a list
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480 pointing to the original values for other data types.
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481 """
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482 all_numpy=True
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diff changeset
483 for value in fieldvalues:
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diff changeset
484 if not type(value) is numpy.ndarray:
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diff changeset
485 all_numpy=False
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486 if all_numpy:
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487 return numpy.hstack(fieldvalues)
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488 # the default implementation of horizontal stacking is to put values in a list
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489 return fieldvalues
26
672fe4b23032 Fixed dataset errors so that _test_dataset.py works again.
bengioy@grenat.iro.umontreal.ca
parents: 23
diff changeset
490
672fe4b23032 Fixed dataset errors so that _test_dataset.py works again.
bengioy@grenat.iro.umontreal.ca
parents: 23
diff changeset
491
36
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492 def valuesVStack(self,fieldname,values):
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493 """
268
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494 Return a value that corresponds to concatenating (vertically) several values of the
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
495 same field. This can be important to build a minibatch out of individual examples. This
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
496 is likely to involve a copy of the original values. When the values are numpy arrays, the
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
497 result should be numpy.vstack(values).
3f1cd8897fda reverting dataset
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parents: 266
diff changeset
498 The default is to use numpy.vstack for numpy.ndarray values, and a list
3f1cd8897fda reverting dataset
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parents: 266
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499 pointing to the original values for other data types.
36
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500 """
268
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501 all_numpy=True
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parents: 266
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502 for value in values:
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parents: 266
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503 if not type(value) is numpy.ndarray:
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504 all_numpy=False
3f1cd8897fda reverting dataset
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parents: 266
diff changeset
505 if all_numpy:
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parents: 266
diff changeset
506 return numpy.vstack(values)
3f1cd8897fda reverting dataset
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diff changeset
507 # the default implementation of vertical stacking is to put values in a list
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parents: 266
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508 return values
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
509
36
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parents: 29
diff changeset
510 def __or__(self,other):
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511 """
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diff changeset
512 dataset1 | dataset2 returns a dataset whose list of fields is the concatenation of the list of
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parents: 29
diff changeset
513 fields of the argument datasets. This only works if they all have the same length.
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parents: 29
diff changeset
514 """
135
0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 134
diff changeset
515 return HStackedDataSet([self,other])
3
378b68d5c4ad Added first (untested) version of ArrayDataSet
bengioy@bengiomac.local
parents: 2
diff changeset
516
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
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parents: 39
diff changeset
517 def __and__(self,other):
36
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diff changeset
518 """
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
519 dataset1 & dataset2 is a dataset that concatenates the examples from the argument datasets
36
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
520 (and whose length is the sum of the length of the argument datasets). This only
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
521 works if they all have the same fields.
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parents: 29
diff changeset
522 """
135
0d8e721cc63c Fixed bugs in dataset to make test_mlp.py work
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 134
diff changeset
523 return VStackedDataSet([self,other])
23
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
524
36
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parents: 29
diff changeset
525 def hstack(datasets):
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
526 """
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parents: 29
diff changeset
527 hstack(dataset1,dataset2,...) returns dataset1 | datataset2 | ...
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parents: 29
diff changeset
528 which is a dataset whose fields list is the concatenation of the fields
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parents: 29
diff changeset
529 of the individual datasets.
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bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
530 """
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parents: 29
diff changeset
531 assert len(datasets)>0
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parents: 29
diff changeset
532 if len(datasets)==1:
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parents: 29
diff changeset
533 return datasets[0]
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parents: 29
diff changeset
534 return HStackedDataSet(datasets)
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
535
36
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parents: 29
diff changeset
536 def vstack(datasets):
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
537 """
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
538 vstack(dataset1,dataset2,...) returns dataset1 & datataset2 & ...
36
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parents: 29
diff changeset
539 which is a dataset which iterates first over the examples of dataset1, then
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
540 over those of dataset2, etc.
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
541 """
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parents: 29
diff changeset
542 assert len(datasets)>0
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bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
543 if len(datasets)==1:
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parents: 29
diff changeset
544 return datasets[0]
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
545 return VStackedDataSet(datasets)
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
546
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
547 class FieldsSubsetDataSet(DataSet):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
548 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
549 A sub-class of L{DataSet} that selects a subset of the fields.
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
550 """
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
551 def __init__(self,src,fieldnames):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
552 self.src=src
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
553 self.fieldnames=fieldnames
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
554 assert src.hasFields(*fieldnames)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
555 self.valuesHStack = src.valuesHStack
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
556 self.valuesVStack = src.valuesVStack
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
557
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
558 def __len__(self): return len(self.src)
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
559
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
560 def fieldNames(self):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
561 return self.fieldnames
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
562
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
563 def __iter__(self):
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
564 class FieldsSubsetIterator(object):
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
565 def __init__(self,ds):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
566 self.ds=ds
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
567 self.src_iter=ds.src.__iter__()
44
5a85fda9b19b Fixed some more iterator bugs
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parents: 43
diff changeset
568 self.example=None
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
569 def __iter__(self): return self
9b68774fcc6b Testing basic functionality and removing obvious bugs
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parents: 41
diff changeset
570 def next(self):
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
571 complete_example = self.src_iter.next()
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
572 if self.example:
5a85fda9b19b Fixed some more iterator bugs
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parents: 43
diff changeset
573 self.example._values=[complete_example[field]
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
574 for field in self.ds.fieldnames]
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
575 else:
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
576 self.example=Example(self.ds.fieldnames,
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
577 [complete_example[field] for field in self.ds.fieldnames])
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
578 return self.example
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
579 return FieldsSubsetIterator(self)
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
580
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
581 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
582 assert self.hasFields(*fieldnames)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
583 return self.src.minibatches_nowrap(fieldnames,minibatch_size,n_batches,offset)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
584 def __getitem__(self,i):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
585 return FieldsSubsetDataSet(self.src[i],self.fieldnames)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
586
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
587
36
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parents: 29
diff changeset
588 class DataSetFields(LookupList):
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parents: 29
diff changeset
589 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
590 Although a L{DataSet} iterates over examples (like rows of a matrix), an associated
36
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parents: 29
diff changeset
591 DataSetFields iterates over fields (like columns of a matrix), and can be understood
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
592 as a transpose of the associated dataset.
