Mercurial > pylearn
annotate test_dataset.py @ 278:f708a14acdbc
removed test for dataset[fieldname] as this is not possible anymore
| author | Frederic Bastien <bastienf@iro.umontreal.ca> |
|---|---|
| date | Thu, 05 Jun 2008 14:40:18 -0400 |
| parents | 6255359318bf |
| children |
| rev | line source |
|---|---|
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59757365a057
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 | |
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229
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Added speed test for ArraDataSet
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5 from misc import * |
| 45 | 6 |
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7 def have_raised(to_eval, **var): |
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8 have_thrown = False |
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9 try: |
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10 eval(to_eval) |
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11 except : |
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12 have_thrown = True |
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13 return have_thrown |
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14 |
| 173 | 15 def have_raised2(f, *args, **kwargs): |
| 16 have_thrown = False | |
| 17 try: | |
| 18 f(*args, **kwargs) | |
| 19 except : | |
| 20 have_thrown = True | |
| 21 return have_thrown | |
| 22 | |
| 45 | 23 def test1(): |
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24 print "test1" |
| 45 | 25 global a,ds |
| 26 a = numpy.random.rand(10,4) | |
| 27 print a | |
| 28 ds = ArrayDataSet(a,{'x':slice(3),'y':3,'z':[0,2]}) | |
| 29 print "len(ds)=",len(ds) | |
| 54 | 30 assert(len(ds)==10) |
| 45 | 31 print "example 0 = ",ds[0] |
| 54 | 32 # assert |
| 45 | 33 print "x=",ds["x"] |
| 34 print "x|y" | |
| 35 for x,y in ds("x","y"): | |
| 36 print x,y | |
| 37 minibatch_iterator = ds.minibatches(fieldnames=['z','y'],n_batches=1,minibatch_size=3,offset=4) | |
| 38 minibatch = minibatch_iterator.__iter__().next() | |
| 39 print "minibatch=",minibatch | |
| 40 for var in minibatch: | |
| 41 print "var=",var | |
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Fixing MinibatchDataSet getitem
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42 print "take a slice and look at field y",ds[1:6:2]["y"] |
| 45 | 43 |
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165
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44 del a,ds,x,y,minibatch_iterator,minibatch,var |
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45 |
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46 def test_iterate_over_examples(array,ds): |
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47 #not in doc!!! |
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48 i=0 |
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49 for example in range(len(ds)): |
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50 assert (ds[example]['x']==array[example][:3]).all() |
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51 assert ds[example]['y']==array[example][3] |
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52 assert (ds[example]['z']==array[example][[0,2]]).all() |
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53 i+=1 |
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54 assert i==len(ds) |
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55 del example,i |
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56 |
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57 # - for example in dataset: |
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58 i=0 |
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59 for example in ds: |
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60 assert len(example)==3 |
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61 assert (example['x']==array[i][:3]).all() |
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62 assert example['y']==array[i][3] |
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63 assert (example['z']==array[i][0:3:2]).all() |
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64 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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65 i+=1 |
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66 assert i==len(ds) |
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67 del example,i |
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68 |
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69 # - for val1,val2,... in dataset: |
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70 i=0 |
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71 for x,y,z in ds: |
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72 assert (x==array[i][:3]).all() |
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73 assert y==array[i][3] |
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74 assert (z==array[i][0:3:2]).all() |
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75 assert (numpy.append(x,y)==array[i]).all() |
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76 i+=1 |
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77 assert i==len(ds) |
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78 del x,y,z,i |
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79 |
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80 # - for example in dataset(field1, field2,field3, ...): |
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81 i=0 |
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82 for example in ds('x','y','z'): |
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83 assert len(example)==3 |
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84 assert (example['x']==array[i][:3]).all() |
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85 assert example['y']==array[i][3] |
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86 assert (example['z']==array[i][0:3:2]).all() |
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87 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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88 i+=1 |
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89 assert i==len(ds) |
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90 del example,i |
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91 i=0 |
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92 for example in ds('y','x'): |
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93 assert len(example)==2 |
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94 assert (example['x']==array[i][:3]).all() |
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95 assert example['y']==array[i][3] |
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96 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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97 i+=1 |
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98 assert i==len(ds) |
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99 del example,i |
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100 |
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101 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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102 i=0 |
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103 for x,y,z in ds('x','y','z'): |
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104 assert (x==array[i][:3]).all() |
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105 assert y==array[i][3] |
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106 assert (z==array[i][0:3:2]).all() |
