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collate.py

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density of the model using the specified AD type, divided by the time taken to
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calculate the log density itself (in AD speak, the primal). Basically:
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<b>smaller means faster.</b></li>
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<li>'<span class="wrong">wrong</span>' means that AD ran but the result was not correct. If this happens
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you should be very wary!</li>
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<li>'<span class="wrong">wrong</span>' means that AD ran but the result was not
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correct. If this happens you should be very wary! Note that this is done by
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comparing against the result obtained using ForwardDiff, i.e., ForwardDiff is
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by definition always 'correct'.</li>
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<li>'<span class="error">error</span>' means that AD didn't run.</li>
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<li>Some of the 'wrong' or 'error' entries have question marks next to them.
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These will link to a GitHub issue or other page that describes the problem.

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