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
593
36
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parents: 29
diff changeset
594 To iterate over fields, one can do
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
595 * for fields in dataset.fields()
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
596 * for fields in dataset(field1,field2,...).fields() to select a subset of fields
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
597 * for fields in dataset.fields(field1,field2,...) to select a subset of fields
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parents: 29
diff changeset
598 and each of these fields is iterable over the examples:
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parents: 29
diff changeset
599 * for field_examples in dataset.fields():
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
600 for example_value in field_examples:
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
601 ...
241
ddb88a8e9fd2 If I understand properly, the length of an unbounded stream is sys.maxint
delallea@opale.iro.umontreal.ca
parents: 231
diff changeset
602 but when the dataset is a stream (unbounded length), it is not recommended to do
36
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
603 such things because the underlying dataset may refuse to access the different fields in
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
604 an unsynchronized ways. Hence the fields() method is illegal for streams, by default.
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
605 The result of fields() is a DataSetFields object, which iterates over fields,
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
606 and whose elements are iterable over examples. A DataSetFields object can
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
607 be turned back into a DataSet with its examples() method:
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
608 dataset2 = dataset1.fields().examples()
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
609 and dataset2 should behave exactly like dataset1 (in fact by default dataset2==dataset1).
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
610
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
611 DataSetFields can be concatenated vertically or horizontally. To be consistent with
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
612 the syntax used for DataSets, the | concatenates the fields and the & concatenates
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
613 the examples.
36
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
614 """
74
b4159cbdc06b Fixed errors raised by test_dataset
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 73
diff changeset
615 def __init__(self,dataset,fieldnames):
65
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
616 original_dataset=dataset
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
617 if not fieldnames:
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
618 fieldnames=dataset.fieldNames()
65
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
619 elif not fieldnames==dataset.fieldNames():
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
620 dataset = FieldsSubsetDataSet(dataset,fieldnames)
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
621 assert dataset.hasFields(*fieldnames)
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
622 self.dataset=dataset
66
dde1fb1b63ba fixed test and removed print
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 65
diff changeset
623
64
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
624 if isinstance(dataset,MinibatchDataSet):
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
625 LookupList.__init__(self,fieldnames,list(dataset._fields))
65
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
626 elif isinstance(original_dataset,MinibatchDataSet):
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
627 LookupList.__init__(self,fieldnames,
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
628 [original_dataset._fields[field]
d48eba49a2f4 fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 64
diff changeset
629 for field in fieldnames])
64
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
630 else:
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
631 minibatch_iterator = dataset.minibatches(fieldnames,
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
632 minibatch_size=len(dataset),
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
633 n_batches=1)
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
634 minibatch=minibatch_iterator.next()
863da25a60f1 trying to fix infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 62
diff changeset
635 LookupList.__init__(self,fieldnames,minibatch)
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
636
36
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parents: 29
diff changeset
637 def examples(self):
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parents: 29
diff changeset
638 return self.dataset
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parents: 29
diff changeset
639
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
640 def __or__(self,other):
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parents: 29
diff changeset
641 """
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
642 fields1 | fields2 is a DataSetFields that whose list of examples is the concatenation
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
643 of the list of examples of DataSetFields fields1 and fields2.
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
644 """
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
645 return (self.examples() + other.examples()).fields()
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
646
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
647 def __and__(self,other):
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
648 """
36
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parents: 29
diff changeset
649 fields1 + fields2 is a DataSetFields that whose list of fields is the concatenation
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
650 of the fields of DataSetFields fields1 and fields2.
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
651 """
438440ba0627 Rewriting dataset.py completely
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parents: 29
diff changeset
652 return (self.examples() | other.examples()).fields()
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
653
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
654
36
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parents: 29
diff changeset
655 class MinibatchDataSet(DataSet):
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parents: 29
diff changeset
656 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
657 Turn a L{LookupList} of same-length (iterable) fields into an example-iterable dataset.
36
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parents: 29
diff changeset
658 Each element of the lookup-list should be an iterable and sliceable, all of the same length.
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parents: 29
diff changeset
659 """
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parents: 29
diff changeset
660 def __init__(self,fields_lookuplist,values_vstack=DataSet().valuesVStack,
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parents: 29
diff changeset
661 values_hstack=DataSet().valuesHStack):
17
759d17112b23 more comments, looping ArrayDataSet iterator, bugfixes to lookup_list, more tests
bergstrj@iro.umontreal.ca
parents: 16 12
diff changeset
662 """
36
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diff changeset
663 The user can (and generally should) also provide values_vstack(fieldname,fieldvalues)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
664 and a values_hstack(fieldnames,fieldvalues) functions behaving with the same
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
665 semantics as the DataSet methods of the same name (but without the self argument).
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
666 """
211
bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 203
diff changeset
667
61
a8b70a9117ad bugfix: in MinibatchDataSet renamed the class variable fields to _fields as parent class have a function called field.
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 60
diff changeset
668 self._fields=fields_lookuplist
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
669 assert len(fields_lookuplist)>0
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
670 self.length=len(fields_lookuplist[0])
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
671 for field in fields_lookuplist[1:]:
223
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
672 if self.length != len(field) :
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
673 print 'self.length = ',self.length
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
674 print 'len(field) = ', len(field)
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
675 print 'self._fields.keys() = ', self._fields.keys()
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
676 print 'field=',field
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
677 assert self.length==len(field)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
678 self.values_vstack=values_vstack
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
679 self.values_hstack=values_hstack
3
378b68d5c4ad Added first (untested) version of ArrayDataSet
bengioy@bengiomac.local
parents: 2
diff changeset
680
378b68d5c4ad Added first (untested) version of ArrayDataSet
bengioy@bengiomac.local
parents: 2
diff changeset
681 def __len__(self):
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
682 return self.length
28
541a273bc89f Removed __array__ method from dataset, whose
bengioy@grenat.iro.umontreal.ca
parents: 26
diff changeset
683
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
684 def __getitem__(self,i):
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
685 if type(i) in (slice,list):
48
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
686 return DataSetFields(MinibatchDataSet(
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
687 Example(self._fields.keys(),[field[i] for field in self._fields])),self.fieldNames())
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
688 if type(i) is int:
85
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 83
diff changeset
689 return Example(self._fields.keys(),[field[i] for field in self._fields])
48
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
690 if self.hasFields(i):
61
a8b70a9117ad bugfix: in MinibatchDataSet renamed the class variable fields to _fields as parent class have a function called field.
