| Conditions | 7 |
| Total Lines | 97 |
| Code Lines | 60 |
| Lines | 0 |
| Ratio | 0 % |
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
| 1 | """ |
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| 122 | def test_config_sanity_check(caplog): |
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| 123 | """ |
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| 124 | Test config_sanity_check by check error messages |
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| 125 | |||
| 126 | :param caplog: used to check warning message. |
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| 127 | """ |
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| 128 | |||
| 129 | # unknown data type |
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| 130 | with pytest.raises(ValueError) as err_info: |
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| 131 | config_sanity_check(config=dict(dataset=dict(type="type"))) |
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| 132 | assert "data type must be paired / unpaired / grouped" in str(err_info.value) |
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| 133 | |||
| 134 | # unknown data format |
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| 135 | with pytest.raises(ValueError) as err_info: |
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| 136 | config_sanity_check(config=dict(dataset=dict(type="paired", format="format"))) |
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| 137 | assert "data format must be nifti / h5" in str(err_info.value) |
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| 138 | |||
| 139 | # dir is not in data_config |
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| 140 | with pytest.raises(AssertionError): |
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| 141 | config_sanity_check(config=dict(dataset=dict(type="paired", format="h5"))) |
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| 142 | |||
| 143 | # dir doesn't have train/valid/test |
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| 144 | with pytest.raises(AssertionError): |
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| 145 | config_sanity_check( |
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| 146 | config=dict(dataset=dict(type="paired", format="h5", dir=dict())) |
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| 147 | ) |
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| 148 | |||
| 149 | # train/valid/test of dir is not string or list of string |
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| 150 | with pytest.raises(ValueError) as err_info: |
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| 151 | config_sanity_check( |
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| 152 | config=dict( |
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| 153 | dataset=dict( |
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| 154 | type="paired", |
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| 155 | format="h5", |
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| 156 | dir=dict(train=1, valid=None, test=None), |
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| 157 | labeled=True, |
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| 158 | ), |
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| 159 | train=dict(model=dict(method="ddf")), |
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| 160 | ) |
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| 161 | ) |
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| 162 | assert "data_dir for mode train must be string or list of strings" in str( |
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| 163 | err_info.value |
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| 164 | ) |
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| 165 | |||
| 166 | # use unlabeled data for conditional model |
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| 167 | with pytest.raises(ValueError) as err_info: |
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| 168 | config_sanity_check( |
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| 169 | config=dict( |
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| 170 | dataset=dict( |
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| 171 | type="paired", |
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| 172 | format="h5", |
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| 173 | dir=dict(train=None, valid=None, test=None), |
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| 174 | labeled=False, |
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| 175 | ), |
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| 176 | train=dict( |
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| 177 | method="conditional", |
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| 178 | loss=dict(), |
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| 179 | preprocess=dict(), |
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| 180 | optimizer=dict(name="Adam"), |
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| 181 | ), |
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| 182 | ) |
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| 183 | ) |
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| 184 | assert "For conditional model, data have to be labeled, got unlabeled data." in str( |
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| 185 | err_info.value |
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| 186 | ) |
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| 187 | |||
| 188 | # check warnings |
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| 189 | # train/valid/test of dir is None |
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| 190 | # all loss weight <= 0 |
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| 191 | caplog.clear() # clear previous log |
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| 192 | config_sanity_check( |
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| 193 | config=dict( |
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| 194 | dataset=dict( |
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| 195 | type="paired", |
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| 196 | format="h5", |
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| 197 | dir=dict(train=None, valid=None, test=None), |
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| 198 | labeled=False, |
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| 199 | ), |
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| 200 | train=dict( |
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| 201 | method="ddf", |
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| 202 | loss=dict( |
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| 203 | image=dict(name="lncc", weight=0.0), |
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| 204 | label=dict(name="ssd", weight=0.0), |
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| 205 | regularization=dict(name="bending", weight=0.0), |
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| 206 | ), |
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| 207 | preprocess=dict(), |
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| 208 | optimizer=dict(name="Adam"), |
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| 209 | ), |
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| 210 | ) |
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| 211 | ) |
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| 212 | # warning messages can be detected together |
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| 213 | assert "Data directory for train is not defined." in caplog.text |
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| 214 | assert "Data directory for valid is not defined." in caplog.text |
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| 215 | assert "Data directory for test is not defined." in caplog.text |
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| 216 | assert "The image loss weight 0.00 is not positive." in caplog.text |
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| 217 | assert "The label loss weight 0.00 is not positive." in caplog.text |
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| 218 | assert "The regularization loss weight 0.00 is not positive." in caplog.text |
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| 219 |