Mercurial > pylearn
annotate _test_dataset.py @ 293:4bfdda107a17
still merging
author | James Bergstra <bergstrj@iro.umontreal.ca> |
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date | Fri, 06 Jun 2008 16:13:17 -0400 |
parents | 174374d59405 |
children | f7924e13e426 |
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 * | |
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4 import numpy,unittest |
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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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42 print "take a slice and look at field y",ds[1:6:2]["y"] |
45 | 43 |
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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)): |
293 | 50 wanted = array[example][:3] |
51 returned = ds[example]['x'] | |
52 if (wanted != returned).all(): | |
53 print 'returned:', returned | |
54 print 'wanted:', wanted | |
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55 assert (ds[example]['x']==array[example][:3]).all() |
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56 assert ds[example]['y']==array[example][3] |
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57 assert (ds[example]['z']==array[example][[0,2]]).all() |
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58 i+=1 |
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59 assert i==len(ds) |
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60 del example,i |
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61 |
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62 # - for example in dataset: |
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63 i=0 |
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64 for example in ds: |
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65 assert len(example)==3 |
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66 assert (example['x']==array[i][:3]).all() |
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67 assert example['y']==array[i][3] |
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68 assert (example['z']==array[i][0:3:2]).all() |
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69 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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70 i+=1 |
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71 assert i==len(ds) |
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72 del example,i |
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73 |
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74 # - for val1,val2,... in dataset: |
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75 i=0 |
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76 for x,y,z in ds: |
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77 assert (x==array[i][:3]).all() |
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78 assert y==array[i][3] |
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79 assert (z==array[i][0:3:2]).all() |
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80 assert (numpy.append(x,y)==array[i]).all() |
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81 i+=1 |
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82 assert i==len(ds) |
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83 del x,y,z,i |
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84 |
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85 # - for example in dataset(field1, field2,field3, ...): |
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86 i=0 |
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87 for example in ds('x','y','z'): |
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88 assert len(example)==3 |
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89 assert (example['x']==array[i][:3]).all() |
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90 assert example['y']==array[i][3] |
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91 assert (example['z']==array[i][0:3:2]).all() |
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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 i=0 |
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97 for example in ds('y','x'): |
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98 assert len(example)==2 |
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99 assert (example['x']==array[i][:3]).all() |
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100 assert example['y']==array[i][3] |
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101 assert (numpy.append(example['x'],example['y'])==array[i]).all() |
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102 i+=1 |
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103 assert i==len(ds) |
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104 del example,i |
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105 |
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106 # - for val1,val2,val3 in dataset(field1, field2,field3): |
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107 i=0 |
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108 for x,y,z in ds('x','y','z'): |
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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 (z==array[i][0:3:2]).all() |
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112 assert (numpy.append(x,y)==array[i]).all() |
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113 i+=1 |
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114 assert i==len(ds) |
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115 del x,y,z,i |
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116 i=0 |
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117 for y,x in ds('y','x',): |
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118 assert (x==array[i][:3]).all() |
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119 assert y==array[i][3] |
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120 assert (numpy.append(x,y)==array[i]).all() |
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121 i+=1 |
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122 assert i==len(ds) |
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123 del x,y,i |
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124 |
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125 def test_minibatch_size(minibatch,minibatch_size,len_ds,nb_field,nb_iter_finished): |
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126 ##full minibatch or the last minibatch |
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127 for idx in range(nb_field): |
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128 test_minibatch_field_size(minibatch[idx],minibatch_size,len_ds,nb_iter_finished) |
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129 del idx |
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130 def test_minibatch_field_size(minibatch_field,minibatch_size,len_ds,nb_iter_finished): |
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131 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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132 |
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133 # - for minibatch in dataset.minibatches([field1, field2, ...],minibatch_size=N): |
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134 i=0 |
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135 mi=0 |
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136 m=ds.minibatches(['x','z'], minibatch_size=3) |
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137 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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138 for minibatch in m: |
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139 assert isinstance(minibatch,DataSetFields) |