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 60
diff changeset
691 return self._fields[i]
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
692 assert i in self.__dict__ # else it means we are trying to access a non-existing property
48
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
693 return self.__dict__[i]
11
be128b9127c8 Debugged (to the extent of my tests) the new version of dataset
bengioy@esprit.iro.umontreal.ca
parents: 9
diff changeset
694
29
46c5c90019c2 Changed apply_function so that it propagates methods of the source.
bengioy@grenat.iro.umontreal.ca
parents: 28
diff changeset
695 def fieldNames(self):
61
a8b70a9117ad bugfix: in MinibatchDataSet renamed the class variable fields to _fields as parent class have a function called field.
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 60
diff changeset
696 return self._fields.keys()
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
697
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
698 def hasFields(self,*fieldnames):
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
699 for fieldname in fieldnames:
61
a8b70a9117ad bugfix: in MinibatchDataSet renamed the class variable fields to _fields as parent class have a function called field.
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 60
diff changeset
700 if fieldname not in self._fields.keys():
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
701 return False
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
702 return True
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
703
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
704 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
223
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
705 #@TODO bug somewhere here, fieldnames doesnt seem to be well handled
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
706 class Iterator(object):
223
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
707 def __init__(self,ds,fieldnames):
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
708 # tbm: added two next lines to handle fieldnames
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
709 if fieldnames is None: fieldnames = ds._fields.keys()
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
710 self.fieldnames = fieldnames
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
711
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
712 self.ds=ds
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
713 self.next_example=offset
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
714 assert minibatch_size > 0
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
715 if offset+minibatch_size > ds.length:
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
716 raise NotImplementedError()
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
717 def __iter__(self):
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
718 return self
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
719 def next(self):
61
a8b70a9117ad bugfix: in MinibatchDataSet renamed the class variable fields to _fields as parent class have a function called field.
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 60
diff changeset
720 upper = self.next_example+minibatch_size
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
721 assert upper<=self.ds.length
223
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
722 #minibatch = Example(self.ds._fields.keys(),
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
723 # [field[self.next_example:upper]
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
724 # for field in self.ds._fields])
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
725 # tbm: modif to use fieldnames
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
726 values = []
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
727 for f in self.fieldnames :
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
728 #print 'we have field',f,'in fieldnames'
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
729 values.append( self.ds._fields[f][self.next_example:upper] )
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
730 minibatch = Example(self.fieldnames,values)
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
731 #print minibatch
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
732 self.next_example+=minibatch_size
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
733 return minibatch
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
734
223
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
735 # tbm: added fieldnames to handle subset of fieldnames
517364d48ae0 should have solved the problem with minibatches not handling subsets of fieldnames, although maybe not super efficient
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 218
diff changeset
736 return Iterator(self,fieldnames)
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
737
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
738 def valuesVStack(self,fieldname,fieldvalues):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
739 return self.values_vstack(fieldname,fieldvalues)
20
266c68cb6136 Minor editions, plus adding untested ApplyFunctionDataset for GradientLearner in the works.
bengioy@bengiomac.local
parents: 19
diff changeset
740
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
741 def valuesHStack(self,fieldnames,fieldvalues):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
742 return self.values_hstack(fieldnames,fieldvalues)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
743
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
744 class HStackedDataSet(DataSet):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
745 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
746 A L{DataSet} that wraps several datasets and shows a view that includes all their fields,
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
747 i.e. whose list of fields is the concatenation of their lists of fields.
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
748
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
749 If a field name is found in more than one of the datasets, then either an error is
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
750 raised or the fields are renamed (either by prefixing the __name__ attribute
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
751 of the dataset + ".", if it exists, or by suffixing the dataset index in the argument list).
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
752
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
753 @todo: automatically detect a chain of stacked datasets due to A | B | C | D ...
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
754 """
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
755 def __init__(self,datasets,accept_nonunique_names=False,description=None,field_types=None):
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
756 DataSet.__init__(self,description,field_types)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
757 self.datasets=datasets
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
758 self.accept_nonunique_names=accept_nonunique_names
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
759 self.fieldname2dataset={}
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
760
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
761 def rename_field(fieldname,dataset,i):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
762 if hasattr(dataset,"__name__"):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
763 return dataset.__name__ + "." + fieldname
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
764 return fieldname+"."+str(i)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
765
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
766 # make sure all datasets have the same length and unique field names
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
767 self.length=None
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
768 names_to_change=[]
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
769 for i in xrange(len(datasets)):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
770 dataset = datasets[i]
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
771 length=len(dataset)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
772 if self.length:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
773 assert self.length==length
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
774 else:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
775 self.length=length
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
776 for fieldname in dataset.fieldNames():
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
777 if fieldname in self.fieldname2dataset: # name conflict!