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107 assert (numpy.append(x,y)==array[i]).all() |
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108 i+=1 |
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109 assert i==len(ds) |
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110 del x,y,z,i |
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111 i=0 |
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112 for y,x in ds('y','x',): |
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113 assert (x==array[i][:3]).all() |
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114 assert y==array[i][3] |
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115 assert (numpy.append(x,y)==array[i]).all() |
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116 i+=1 |
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117 assert i==len(ds) |
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118 del x,y,i |
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119 |
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120 def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished): |
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121 ##full minibatch or the last minibatch |
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122 for idx in range(nb_field): |
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123 test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished) |
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124 del idx |
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125 def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished): |
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126 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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127 |
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128 # - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N): |
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129 i=0 |
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130 mi=0 |
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131 m=ds.minibatches(['x','z'], minibatch_size=3) |
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132 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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133 for minibatch in m: |
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161
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134 assert isinstance(minibatch,DataSetFields) |
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135 assert len(minibatch)==2 |
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136 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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161
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137 if type(ds)==ArrayDataSet: |
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138 assert (minibatch[0][:,::2]==minibatch[1]).all() |
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139 else: |
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162
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140 for j in xrange(len(minibatch[0])): |
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141 (minibatch[0][j][::2]==minibatch[1][j]).all() |
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142 mi+=1 |
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143 i+=len(minibatch[0]) |
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144 assert i==len(ds) |
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145 assert mi==4 |
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146 del minibatch,i,m,mi |
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147 |
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148 i=0 |
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149 mi=0 |
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150 m=ds.minibatches(['x','y'], minibatch_size=3) |
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151 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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152 for minibatch in m: |
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153 assert len(minibatch)==2 |
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154 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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155 mi+=1 |
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156 for id in range(len(minibatch[0])): |
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157 assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all() |
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158 i+=1 |
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159 assert i==len(ds) |
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160 assert mi==4 |
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161 del minibatch,i,id,m,mi |
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162 |
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163 # - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N): |
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164 i=0 |
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165 mi=0 |
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166 m=ds.minibatches(['x','z'], minibatch_size=3) |
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167 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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168 for x,z in m: |
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169 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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170 test_minibatch_field_size(z,m.minibatch_size,len(ds),mi) |
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164
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171 for id in range(len(x)): |
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172 assert (x[id][::2]==z[id]).all() |
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173 i+=1 |
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174 mi+=1 |
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175 assert i==len(ds) |
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176 assert mi==4 |
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177 del x,z,i,m,mi |
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178 i=0 |
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179 mi=0 |
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180 m=ds.minibatches(['x','y'], minibatch_size=3) |
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181 for x,y in m: |
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182 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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183 test_minibatch_field_size(y,m.minibatch_size,len(ds),mi) |
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184 mi+=1 |
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185 for id in range(len(x)): |
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186 assert (numpy.append(x[id],y[id])==array[i]).all() |
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187 i+=1 |
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188 assert i==len(ds) |
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189 assert mi==4 |
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190 del x,y,i,id,m,mi |
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191 |
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192 #not in doc |
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193 i=0 |
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194 m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4) |