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140 assert len(minibatch)==2 |
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141 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
161
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142 if type(ds)==ArrayDataSet: |
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143 assert (minibatch[0][:,::2]==minibatch[1]).all() |
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144 else: |
162
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145 for j in xrange(len(minibatch[0])): |
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146 (minibatch[0][j][::2]==minibatch[1][j]).all() |
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147 mi+=1 |
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148 i+=len(minibatch[0]) |
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149 assert i==len(ds) |
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150 assert mi==4 |
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151 del minibatch,i,m,mi |
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152 |
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153 i=0 |
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154 mi=0 |
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155 m=ds.minibatches(['x','y'], minibatch_size=3) |
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156 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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157 for minibatch in m: |
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158 assert len(minibatch)==2 |
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159 test_minibatch_size(minibatch,m.minibatch_size,len(ds),2,mi) |
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160 mi+=1 |
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161 for id in range(len(minibatch[0])): |
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162 assert (numpy.append(minibatch[0][id],minibatch[1][id])==array[i]).all() |
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163 i+=1 |
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164 assert i==len(ds) |
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165 assert mi==4 |
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166 del minibatch,i,id,m,mi |
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167 |
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168 # - for mini1,mini2,mini3 in dataset.minibatches([field1, field2, field3], minibatch_size=N): |
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169 i=0 |
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170 mi=0 |
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171 m=ds.minibatches(['x','z'], minibatch_size=3) |
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172 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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173 for x,z in m: |
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174 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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175 test_minibatch_field_size(z,m.minibatch_size,len(ds),mi) |
164
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176 for id in range(len(x)): |
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177 assert (x[id][::2]==z[id]).all() |
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178 i+=1 |
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179 mi+=1 |
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180 assert i==len(ds) |
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181 assert mi==4 |
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182 del x,z,i,m,mi |
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183 i=0 |
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184 mi=0 |
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185 m=ds.minibatches(['x','y'], minibatch_size=3) |
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186 for x,y in m: |
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187 test_minibatch_field_size(x,m.minibatch_size,len(ds),mi) |
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188 test_minibatch_field_size(y,m.minibatch_size,len(ds),mi) |
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189 mi+=1 |
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190 for id in range(len(x)): |
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191 assert (numpy.append(x[id],y[id])==array[i]).all() |
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192 i+=1 |
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193 assert i==len(ds) |
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194 assert mi==4 |
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195 del x,y,i,id,m,mi |
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196 |
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197 #not in doc |
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198 i=0 |
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199 m=ds.minibatches(['x','y'],n_batches=1,minibatch_size=3,offset=4) |
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200 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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201 for x,y in m: |
239
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202 assert len(x)==m.minibatch_size |
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203 assert len(y)==m.minibatch_size |
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204 for id in range(m.minibatch_size): |
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205 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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206 i+=1 |
239
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207 assert i==m.n_batches*m.minibatch_size |
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208 del x,y,i,id,m |
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209 |
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210 i=0 |
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211 m=ds.minibatches(['x','y'],n_batches=2,minibatch_size=3,offset=4) |
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212 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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213 for x,y in m: |
239
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214 assert len(x)==m.minibatch_size |
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215 assert len(y)==m.minibatch_size |
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216 for id in range(m.minibatch_size): |
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217 assert (numpy.append(x[id],y[id])==array[i+4]).all() |
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218 i+=1 |
239
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219 assert i==m.n_batches*m.minibatch_size |
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220 del x,y,i,id,m |
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221 |
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222 i=0 |
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223 m=ds.minibatches(['x','y'],n_batches=20,minibatch_size=3,offset=4) |
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224 assert isinstance(m,DataSet.MinibatchWrapAroundIterator) |
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225 for x,y in m: |
239
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226 assert len(x)==m.minibatch_size |
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227 assert len(y)==m.minibatch_size |
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228 for id in range(m.minibatch_size): |
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229 assert (numpy.append(x[id],y[id])==array[(i+4)%array.shape[0]]).all() |