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
778 if accept_nonunique_names:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
779 fieldname=rename_field(fieldname,dataset,i)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
780 names2change.append((fieldname,i))
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
781 else:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
782 raise ValueError("Incompatible datasets: non-unique field name = "+fieldname)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
783 self.fieldname2dataset[fieldname]=i
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
784 for fieldname,i in names_to_change:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
785 del self.fieldname2dataset[fieldname]
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
786 self.fieldname2dataset[rename_field(fieldname,self.datasets[i],i)]=i
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
787
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
788 def hasFields(self,*fieldnames):
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
789 for fieldname in fieldnames:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
790 if not fieldname in self.fieldname2dataset:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
791 return False
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
792 return True
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
793
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
794 def fieldNames(self):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
795 return self.fieldname2dataset.keys()
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
796
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
797 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
798
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
799 class HStackedIterator(object):
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
800 def __init__(self,hsds,iterators):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
801 self.hsds=hsds
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
802 self.iterators=iterators
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
803 def __iter__(self):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
804 return self
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
805 def next(self):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
806 # concatenate all the fields of the minibatches
140
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 136
diff changeset
807 l=LookupList()
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 136
diff changeset
808 for iter in self.iterators:
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 136
diff changeset
809 l.append_lookuplist(iter.next())
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 136
diff changeset
810 return l
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
811
125
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 123
diff changeset
812 assert self.hasFields(*fieldnames)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
813 # find out which underlying datasets are necessary to service the required fields
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
814 # and construct corresponding minibatch iterators
140
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 136
diff changeset
815 if fieldnames and fieldnames!=self.fieldNames():
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
816 datasets=set([])
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
817 fields_in_dataset=dict([(dataset,[]) for dataset in datasets])
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
818 for fieldname in fieldnames:
136
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 125
diff changeset
819 dataset=self.datasets[self.fieldname2dataset[fieldname]]
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
820 datasets.add(dataset)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
821 fields_in_dataset[dataset].append(fieldname)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
822 datasets=list(datasets)
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
823 iterators=[dataset.minibatches(fields_in_dataset[dataset],minibatch_size,n_batches,offset)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
824 for dataset in datasets]
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
825 else:
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
826 datasets=self.datasets
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
827 iterators=[dataset.minibatches(None,minibatch_size,n_batches,offset) for dataset in datasets]
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
828 return HStackedIterator(self,iterators)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
829
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
830
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
831 def valuesVStack(self,fieldname,fieldvalues):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
832 return self.datasets[self.fieldname2dataset[fieldname]].valuesVStack(fieldname,fieldvalues)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
833
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
834 def valuesHStack(self,fieldnames,fieldvalues):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
835 """
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
836 We will use the sub-dataset associated with the first fieldname in the fieldnames list
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
837 to do the work, hoping that it can cope with the other values (i.e. won't care
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
838 about the incompatible fieldnames). Hence this heuristic will always work if
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
839 all the fieldnames are of the same sub-dataset.
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
840 """
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
841 return self.datasets[self.fieldname2dataset[fieldnames[0]]].valuesHStack(fieldnames,fieldvalues)
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
842
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
843 class VStackedDataSet(DataSet):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
844 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
845 A L{DataSet} that wraps several datasets and shows a view that includes all their examples,
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
846 in the order provided. This clearly assumes that they all have the same field names
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
847 and all (except possibly the last one) are of finite length.
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
848
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
849 @todo: automatically detect a chain of stacked datasets due to A + B + C + D ...
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
850 """
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
851 def __init__(self,datasets):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
852 self.datasets=datasets
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
853 self.length=0
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
854 self.index2dataset={}
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
855 assert len(datasets)>0
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
856 fieldnames = datasets[-1].fieldNames()
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
857 self.datasets_start_row=[]
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
858 # We use this map from row index to dataset index for constant-time random access of examples,
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
859 # to avoid having to search for the appropriate dataset each time and slice is asked for.
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
860 for dataset,k in enumerate(datasets[0:-1]):
48
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
861 assert dataset.is_unbounded() # All VStacked datasets (except possibly the last) must be bounded (have a length).
b6730f9a336d Fixing MinibatchDataSet getitem
bengioy@grenat.iro.umontreal.ca
parents: 46
diff changeset
862 L=len(dataset)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
863 for i in xrange(L):
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
864 self.index2dataset[self.length+i]=k
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
865 self.datasets_start_row.append(self.length)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
866 self.length+=L
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
867 assert dataset.fieldNames()==fieldnames
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
868 self.datasets_start_row.append(self.length)
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
869 self.length+=len(datasets[-1])
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
870 # If length is very large, we should use a more memory-efficient mechanism
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
871 # that does not store all indices
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
872 if self.length>1000000:
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
873 # 1 million entries would require about 60 meg for the index2dataset map
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
874 # TODO
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
875 print "A more efficient mechanism for index2dataset should be implemented"
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
876
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
877 def __len__(self):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
878 return self.length
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
879
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
880 def fieldNames(self):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
881 return self.datasets[0].fieldNames()
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
882
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
883 def hasFields(self,*fieldnames):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
884 return self.datasets[0].hasFields(*fieldnames)
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
885
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
886 def locate_row(self,row):
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
887 """Return (dataset_index, row_within_dataset) for global row number"""
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
888 dataset_index = self.index2dataset[row]
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
889 row_within_dataset = self.datasets_start_row[dataset_index]
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
890 return dataset_index, row_within_dataset
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
891
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
892 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
893
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
894 class VStackedIterator(object):
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
895 def __init__(self,vsds):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
896 self.vsds=vsds
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
897 self.next_row=offset
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
898 self.next_dataset_index,self.next_dataset_row=self.vsds.locate_row(offset)
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
899 self.current_iterator,self.n_left_at_the_end_of_ds,self.n_left_in_mb= \
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
900 self.next_iterator(vsds.datasets[0],offset,n_batches)
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
901
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
902 def next_iterator(self,dataset,starting_offset,batches_left):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
903 L=len(dataset)
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
904 ds_nbatches = (L-starting_offset)/minibatch_size
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
905 if batches_left is not None:
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
906 ds_nbatches = max(batches_left,ds_nbatches)
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
907 if minibatch_size>L:
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
908 ds_minibatch_size=L
