Mercurial > pylearn
annotate test_dataset.py @ 132:f6505ec32dc3
Updated documentation slightly
| author | Joseph Turian <turian@gmail.com> |
|---|---|
| date | Thu, 08 May 2008 00:54:14 -0400 |
| parents | d3c72e412065 |
| children | 86bc934a7518 |
| rev | line source |
|---|---|
|
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the script can be autorun
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1 #!/bin/env python |
| 45 | 2 from dataset import * |
| 3 from math import * | |
| 4 import numpy | |
| 5 | |
|
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6 def have_raised(to_eval): |
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7 have_thrown = False |
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8 try: |
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9 eval(to_eval) |
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10 except : |
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11 have_thrown = True |
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12 return have_thrown |
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13 |
| 45 | 14 def test1(): |
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15 print "test1" |
| 45 | 16 global a,ds |
| 17 a = numpy.random.rand(10,4) | |
| 18 print a | |
| 19 ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]}) | |
| 20 print "len(ds)=",len(ds) | |
| 54 | 21 assert(len(ds)==10) |
| 45 | 22 print "example 0 = ",ds[0] |
| 54 | 23 # assert |
| 45 | 24 print "x=",ds["x"] |
| 25 print "x|y" | |
| 26 for x,y in ds("x","y"): | |
| 27 print x,y | |
| 28 minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4) | |
| 29 minibatch = minibatch_iterator.__iter__().next() | |
| 30 print "minibatch=",minibatch | |
| 31 for var in minibatch: | |
| 32 print "var=",var | |
|
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33 print "take a slice and look at field y",ds[1:6:2]["y"] |
| 45 | 34 |
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35 def test_ArrayDataSet(): |
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36 #don't test stream |
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37 #tested only with float value |
| 106 | 38 #don't always test with y |
| 39 #don't test missing value | |
| 40 #don't test with tuple | |
| 41 #don't test proterties | |
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42 def test_iterate_over_examples(array,ds): |
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43 #not in doc!!! |
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44 i=0 |
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45 for example in range(len(ds)): |
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46 assert (ds[example]['x']==a[example][:3]).all() |
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47 assert ds[example]['y']==a[example][3] |
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48 assert (ds[example]['z']==a[example][[0,2]]).all() |
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49 i+=1 |
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50 assert i==len(ds) |
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51 del example,i |
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52 |
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53 # - for example in dataset: |
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54 i=0 |
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55 for example in ds: |
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56 assert len(example)==3 |
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57 assert (example['x']==array[i][:3]).all() |
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58 assert example['y']==array[i][3] |
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59 assert (example['z']==array[i][0:3:2]).all() |
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60 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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61 i+=1 |
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62 assert i==len(ds) |
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63 del example,i |
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64 |
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65 # - for val1,val2,... in dataset: |
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66 i=0 |
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67 for x,y,z in ds: |
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68 assert (x==array[i][:3]).all() |
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69 assert y==array[i][3] |
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70 assert (z==array[i][0:3:2]).all() |
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71 assert (numpy.append(x,y)==array[i]).all() |
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72 i+=1 |
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73 assert i==len(ds) |
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74 del x,y,z,i |
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75 |
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76 # - for example in dataset(field1, field2,field3, ...): |
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77 i=0 |
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78 for example in ds('x','y','z'): |
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79 assert len(example)==3 |
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80 assert (example['x']==array[i][:3]).all() |
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81 assert example['y']==array[i][3] |
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82 assert (example['z']==array[i][0:3:2]).all() |
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83 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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84 i+=1 |
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85 assert i==len(ds) |
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86 del example,i |
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87 i=0 |
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88 for example in ds('y','x'): |
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89 assert len(example)==2 |
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90 assert (example['x']==array[i][:3]).all() |
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91 assert example['y']==array[i][3] |
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92 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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93 i+=1 |
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94 assert i==len(ds) |
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95 del example,i |
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96 |
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97 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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98 i=0 |
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99 for x,y,z in ds('x','y','z'): |
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100 assert (x==array[i][:3]).all() |
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101 assert y==array[i][3] |
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102 assert (z==array[i][0:3:2]).all() |
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103 assert (numpy.append(x,y)==array[i]).all() |
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104 i+=1 |
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105 assert i==len(ds) |
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106 del x,y,z,i |
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107 i=0 |
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108 for y,x in ds('y','x',): |
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109 assert (x==array[i][:3]).all() |
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110 assert y==array[i][3] |
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111 assert (numpy.append(x,y)==array[i]).all() |
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112 i+=1 |
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113 assert i==len(ds) |
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114 del x,y,i |
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115 |