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230 i+=1 |
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231 assert i==m.n_batches*m.minibatch_size |
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232 del x,y,i,id |
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233 |
293 | 234 assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array)+1,offset=0) |
240
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235 assert not have_raised2(ds.minibatches,['x','y'],n_batches=1,minibatch_size=len(array),offset=0) |
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236 |
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237 def test_ds_iterator(array,iterator1,iterator2,iterator3): |
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238 l=len(iterator1) |
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239 i=0 |
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240 for x,y in iterator1: |
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241 assert (x==array[i][:3]).all() |
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242 assert y==array[i][3] |
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243 assert (numpy.append(x,y)==array[i]).all() |
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244 i+=1 |
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245 assert i==l |
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246 i=0 |
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247 for y,z in iterator2: |
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248 assert y==array[i][3] |
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249 assert (z==array[i][0:3:2]).all() |
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250 i+=1 |
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251 assert i==l |
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252 i=0 |
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253 for x,y,z in iterator3: |
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254 assert (x==array[i][:3]).all() |
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255 assert y==array[i][3] |
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256 assert (z==array[i][0:3:2]).all() |
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257 assert (numpy.append(x,y)==array[i]).all() |
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258 i+=1 |
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259 assert i==l |
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260 |
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261 def test_getitem(array,ds): |
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262 def test_ds(orig,ds,index): |
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263 i=0 |
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264 assert len(ds)==len(index) |
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265 for x,z,y in ds('x','z','y'): |
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266 assert (orig[index[i]]['x']==array[index[i]][:3]).all() |
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267 assert (orig[index[i]]['x']==x).all() |
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268 assert orig[index[i]]['y']==array[index[i]][3] |
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269 assert orig[index[i]]['y']==y |
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270 assert (orig[index[i]]['z']==array[index[i]][0:3:2]).all() |
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271 assert (orig[index[i]]['z']==z).all() |
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272 i+=1 |
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273 del i |
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274 ds[0] |
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275 if len(ds)>2: |
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276 ds[:1] |
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277 ds[1:1] |
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278 ds[1:1:1] |
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279 if len(ds)>5: |
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280 ds[[1,2,3]] |
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281 for x in ds: |
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282 pass |
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283 |
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284 #ds[:n] returns a dataset with the n first examples. |
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285 ds2=ds[:3] |
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286 assert isinstance(ds2,DataSet) |
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287 test_ds(ds,ds2,index=[0,1,2]) |
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288 del ds2 |
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289 |
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290 #ds[i1:i2:s]# returns a ds with the examples i1,i1+s,...i2-s. |
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291 ds2=ds[1:7:2] |
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292 assert isinstance(ds2,DataSet) |
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293 test_ds(ds,ds2,[1,3,5]) |
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294 del ds2 |
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295 |
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296 #ds[i] |
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297 ds2=ds[5] |
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298 assert isinstance(ds2,Example) |
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299 assert have_raised("var['ds']["+str(len(ds))+"]",ds=ds) # index not defined |
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300 assert not have_raised("var['ds']["+str(len(ds)-1)+"]",ds=ds) |
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301 del ds2 |
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302 |
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303 #ds[[i1,i2,...in]]# returns a ds with examples i1,i2,...in. |
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304 ds2=ds[[4,7,2,8]] |
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305 assert isinstance(ds2,DataSet) |
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306 test_ds(ds,ds2,[4,7,2,8]) |
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307 del ds2 |
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308 |
269
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309 #ds.<property># returns the value of a property associated with |
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310 #the name <property>. The following properties should be supported: |
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311 # - 'description': a textual description or name for the ds |
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312 # - 'fieldtypes': a list of types (one per field) |
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313 |
269
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314 #* ds1 | ds2 | ds3 == ds.hstack([ds1,ds2,ds3])#???? |
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315 #assert hstack([ds('x','y'),ds('z')])==ds |
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316 #hstack([ds('z','y'),ds('x')])==ds |
173 | 317 assert have_raised2(hstack,[ds('x'),ds('x')]) |
318 assert have_raised2(hstack,[ds('y','x'),ds('x')]) | |
319 assert not have_raised2(hstack,[ds('x'),ds('y')]) | |
269
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320 |
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321 # i=0 |
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322 # for example in hstack([ds('x'),ds('y'),ds('z')]): |
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323 # example==ds[i] |