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
909 n_left_in_mb=minibatch_size-L
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
910 ds_nbatches=1
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
911 else:
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
912 n_left_in_mb=0
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
913 return dataset.minibatches(fieldnames,minibatch_size,ds_nbatches,starting_offset), \
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
914 L-(starting_offset+ds_nbatches*minibatch_size), n_left_in_mb
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
915
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
916 def move_to_next_dataset(self):
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
917 if self.n_left_at_the_end_of_ds>0:
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
918 self.current_iterator,self.n_left_at_the_end_of_ds,self.n_left_in_mb= \
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
919 self.next_iterator(vsds.datasets[self.next_dataset_index],
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
920 self.n_left_at_the_end_of_ds,1)
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
921 else:
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
922 self.next_dataset_index +=1
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
923 if self.next_dataset_index==len(self.vsds.datasets):
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
924 self.next_dataset_index = 0
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
925 self.current_iterator,self.n_left_at_the_end_of_ds,self.n_left_in_mb= \
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
926 self.next_iterator(vsds.datasets[self.next_dataset_index],starting_offset,n_batches)
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
927
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
928 def __iter__(self):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
929 return self
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
930
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
931 def next(self):
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
932 dataset=self.vsds.datasets[self.next_dataset_index]
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
933 mb = self.next_iterator.next()
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
934 if self.n_left_in_mb:
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
935 extra_mb = []
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
936 while self.n_left_in_mb>0:
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
937 self.move_to_next_dataset()
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
938 extra_mb.append(self.next_iterator.next())
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
939 mb = Example(fieldnames,
40
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
940 [dataset.valuesVStack(name,
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
941 [mb[name]]+[b[name] for b in extra_mb])
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
942 for name in fieldnames])
88fd1cce08b9 replaced infinity for length by raise UnboundedDataSet and use & instead of + to concatenate datasets
bengioy@esprit.iro.umontreal.ca
parents: 39
diff changeset
943
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
944 self.next_row+=minibatch_size
38
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
945 self.next_dataset_row+=minibatch_size
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
946 if self.next_row+minibatch_size>len(dataset):
d637ad8f7352 Finished first untested version of VStackedDataset
bengioy@esprit.iro.umontreal.ca
parents: 37
diff changeset
947 self.move_to_next_dataset()
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
948 return examples
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
949 return VStackedIterator(self)
37
73c4212ba5b3 Factored the minibatch-writing code into an iterator class inside DataSet
bengioy@esprit.iro.umontreal.ca
parents: 36
diff changeset
950
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
951 class ArrayFieldsDataSet(DataSet):
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
952 """
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
953 Virtual super-class of datasets whose field values are numpy array,
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
954 thus defining valuesHStack and valuesVStack for sub-classes.
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
955 """
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
956 def __init__(self,description=None,field_types=None):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
957 DataSet.__init__(self,description,field_types)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
958 def valuesHStack(self,fieldnames,fieldvalues):
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
959 """Concatenate field values horizontally, e.g. two vectors
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
960 become a longer vector, two matrices become a wider matrix, etc."""
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
961 return numpy.hstack(fieldvalues)
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
962 def valuesVStack(self,fieldname,values):
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
963 """Concatenate field values vertically, e.g. two vectors
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
964 become a two-row matrix, two matrices become a longer matrix, etc."""
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
965 return numpy.vstack(values)
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
966
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
967 class ArrayDataSet(ArrayFieldsDataSet):
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
968 """
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
969 An ArrayDataSet stores the fields as groups of columns in a numpy tensor,
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
970 whose first axis iterates over examples, second axis determines fields.
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
971 If the underlying array is N-dimensional (has N axes), then the field
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
972 values are (N-2)-dimensional objects (i.e. ordinary numbers if N=2).
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
973 """
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
974
188
f01ac276c6fb added __contains__ to Dataset, added parent constructor call to ArrayDataSet
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 171
diff changeset
975 def __init__(self, data_array, fields_columns, **kwargs):
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
976 """
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
977 Construct an ArrayDataSet from the underlying numpy array (data) and
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
978 a map (fields_columns) from fieldnames to field columns. The columns of a field are specified
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
979 using the standard arguments for indexing/slicing: integer for a column index,
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
980 slice for an interval of columns (with possible stride), or iterable of column indices.
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
981 """
188
f01ac276c6fb added __contains__ to Dataset, added parent constructor call to ArrayDataSet
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 171
diff changeset
982 ArrayFieldsDataSet.__init__(self, **kwargs)
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
983 self.data=data_array
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
984 self.fields_columns=fields_columns
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
985
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
986 # check consistency and complete slices definitions
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
987 for fieldname, fieldcolumns in self.fields_columns.items():
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
988 if type(fieldcolumns) is int:
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
989 assert fieldcolumns>=0 and fieldcolumns<data_array.shape[1]
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
990 if 1:
227
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
991 #I changed this because it didn't make sense to me,
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
992 # and it made it more difficult to write my learner.
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
993 # If it breaks stuff, let's talk about it.
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
994 # - James 22/05/2008
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
995 self.fields_columns[fieldname]=[fieldcolumns]
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
996 else:
17c5d080964b reinstating changeset 216 clobbered accidentally by 218
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 223
diff changeset
997 self.fields_columns[fieldname]=fieldcolumns
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
998 elif type(fieldcolumns) is slice:
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
999 start,step=None,None
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1000 if not fieldcolumns.start:
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1001 start=0
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1002 if not fieldcolumns.step:
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1003 step=1
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1004 if start or step:
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1005 self.fields_columns[fieldname]=slice(start,fieldcolumns.stop,step)
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1006 elif hasattr(fieldcolumns,"__iter__"): # something like a list
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1007 for i in fieldcolumns:
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1008 assert i>=0 and i<data_array.shape[1]
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1009
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1010 def fieldNames(self):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1011 return self.fields_columns.keys()
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1012
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1013 def __len__(self):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1014 return len(self.data)
41
283e95c15b47 Added ArrayDataSet
bengioy@grenat.iro.umontreal.ca
parents: 40
diff changeset
1015
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1016 def __getitem__(self,key):
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1017 """More efficient implementation than the default __getitem__"""
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1018 fieldnames=self.fields_columns.keys()
243
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1019 values=self.fields_columns.values()
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1020 if type(key) is int:
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1021 return Example(fieldnames,
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1022 [self.data[key,col] for col in values])
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1023 if type(key) is slice:
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1024 return MinibatchDataSet(Example(fieldnames,
243
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1025 [self.data[key,col] for col in values]))
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1026 if type(key) is list:
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1027 for i in range(len(key)):
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1028 if self.hasFields(key[i]):
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1029 key[i]=self.fields_columns[key[i]]
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1030 return MinibatchDataSet(Example(fieldnames,
88
6749d18e11c8 bugfix as numpy numpy don't support self.data[[i1,...],[i2,...]] when their is more then two i1 and i2
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 85
diff changeset
1031 #we must separate differently for list as numpy
128
ee5507af2c60 minor edits
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 125
diff changeset
1032 # doesn't support self.data[[i1,...],[i2,...]]
