When dealing with shape errors, the best strategy (in my experience) is to work with a cut down data set that has the same dims. You can iterate faster that way then scale back up once you have a solution.
When dealing with shape errors, the best strategy (in my experience) is to work with a cut down data set that has the same dims. You can iterate faster that way then scale back up once you have a solution.