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116 def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished): |
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117 ##full minibatch or the last minibatch |
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118 for idx in range(nb_field): |
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119 test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished) |
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120 del idx |
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121 def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished): |
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122 assert len(minibatch_field)==minibatch_size or ((nb_iter_finished*minibatch_size+len(minibatch_field))==len_ds and len(minibatch_field)<minibatch_size) |
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123 |
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124 # - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N): |
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125 i=0 |
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126 mi=0 |
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127 m=ds.minibatches(['x','z'], minibatch_size=3) |
| 104 | 128 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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129 for minibatch in m: |
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130 assert len(minibatch)==2 |
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131 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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132 assert (minibatch[0][:,0:3:2]==minibatch[1]).all() |
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102
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133 mi+=1 |
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134 i+=len(minibatch[0]) |
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135 assert i==len(ds) |
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136 assert mi==4 |
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137 del minibatch,i,m,mi |
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138 |
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139 i=0 |
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102
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140 mi=0 |
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141 m=ds.minibatches(['x','y'], minibatch_size=3) |
| 104 | 142 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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143 for minibatch in m: |
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144 assert len(minibatch)==2 |
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145 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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146 mi+=1 |
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147 for id in range(len(minibatch[0])): |
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148 assert (numpy.append(minibatch[0][id],minibatch[1][id])==a[i]).all() |
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149 i+=1 |
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150 assert i==len(ds) |
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151 assert mi==4 |
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152 del minibatch,i,id,m,mi |
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153 |
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154 # - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N): |
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155 i=0 |
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156 mi=0 |
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157 m=ds.minibatches(['x','z'], minibatch_size=3) |
| 104 | 158 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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159 for x,z in m: |
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160 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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161 test_minibatch_field_size(z,m.minibatch_size,len(ds),mi) |
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162 assert (x[:,0:3:2]==z).all() |
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163 i+=len(x) |
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164 mi+=1 |
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165 assert i==len(ds) |
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166 assert mi==4 |
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167 del x,z,i,m,mi |
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168 i=0 |
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169 mi=0 |
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170 m=ds.minibatches(['x','y'], minibatch_size=3) |
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171 for x,y in m: |
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172 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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173 test_minibatch_field_size(y,m.minibatch_size,len(ds),mi) |
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174 mi+=1 |
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175 for id in range(len(x)): |
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176 assert (numpy.append(x[id],y[id])==a[i]).all() |
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177 i+=1 |
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178 assert i==len(ds) |
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179 assert mi==4 |
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180 del x,y,i,id,m,mi |
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181 |
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182 #not in doc |
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183 i=0 |
| 104 | 184 m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4) |
| 185 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) | |
| 186 for x,y in m: | |
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187 assert len(x)==3 |
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188 assert len(y)==3 |
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189 for id in range(3): |
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190 assert (numpy.append(x[id],y[id])==a[i+4]).all() |
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191 i+=1 |
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192 assert i==3 |
| 104 | 193 del x,y,i,id,m |
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194 |
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195 i=0 |
| 104 | 196 m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4) |
| 197 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) | |
| 198 for x,y in m: | |
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199 assert len(x)==3 |
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200 assert len(y)==3 |
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201 for id in range(3): |
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202 assert (numpy.append(x[id],y[id])==a[i+4]).all() |
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203 i+=1 |
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204 assert i==6 |
| 104 | 205 del x,y,i,id,m |
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206 |
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207 i=0 |
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103
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208 m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4) |
| 104 | 209 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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100
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210 for x,y in m: |
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211 assert len(x)==3 |
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212 assert len(y)==3 |
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213 for id in range(3): |
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214 assert (numpy.append(x[id],y[id])==a[(i+4)%a.shape[0]]).all() |
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215 i+=1 |
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216 assert i==m.n_batches*m.minibatch_size |
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217 del x,y,i,id |