88
6749d18e11c8 bugfix as numpy numpy don't support self.data[[i1,...],[i2,...]] when their is more then two i1 and i2
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 85
diff changeset
1033 # when their is more then two i1 and i2
243
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1034 [self.data[key,:][:,col]
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1035 if isinstance(col,list) else
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1036 self.data[key,col] for col in values]),
c8f19a9eb10f Optimisation in ArrayDataSet::__getitem__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 242
diff changeset
1037
128
ee5507af2c60 minor edits
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 125
diff changeset
1038
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1039 self.valuesVStack,self.valuesHStack)
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1040
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1041 # else check for a fieldname
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1042 if self.hasFields(key):
105
8c0a1b11b007 bugfix, we keep all the line, but only a some columns
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 101
diff changeset
1043 return self.data[:,self.fields_columns[key]]
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1044 # else we are trying to access a property of the dataset
80
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1045 assert key in self.__dict__ # else it means we are trying to access a non-existing property
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 66
diff changeset
1046 return self.__dict__[key]
55
66619ce44497 Efficient implementation of getitem for ArrayDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 48
diff changeset
1047
228
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1048 def __iter__(self):
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1049 class ArrayDataSetIterator2(object):
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1050 def __init__(self,dataset,fieldnames,minibatch_size,n_batches,offset):
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1051 if fieldnames is None: fieldnames = dataset.fieldNames()
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1052 # store the resulting minibatch in a lookup-list of values
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1053 self.minibatch = LookupList(fieldnames,[0]*len(fieldnames))
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1054 self.dataset=dataset
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1055 self.minibatch_size=minibatch_size
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1056 assert offset>=0 and offset<len(dataset.data)
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1057 assert offset+minibatch_size<=len(dataset.data)
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1058 self.current=offset
238
ae1d85aca858 optimization in ArrayDataSet::__iter__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 235
diff changeset
1059 self.columns = [self.dataset.fields_columns[f]
ae1d85aca858 optimization in ArrayDataSet::__iter__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 235
diff changeset
1060 for f in self.minibatch._names]
228
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1061 def __iter__(self):
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1062 return self
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1063 def next(self):
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1064 #@todo: we suppose that we need to stop only when minibatch_size == 1.
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1065 # Otherwise, MinibatchWrapAroundIterator do it.
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1066 if self.current>=self.dataset.data.shape[0]:
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1067 raise StopIteration
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1068 sub_data = self.dataset.data[self.current]
238
ae1d85aca858 optimization in ArrayDataSet::__iter__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 235
diff changeset
1069 self.minibatch._values = [sub_data[c] for c in self.columns]
ae1d85aca858 optimization in ArrayDataSet::__iter__
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 235
diff changeset
1070
228
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1071 self.current+=self.minibatch_size
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1072 return self.minibatch
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1073
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1074 return ArrayDataSetIterator2(self,self.fieldNames(),1,0,0)
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1075
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1076 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1077 class ArrayDataSetIterator(object):
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1078 def __init__(self,dataset,fieldnames,minibatch_size,n_batches,offset):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1079 if fieldnames is None: fieldnames = dataset.fieldNames()
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1080 # store the resulting minibatch in a lookup-list of values
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1081 self.minibatch = LookupList(fieldnames,[0]*len(fieldnames))
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1082 self.dataset=dataset
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1083 self.minibatch_size=minibatch_size
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1084 assert offset>=0 and offset<len(dataset.data)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1085 assert offset+minibatch_size<=len(dataset.data)
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1086 self.current=offset
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1087 def __iter__(self):
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1088 return self
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1089 def next(self):
228
6f55e301c687 optimisation of ArrayDataSet
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 203
diff changeset
1090 #@todo: we suppose that MinibatchWrapAroundIterator stop the iterator
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1091 sub_data = self.dataset.data[self.current:self.current+self.minibatch_size]
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1092 self.minibatch._values = [sub_data[:,self.dataset.fields_columns[f]] for f in self.minibatch._names]
43
e92244f30116 Corrected iterator logic errors
bengioy@grenat.iro.umontreal.ca
parents: 42
diff changeset
1093 self.current+=self.minibatch_size
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1094 return self.minibatch
42
9b68774fcc6b Testing basic functionality and removing obvious bugs
bengioy@grenat.iro.umontreal.ca
parents: 41
diff changeset
1095
44
5a85fda9b19b Fixed some more iterator bugs
bengioy@grenat.iro.umontreal.ca
parents: 43
diff changeset
1096 return ArrayDataSetIterator(self,fieldnames,minibatch_size,n_batches,offset)
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1097
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1098
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1099 class CachedDataSet(DataSet):
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1100 """
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1101 Wrap a L{DataSet} whose values are computationally expensive to obtain
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1102 (e.g. because they involve some computation, or disk access),
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1103 so that repeated accesses to the same example are done cheaply,
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1104 by caching every example value that has been accessed at least once.
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1105
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1106 Optionally, for finite-length dataset, all the values can be computed
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1107 (and cached) upon construction of the CachedDataSet, rather at the
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1108 first access.