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324 # i+=1 |
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325 # del i,example |
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326 #* ds1 & ds2 & ds3 == ds.vstack([ds1,ds2,ds3])#???? |
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327 |
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328 def test_fields_fct(ds): |
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329 #@todo, fill correctly |
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330 assert len(ds.fields())==3 |
168 | 331 i=0 |
332 v=0 | |
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333 for field in ds.fields(): |
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334 for field_value in field: # iterate over the values associated to that field for all the ds examples |
168 | 335 v+=1 |
336 i+=1 | |
337 assert i==3 | |
338 assert v==3*10 | |
339 del i,v | |
340 | |
341 i=0 | |
342 v=0 | |
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343 for field in ds('x','z').fields(): |
168 | 344 i+=1 |
345 for val in field: | |
346 v+=1 | |
347 assert i==2 | |
348 assert v==2*10 | |
349 del i,v | |
350 | |
351 i=0 | |
352 v=0 | |
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353 for field in ds.fields('x','y'): |
168 | 354 i+=1 |
355 for val in field: | |
356 v+=1 | |
357 assert i==2 | |
358 assert v==2*10 | |
359 del i,v | |
360 | |
361 i=0 | |
362 v=0 | |
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363 for field_examples in ds.fields(): |
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364 for example_value in field_examples: |
168 | 365 v+=1 |
366 i+=1 | |
367 assert i==3 | |
368 assert v==3*10 | |
369 del i,v | |
370 | |
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371 assert ds == ds.fields().examples() |
168 | 372 assert len(ds('x','y').fields()) == 2 |
373 assert len(ds('x','z').fields()) == 2 | |
374 assert len(ds('y').fields()) == 1 | |
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375 |
168 | 376 del field |
194
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377 def test_all(array,ds): |
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378 assert len(ds)==10 |
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379 |
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380 test_iterate_over_examples(array, ds) |
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381 test_getitem(array, ds) |
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382 test_ds_iterator(array,ds('x','y'),ds('y','z'),ds('x','y','z')) |
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383 test_fields_fct(ds) |
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384 |
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385 class T_DataSet(unittest.TestCase): |
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386 def test_ArrayDataSet(self): |
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387 #don't test stream |
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388 #tested only with float value |
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389 #don't always test with y |
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390 #don't test missing value |
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391 #don't test with tuple |
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392 #don't test proterties |
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393 a2 = numpy.random.rand(10,4) |
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394 ds = ArrayDataSet(a2,{'x':slice(3),'y':3,'z':[0,2]})###???tuple not tested |
292 | 395 ds = ArrayDataSet(a2,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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396 #assert ds==a? should this work? |
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397 |
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398 test_all(a2,ds) |
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399 |
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400 del a2, ds |
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401 |
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402 def test_CachedDataSet(self): |
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403 a = numpy.random.rand(10,4) |
292 | 404 ds1 = ArrayDataSet(a,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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405 ds2 = CachedDataSet(ds1) |
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406 ds3 = CachedDataSet(ds1,cache_all_upon_construction=True) |
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407 |
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408 test_all(a,ds2) |
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409 test_all(a,ds3) |
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410 |
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411 del a,ds1,ds2,ds3 |
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412 |
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413 |
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414 def test_DataSetFields(self): |
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415 raise NotImplementedError() |
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416 |
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417 def test_ApplyFunctionDataSet(self): |
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418 a = numpy.random.rand(10,4) |
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419 a2 = a+1 |
292 | 420 ds1 = ArrayDataSet(a,Example(['x','y','z'],[slice(3),3,[0,2]]))###???tuple not tested |
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421 |
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422 ds2 = ApplyFunctionDataSet(ds1,lambda x,y,z: (x+1,y+1,z+1), ['x','y','z'],minibatch_mode=False) |
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423 ds3 = ApplyFunctionDataSet(ds1,lambda x,y,z: (numpy.array(x)+1,numpy.array(y)+1,numpy.array(z)+1), |
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424 ['x','y','z'], |
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425 minibatch_mode=True) |
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426 |
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427 test_all(a2,ds2) |
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428 test_all(a2,ds3) |
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429 |
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430 del a,ds1,ds2,ds3 |
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431 |
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432 def test_FieldsSubsetDataSet(self): |
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433 raise NotImplementedError() |
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434 def test_MinibatchDataSet(self): |
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435 raise NotImplementedError() |
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436 def test_HStackedDataSet(self): |
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437 raise NotImplementedError() |
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438 def test_VStackedDataSet(self): |
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439 raise NotImplementedError() |
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440 def test_ArrayFieldsDataSet(self): |
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441 raise NotImplementedError() |
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442 |
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443 |
157
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444 if __name__=='__main__': |
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445 unittest.main() |
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446 |