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195 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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196 for x,y in m: |
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239
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197 assert len(x)==m.minibatch_size |
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198 assert len(y)==m.minibatch_size |
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199 for id in range(m.minibatch_size): |
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200 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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201 i+=1 |
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239
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202 assert i==m.n_batches*m.minibatch_size |
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203 del x,y,i,id,m |
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204 |
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205 i=0 |
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206 m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4) |
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207 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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208 for x,y in m: |
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239
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209 assert len(x)==m.minibatch_size |
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210 assert len(y)==m.minibatch_size |
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211 for id in range(m.minibatch_size): |
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212 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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213 i+=1 |
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214 assert i==m.n_batches*m.minibatch_size |
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215 del x,y,i,id,m |
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216 |
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217 i=0 |
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218 m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4) |
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219 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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220 for x,y in m: |
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239
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221 assert len(x)==m.minibatch_size |
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222 assert len(y)==m.minibatch_size |
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223 for id in range(m.minibatch_size): |
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224 assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all() |
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225 i+=1 |
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226 assert i==m.n_batches*m.minibatch_size |
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227 del x,y,i,id |
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228 |
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240
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229 #@todo: we can't do minibatch bigger then the size of the dataset??? |
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230 assert have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array)+1,offset=0) |
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231 assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array),offset=0) |
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232 |
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233 def test_ds_iterator(array,iterator1,iterator2,iterator3): |
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234 l=len(iterator1) |
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235 i=0 |
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236 for x,y in iterator1: |
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237 assert (x==array[i][:3]).all() |
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238 assert y==array[i][3] |
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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==l |
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242 i=0 |
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243 for y,z in iterator2: |
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244 assert y==array[i][3] |
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245 assert (z==array[i][0:3:2]).all() |
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246 i+=1 |
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247 assert i==l |
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248 i=0 |
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249 for x,y,z in iterator3: |
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250 assert (x==array[i][:3]).all() |
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251 assert y==array[i][3] |
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252 assert (z==array[i][0:3:2]).all() |
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253 assert (numpy.append(x,y)==array[i]).all() |
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254 i+=1 |
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255 assert i==l |
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256 |
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257 def test_getitem(array,ds): |
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258 def test_ds(orig,ds,index): |
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259 i=0 |
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260 assert len(ds)==len(index) |
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261 for x,z,y in ds('x','z','y'): |
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262 assert (orig[index[i]]['x']==array[index[i]][:3]).all() |
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263 assert (orig[index[i]]['x']==x).all() |
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264 assert orig[index[i]]['y']==array[index[i]][3] |
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265 assert orig[index[i]]['y']==y |
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266 assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all() |
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267 assert (orig[index[i]]['z']==z).all() |
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268 i+=1 |
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269 del i |
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270 ds[0] |
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271 if len(ds)>2: |
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272 ds[:1] |
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273 ds[1:1] |
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274 ds[1:1:1] |
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275 if len(ds)>5: |
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276 ds[[1,2,3]] |
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277 for x in ds: |
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278 pass |
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279 |
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280 #ds[:n] returns a dataset with the n first examples. |
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281 ds2=ds[:3] |
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282 assert isinstance(ds2,DataSet) |