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1109
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1110 @todo: when cache_all_upon_construction create mini-batches that are as
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1111 large as possible but not so large as to fill up memory.
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1112
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1113 @todo: add disk-buffering capability, so that when the cache becomes too
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1114 big for memory, we cache things on disk, trying to keep in memory only
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1115 the record most likely to be accessed next.
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1116 """
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1117 def __init__(self,source_dataset,cache_all_upon_construction=False):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1118 self.source_dataset=source_dataset
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1119 self.cache_all_upon_construction=cache_all_upon_construction
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1120 self.cached_examples = []
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1121 if cache_all_upon_construction:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1122 # this potentially brings all the source examples
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1123 # into memory at once, which may be too much
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1124 # the work could possibly be done by minibatches
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1125 # that are as large as possible but no more than what memory allows.
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1126 fields_values = source_dataset.minibatches(minibatch_size=len(source_dataset)).__iter__().next()
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1127 assert all([len(self)==len(field_values) for field_values in fields_values])
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1128 for example in fields_values.examples():
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1129 self.cached_examples.append(copy.copy(example))
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1130
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1131 self.fieldNames = source_dataset.fieldNames
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1132 self.hasFields = source_dataset.hasFields
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1133 self.valuesHStack = source_dataset.valuesHStack
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1134 self.valuesVStack = source_dataset.valuesVStack
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1135
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1136 def __len__(self):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1137 return len(self.source_dataset)
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1138
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1139 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1140 class CacheIterator(object):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1141 def __init__(self,dataset):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1142 self.dataset=dataset
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1143 self.current=offset
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1144 self.all_fields = self.dataset.fieldNames()==fieldnames
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1145 def __iter__(self): return self
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1146 def next(self):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1147 upper = self.current+minibatch_size
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1148 cache_len = len(self.dataset.cached_examples)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1149 if upper>cache_len: # whole minibatch is not already in cache
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1150 # cache everything from current length to upper
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1151 for example in self.dataset.source_dataset[cache_len:upper]:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1152 self.dataset.cached_examples.append(example)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1153 all_fields_minibatch = Example(self.dataset.fieldNames(),
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1154 zip(*self.dataset.cached_examples[self.current:self.current+minibatch_size]))
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1155 self.current+=minibatch_size
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1156 if self.all_fields:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1157 return all_fields_minibatch
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1158 return Example(fieldnames,[all_fields_minibatch[name] for name in fieldnames])
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1159 return CacheIterator(self)
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1160
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1161 def __getitem__(self,i):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1162 if type(i)==int and len(self.cached_examples)>i:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1163 return self.cached_examples[i]
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1164 else:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1165 return self.source_dataset[i]
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1166
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1167 def __iter__(self):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1168 class CacheIteratorIter(object):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1169 def __init__(self,dataset):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1170 self.dataset=dataset
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1171 self.l = len(dataset)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1172 self.current = 0
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1173 self.fieldnames = self.dataset.fieldNames()
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1174 self.example = LookupList(self.fieldnames,[0]*len(self.fieldnames))
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1175 def __iter__(self): return self
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1176 def next(self):
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1177 if self.current>=self.l:
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1178 raise StopIteration
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1179 cache_len = len(self.dataset.cached_examples)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1180 if self.current>=cache_len: # whole minibatch is not already in cache
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1181 # cache everything from current length to upper
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1182 self.dataset.cached_examples.append(
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1183 self.dataset.source_dataset[self.current])
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1184 self.example._values = self.dataset.cached_examples[self.current]
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1185 self.current+=1
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1186 return self.example
252
856d14dc4468 implemented CachedDataSet.__iter__ as an optimization
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 251
diff changeset
1187
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1188 return CacheIteratorIter(self)
252
856d14dc4468 implemented CachedDataSet.__iter__ as an optimization
Frederic Bastien <bastienf@iro.umontreal.ca>
parents: 251
diff changeset
1189
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1190 class ApplyFunctionDataSet(DataSet):
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1191 """
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1192 A L{DataSet} that contains as fields the results of applying a
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1193 given function example-wise or minibatch-wise to all the fields of
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1194 an input dataset. The output of the function should be an iterable
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1195 (e.g. a list or a LookupList) over the resulting values.
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1196
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1197 The function take as input the fields of the dataset, not the examples.
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1198
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1199 In minibatch mode, the function is expected to work on minibatches
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1200 (takes a minibatch in input and returns a minibatch in output). More
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1201 precisely, it means that each element of the input or output list
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1202 should be iterable and indexable over the individual example values
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1203 (typically these elements will be numpy arrays). All of the elements
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1204 in the input and output lists should have the same length, which is
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1205 the length of the minibatch.
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1206
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1207 The function is applied each time an example or a minibatch is accessed.
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1208 To avoid re-doing computation, wrap this dataset inside a CachedDataSet.
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1209
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1210 If the values_{h,v}stack functions are not provided, then
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1211 the input_dataset.values{H,V}Stack functions are used by default.
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1212 """
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1213 def __init__(self,input_dataset,function,output_names,minibatch_mode=True,
3f1cd8897fda reverting dataset
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diff changeset
1214 values_hstack=None,values_vstack=None,
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James Bergstra <bergstrj@iro.umontreal.ca>
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1215 description=None,fieldtypes=None):
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1216 """
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1217 Constructor takes an input dataset that has as many fields as the function
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James Bergstra <bergstrj@iro.umontreal.ca>
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1218 expects as inputs. The resulting dataset has as many fields as the function
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1219 produces as outputs, and that should correspond to the number of output names
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1220 (provided in a list).
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1221
268
3f1cd8897fda reverting dataset
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1222 Note that the expected semantics of the function differs in minibatch mode
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diff changeset
1223 (it takes minibatches of inputs and produces minibatches of outputs, as
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1224 documented in the class comment).