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218 |
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219 |
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220 def test_ds_iterator(array,iterator1,iterator2,iterator3): |
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221 i=0 |
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222 for x,y in iterator1: |
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223 assert (x==array[i][:3]).all() |
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224 assert y==array[i][3] |
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225 assert (numpy.append(x,y)==array[i]).all() |
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226 i+=1 |
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227 assert i==len(ds) |
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228 i=0 |
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229 for y,z in iterator2: |
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230 assert y==array[i][3] |
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231 assert (z==array[i][0:3:2]).all() |
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232 i+=1 |
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233 assert i==len(ds) |
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234 i=0 |
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235 for x,y,z in iterator3: |
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236 assert (x==array[i][:3]).all() |
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237 assert y==array[i][3] |
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238 assert (z==array[i][0:3:2]).all() |
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239 assert (numpy.append(x,y)==array[i]).all() |
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240 i+=1 |
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241 assert i==len(ds) |
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242 |
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243 def test_getitem(array,ds): |
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244 |
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245 def test_ds(orig,ds,index): |
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246 i=0 |
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247 assert len(ds)==len(index) |
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248 for x,z,y in ds('x','z','y'): |
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249 assert (orig[index[i]]['x']==array[index[i]][:3]).all() |
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250 assert (orig[index[i]]['x']==x).all() |
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251 assert orig[index[i]]['y']==array[index[i]][3] |
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252 assert orig[index[i]]['y']==y |
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253 assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all() |
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254 assert (orig[index[i]]['z']==z).all() |
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255 i+=1 |
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256 del i |
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257 ds[0] |
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258 if len(ds)>2: |
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259 ds[:1] |
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260 ds[1:1] |
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261 ds[1:1:1] |
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262 if len(ds)>5: |
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263 ds[[1,2,3]] |
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264 for x in ds: |
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265 pass |
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266 |
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267 #ds[:n] returns a dataset with the n first examples. |
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268 ds2=ds[:3] |
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269 assert isinstance(ds2,DataSet) |
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270 test_ds(ds,ds2,index=[0,1,2]) |
| 106 | 271 del ds2 |
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272 |
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273 #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s. |
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274 ds2=ds[1:7:2] |
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275 assert isinstance(ds2,DataSet) |
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276 test_ds(ds,ds2,[1,3,5]) |
| 106 | 277 del ds2 |
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278 |
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279 #ds[i] |
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280 ds2=ds[5] |
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281 assert isinstance(ds2,Example) |
| 106 | 282 assert have_raised("ds["+str(len(ds))+"]") # index not defined |
| 283 assert not have_raised("ds["+str(len(ds)-1)+"]") | |
| 284 del ds2 | |
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285 |
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286 #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in. |
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287 ds2=ds[[4,7,2,8]] |
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288 assert isinstance(ds2,DataSet) |
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289 test_ds(ds,ds2,[4,7,2,8]) |
| 106 | 290 del ds2 |
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291 |
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292 #ds[fieldname]# an iterable over the values of the field fieldname across |
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293 #the ds (the iterable is obtained by default by calling valuesVStack |
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294 #over the values for individual examples). |
| 106 | 295 assert have_raised("ds['h']") # h is not defined... |
| 296 assert have_raised("ds[['x']]") # bad syntax | |
| 297 assert not have_raised("ds['x']") | |
| 298 isinstance(ds['x'],DataSetFields) | |
| 299 ds2=ds['x'] | |
| 300 assert len(ds['x'])==10 | |
| 301 assert len(ds['y'])==10 | |
| 302 assert len(ds['z'])==10 | |
| 303 i=0 | |
| 304 for example in ds['x']: | |
| 305 assert (example==a[i][:3]).all() | |
| 306 i+=1 | |
| 307 i=0 | |
| 308 for example in ds['y']: | |
| 309 assert (example==a[i][3]).all() | |
| 310 i+=1 | |
| 311 i=0 | |
| 312 for example in ds['z']: | |
| 313 assert (example==a[i,0:3:2]).all() | |
| 314 i+=1 | |
| 315 del ds2,i | |
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316 |
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317 #ds.<property># returns the value of a property associated with |
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318 #the name <property>. The following properties should be supported: |
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319 # - 'description': a textual description or name for the ds |
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320 # - 'fieldtypes': a list of types (one per field) |
| 106 | 321 |
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322 #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#???? |
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323 i=0 |
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324 for example in hstack([ds('x'),ds('y'),ds('z')]): |
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325 example==ds[i] |
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326 i+=1 |
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327 del i,example |
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328 #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#???? |
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329 |
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330 |
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331 print "test_ArrayDataSet" |
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332 a = numpy.random.rand(10,4) |
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333 ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested |
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334 ds = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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335 assert len(ds)==10 |
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336 #assert ds==a? should this work? |
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337 |
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338 test_iterate_over_examples(a, ds) |
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339 test_getitem(a, ds) |
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340 |
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341 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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342 test_ds_iterator(a,ds('x','y'),ds('y','z'),ds('x','y','z')) |
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343 |
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344 |
| 63 | 345 assert len(ds.fields())==3 |
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346 for field in ds.fields(): |
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347 for field_value in field: # iterate over the values associated to that field for all the ds examples |
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348 pass |
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349 for field in ds('x','z').fields(): |
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350 pass |
| 60 | 351 for field in ds.fields('x','y'): |
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352 pass |
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353 for field_examples in ds.fields(): |
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354 for example_value in field_examples: |
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355 pass |
| 63 | 356 |
| 357 assert ds == ds.fields().examples() | |
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358 # for ((x,y),a_v) in (ds('x','y'),a): #???don't work # haven't found a variant that work.# will not work |
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359 # assert numpy.append(x,y)==z |
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360 |
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361 def test_LookupList(): |
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362 #test only the example in the doc??? |
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363 print "test_LookupList" |
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364 example = LookupList(['x','y','z'],[1,2,3]) |
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365 example['x'] = [1, 2, 3] # set or change a field |
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366 x, y, z = example |
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367 x = example[0] |
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368 x = example["x"] |
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369 assert example.keys()==['x','y','z'] |
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370 assert example.values()==[[1,2,3],2,3] |
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371 assert example.items()==[('x',[1,2,3]),('y',2),('z',3)] |
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372 example.append_keyval('u',0) # adds item with name 'u' and value 0 |
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373 assert len(example)==4 # number of items = 4 here |
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374 example2 = LookupList(['v','w'], ['a','b']) |
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375 example3 = LookupList(['x','y','z','u','v','w'], [[1, 2, 3],2,3,0,'a','b']) |
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376 assert example+example2==example3 |
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377 assert have_raised("example+example") |
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378 |
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379 def test_ApplyFunctionDataSet(): |
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380 print "test_ApplyFunctionDataSet" |
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381 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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382 def test_CacheDataSet(): |
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383 print "test_CacheDataSet" |
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81
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384 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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385 def test_FieldsSubsetDataSet(): |
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parents:
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386 print "test_FieldsSubsetDataSet" |
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81
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parents:
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387 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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388 def test_DataSetFields(): |
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parents:
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389 print "test_DataSetFields" |
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81
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parents:
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390 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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391 def test_MinibatchDataSet(): |
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parents:
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392 print "test_MinibatchDataSet" |
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81
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parents:
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393 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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394 def test_HStackedDataSet(): |
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parents:
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395 print "test_HStackedDataSet" |
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81
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parents:
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396 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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397 def test_VStackedDataSet(): |
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added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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398 print "test_VStackedDataSet" |
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81
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parents:
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399 raise NotImplementedError() |
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84
aa9e786ee849
added function have_raised that evaluate the string in parameter and return true if the function have raised an exception
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parents:
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400 def test_ArrayFieldsDataSet(): |
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parents:
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401 print "test_ArrayFieldsDataSet" |
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parents:
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402 raise NotImplementedError() |
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Added test for ArrayDataSet and LookUpList
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parents:
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403 |
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74
b4159cbdc06b
Fixed errors raised by test_dataset
Yoshua Bengio <bengioy@iro.umontreal.ca>
parents:
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404 test1() |
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405 test_LookupList() |
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65
d48eba49a2f4
fixed the infinite loop
Yoshua Bengio <bengioy@iro.umontreal.ca>
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406 test_ArrayDataSet() |
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122
d3c72e412065
removed datat that should not be commited
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407 #test pmat.py |