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283 test_ds(ds,ds2,index=[0,1,2]) |
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284 del ds2 |
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285 |
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286 #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s. |
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287 ds2=ds[1:7:2] |
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288 assert isinstance(ds2,DataSet) |
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289 test_ds(ds,ds2,[1,3,5]) |
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290 del ds2 |
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291 |
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292 #ds[i] |
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293 ds2=ds[5] |
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294 assert isinstance(ds2,Example) |
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295 assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds) # index not defined |
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296 assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds) |
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297 del ds2 |
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298 |
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299 #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in. |
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300 ds2=ds[[4,7,2,8]] |
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301 assert isinstance(ds2,DataSet) |
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302 test_ds(ds,ds2,[4,7,2,8]) |
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303 del ds2 |
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304 |
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305 #ds.<property># returns the value of a property associated with |
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306 #the name <property>. The following properties should be supported: |
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307 # - 'description': a textual description or name for the ds |
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308 # - 'fieldtypes': a list of types (one per field) |
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309 |
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310 #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#???? |
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311 #assert hstack([ds('x','y'),ds('z')])==ds |
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312 #hstack([ds('z','y'),ds('x')])==ds |
| 173 | 313 assert have_raised2(hstack,[ds('x'),ds('x')]) |
| 314 assert have_raised2(hstack,[ds('y','x'),ds('x')]) | |
| 315 assert not have_raised2(hstack,[ds('x'),ds('y')]) | |
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316 |
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317 # i=0 |
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318 # for example in hstack([ds('x'),ds('y'),ds('z')]): |
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319 # example==ds[i] |
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320 # i+=1 |
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321 # del i,example |
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322 #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#???? |
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323 |
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324 def test_fields_fct(ds): |
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325 #@todo, fill correctly |
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326 assert len(ds.fields())==3 |
| 168 | 327 i=0 |
| 328 v=0 | |
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329 for field in ds.fields(): |
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330 for field_value in field: # iterate over the values associated to that field for all the ds examples |
| 168 | 331 v+=1 |
| 332 i+=1 | |
| 333 assert i==3 | |
| 334 assert v==3*10 | |
| 335 del i,v | |
| 336 | |
| 337 i=0 | |
| 338 v=0 | |
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339 for field in ds('x','z').fields(): |
| 168 | 340 i+=1 |
| 341 for val in field: | |
| 342 v+=1 | |
| 343 assert i==2 | |
| 344 assert v==2*10 | |
| 345 del i,v | |
| 346 | |
| 347 i=0 | |
| 348 v=0 | |
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349 for field in ds.fields('x','y'): |
| 168 | 350 i+=1 |
| 351 for val in field: | |
| 352 v+=1 | |
| 353 assert i==2 | |
| 354 assert v==2*10 | |
| 355 del i,v | |
| 356 | |
| 357 i=0 | |
| 358 v=0 | |
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359 for field_examples in ds.fields(): |
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360 for example_value in field_examples: |
| 168 | 361 v+=1 |
| 362 i+=1 | |
| 363 assert i==3 | |
| 364 assert v==3*10 | |
| 365 del i,v | |
| 366 | |
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367 assert ds == ds.fields().examples() |
| 168 | 368 assert len(ds('x','y').fields()) == 2 |
| 369 assert len(ds('x','z').fields()) == 2 | |
| 370 assert len(ds('y').fields()) == 1 | |
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371 |
| 168 | 372 del field |
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373 def test_all(array,ds): |
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374 assert len(ds)==10 |
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375 |
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376 test_iterate_over_examples(array, ds) |
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377 test_getitem(array, ds) |
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378 test_ds_iterator(array,ds('x','y'),ds('y','z'),ds('x','y','z')) |
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379 test_fields_fct(ds) |
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380 |
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381 def test_ArrayDataSet(): |
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382 #don't test stream |
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383 #tested only with float value |
| 106 | 384 #don't always test with y |
| 385 #don't test missing value | |
| 386 #don't test with tuple | |
| 387 #don't test proterties | |
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388 print "test_ArrayDataSet" |
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389 a2 = numpy.random.rand(10,4) |
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390 ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested |
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391 ds = ArrayDataSet(a2,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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58
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392 #assert ds==a? should this work? |
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100
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restructuring and added test
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393 |
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194
0040ba0f0666
small refactoring
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394 test_all(a2,ds) |
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169
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added test for CachedDataSet(ds,cache_all_upon_construction=True)
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395 |
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268
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396 del a2, ds |
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81