211
bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 203
diff changeset
1225
268
3f1cd8897fda reverting dataset
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diff changeset
1226 TBM: are filedtypes the old field types (from input_dataset) or the new ones
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1227 (for the new dataset created)?
3f1cd8897fda reverting dataset
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diff changeset
1228 """
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1229 self.input_dataset=input_dataset
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diff changeset
1230 self.function=function
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1231 self.output_names=output_names
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1232 self.minibatch_mode=minibatch_mode
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diff changeset
1233 DataSet.__init__(self,description,fieldtypes)
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1234 self.valuesHStack = values_hstack if values_hstack else input_dataset.valuesHStack
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diff changeset
1235 self.valuesVStack = values_vstack if values_vstack else input_dataset.valuesVStack
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
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diff changeset
1236
268
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diff changeset
1237 def __len__(self):
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diff changeset
1238 return len(self.input_dataset)
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1239
268
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1240 def fieldNames(self):
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1241 return self.output_names
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1242
268
3f1cd8897fda reverting dataset
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diff changeset
1243 def minibatches_nowrap(self,fieldnames,minibatch_size,n_batches,offset):
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James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1244 class ApplyFunctionIterator(object):
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1245 def __init__(self,output_dataset):
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diff changeset
1246 self.input_dataset=output_dataset.input_dataset
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diff changeset
1247 self.output_dataset=output_dataset
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diff changeset
1248 self.input_iterator=self.input_dataset.minibatches(minibatch_size=minibatch_size,
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1249 n_batches=n_batches,offset=offset).__iter__()
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1250
268
3f1cd8897fda reverting dataset
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diff changeset
1251 def __iter__(self): return self
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1252
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1253 def next(self):
3f1cd8897fda reverting dataset
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diff changeset
1254 function_inputs = self.input_iterator.next()
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diff changeset
1255 all_output_names = self.output_dataset.output_names
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parents: 266
diff changeset
1256 if self.output_dataset.minibatch_mode:
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parents: 266
diff changeset
1257 function_outputs = self.output_dataset.function(*function_inputs)
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parents: 266
diff changeset
1258 else:
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parents: 266
diff changeset
1259 input_examples = zip(*function_inputs)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1260 output_examples = [self.output_dataset.function(*input_example)
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parents: 266
diff changeset
1261 for input_example in input_examples]
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diff changeset
1262 function_outputs = [self.output_dataset.valuesVStack(name,values)
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diff changeset
1263 for name,values in zip(all_output_names,
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diff changeset
1264 zip(*output_examples))]
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parents: 266
diff changeset
1265 all_outputs = Example(all_output_names,function_outputs)
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diff changeset
1266 if fieldnames==all_output_names:
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parents: 266
diff changeset
1267 return all_outputs
3f1cd8897fda reverting dataset
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diff changeset
1268 return Example(fieldnames,[all_outputs[name] for name in fieldnames])
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1269
211
bd728c83faff in __get__, problem if the i.stop was None, i being the slice, added one line replacing None by the len(self)
Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
parents: 203
diff changeset
1270
268
3f1cd8897fda reverting dataset
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diff changeset
1271 return ApplyFunctionIterator(self)
73
69f97aad3faf Coded untested ApplyFunctionDataSet and CacheDataSet
bengioy@bengiomac.local
parents: 72
diff changeset
1272
268
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
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diff changeset
1273 def __iter__(self): # only implemented for increased efficiency
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diff changeset
1274 class ApplyFunctionSingleExampleIterator(object):
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diff changeset
1275 def __init__(self,output_dataset):
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diff changeset
1276 self.current=0
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diff changeset
1277 self.output_dataset=output_dataset
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parents: 266
diff changeset
1278 self.input_iterator=output_dataset.input_dataset.__iter__()
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parents: 266
diff changeset
1279 def __iter__(self): return self
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parents: 266
diff changeset
1280 def next(self):
3f1cd8897fda reverting dataset
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parents: 266
diff changeset
1281 if self.output_dataset.minibatch_mode:
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parents: 266
diff changeset
1282 function_inputs = [[input] for input in self.input_iterator.next()]
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parents: 266
diff changeset
1283 outputs = self.output_dataset.function(*function_inputs)
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parents: 266
diff changeset
1284 assert all([hasattr(output,'__iter__') for output in outputs])
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parents: 266
diff changeset
1285 function_outputs = [output[0] for output in outputs]
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parents: 266
diff changeset
1286 else:
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diff changeset
1287 function_inputs = self.input_iterator.next()
3f1cd8897fda reverting dataset
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parents: 266
diff changeset
1288 function_outputs = self.output_dataset.function(*function_inputs)
3f1cd8897fda reverting dataset
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 266
diff changeset
1289 return Example(self.output_dataset.output_names,function_outputs)
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parents: 266
diff changeset
1290 return ApplyFunctionSingleExampleIterator(self)
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diff changeset
1291
57
1aabd2e2bb5f Added empty classes with doc: CachedDataSet and ApplyFunctionDataSet
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents: 56
diff changeset
1292
23
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1293 def supervised_learning_dataset(src_dataset,input_fields,target_fields,weight_field=None):
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1294 """
167
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
1295 Wraps an arbitrary L{DataSet} into one for supervised learning tasks
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
1296 by forcing the user to define a set of fields as the 'input' field
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
1297 and a set of fields as the 'target' field. Optionally, a single
4803cb76e26b Updated documentation
Joseph Turian <turian@gmail.com>
parents: 166
diff changeset
1298 weight_field can also be defined.
23
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1299 """
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1300 args = ((input_fields,'input'),(output_fields,'target'))
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1301 if weight_field: args+=(([weight_field],'weight'))
36
438440ba0627 Rewriting dataset.py completely
bengioy@zircon.iro.umontreal.ca
parents: 29
diff changeset
1302 return src_dataset.merge_fields(*args)
23
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1303
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1304
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1305
526e192b0699 Working on ApplyFunctionDataSet, added constraint that
bengioy@esprit.iro.umontreal.ca
parents: 22
diff changeset
1306