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Added test for ArrayDataSet and LookUpList
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397 |
| 158 | 398 def test_CachedDataSet(): |
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399 print "test_CacheDataSet" |
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400 a = numpy.random.rand(10,4) |
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401 ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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402 ds2 = CachedDataSet(ds1) |
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403 ds3 = CachedDataSet(ds1,cache_all_upon_construction=True) |
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404 |
| 195 | 405 test_all(a,ds2) |
| 406 test_all(a,ds3) | |
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407 |
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added test for CachedDataSet(ds,cache_all_upon_construction=True)
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408 del a,ds1,ds2,ds3 |
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409 |
|
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410 |
|
161
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411 def test_DataSetFields(): |
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412 print "test_DataSetFields" |
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bugfix test in case it is not an ArrayDataSet
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413 raise NotImplementedError() |
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bugfix test in case it is not an ArrayDataSet
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414 |
|
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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415 def test_ApplyFunctionDataSet(): |
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416 print "test_ApplyFunctionDataSet" |
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202
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Added test for ApplyFunctionDataset
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417 a = numpy.random.rand(10,4) |
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418 a2 = a+1 |
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Added test for ApplyFunctionDataset
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419 ds1 = ArrayDataSet(a,LookupList(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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Added test for ApplyFunctionDataset
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420 |
|
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Added test for ApplyFunctionDataset
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421 ds2 = ApplyFunctionDataSet(ds1,lambda x,y,z: (x+1,y+1,z+1), ['x','y','z'],minibatch_mode=False) |
|
229
d7250ee86f72
Added speed test for ArraDataSet
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422 ds3 = ApplyFunctionDataSet(ds1,lambda x,y,z: (numpy.array(x)+1,numpy.array(y)+1,numpy.array(z)+1), |
|
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Added speed test for ArraDataSet
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423 ['x','y','z'], |
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Added speed test for ArraDataSet
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424 minibatch_mode=True) |
|
202
b9950ae5e54b
Added test for ApplyFunctionDataset
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diff
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|
425 |
|
b9950ae5e54b
Added test for ApplyFunctionDataset
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426 test_all(a2,ds2) |
|
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Added test for ApplyFunctionDataset
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427 test_all(a2,ds3) |
|
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Added test for ApplyFunctionDataset
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428 |
|
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429 del a,ds1,ds2,ds3 |
|
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Added test for ApplyFunctionDataset
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|
430 |
|
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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431 def test_FieldsSubsetDataSet(): |
|
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432 print "test_FieldsSubsetDataSet" |
|
81
4b0859606d05
Added test for ArrayDataSet and LookUpList
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433 raise NotImplementedError() |
|
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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434 def test_MinibatchDataSet(): |
|
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435 print "test_MinibatchDataSet" |
|
81
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Added test for ArrayDataSet and LookUpList
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|
436 raise NotImplementedError() |
|
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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437 def test_HStackedDataSet(): |
|
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|
438 print "test_HStackedDataSet" |
|
81
4b0859606d05
Added test for ArrayDataSet and LookUpList
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|
439 raise NotImplementedError() |
|
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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|
440 def test_VStackedDataSet(): |
|
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441 print "test_VStackedDataSet" |
|
81
4b0859606d05
Added test for ArrayDataSet and LookUpList
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442 raise NotImplementedError() |
|
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:
82
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|
443 def test_ArrayFieldsDataSet(): |
|
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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|
444 print "test_ArrayFieldsDataSet" |
|
81
4b0859606d05
Added test for ArrayDataSet and LookUpList
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diff
changeset
|
445 raise NotImplementedError() |
|
229
d7250ee86f72
Added speed test for ArraDataSet
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parents:
202
diff
changeset
|
446 |
|
d7250ee86f72
Added speed test for ArraDataSet
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parents:
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diff
changeset
|
447 |
|
157
e8c8022582f4
only exec the test if we are the main
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diff
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448 if __name__=='__main__': |
|
268
3f1cd8897fda
reverting dataset
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|
449 test1() |
|
157
e8c8022582f4
only exec the test if we are the main
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|
450 test_ArrayDataSet() |
| 158 | 451 test_CachedDataSet() |
|
202
b9950ae5e54b
Added test for ApplyFunctionDataset
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parents:
195
diff
changeset
|
452 test_ApplyFunctionDataSet() |
|
122
d3c72e412065
removed datat that should not be commited
Frederic Bastien <bastienf@iro.umontreal.ca>
parents:
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diff
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|
453 #test pmat.py |
|
229
d7250ee86f72
Added speed test for ArraDataSet
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202
diff
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|
454 |