ctask = SON([('transform_average', SON([('transform_name','translation'),('max',True)])), ('N',NUM_SPLITS), ('ntrain',NTRAIN), ('ntest',NTEST), ('overlap',OVERLAP), ('universe',SON([('image.bg_id',SON([('$ne','gray.tdl')]))])), ('query',[SON([('image.model_id',SON([('$in',CAT[cat1])]))]), SON([('image.model_id',SON([('$in',CAT[cat2])]))])]) ]) mtask = SON([('transform_average', SON([('transform_name','translation'),('max',True)])), ('N',NUM_SPLITS), ('ntrain',NTRAIN), ('ntest',NTEST), ('overlap',OVERLAP), ('universe',SON([('image.bg_id',SON([('$ne','gray.tdl')]))])), ('query',[SON([('image.model_id',SON([('$in',k)]))]) for k in mixup(CAT,[[cat1],[cat2]])]) ]) t1 = copy.deepcopy(ctask) t1['universe'].update(trans_q) t1['task_label'] = cat1 + '/' + cat2 + ' trans' task_set.append(t1) t2 = copy.deepcopy(ctask) t2['universe'].update(inrot_q) t2['task_label'] = cat1 + '/' + cat2 + ' inrot' task_set.append(t2) t3 = copy.deepcopy(mtask) t3['universe'].update(trans_q) t3['task_label'] = cat1 + '/' + cat2 + ' trans mixed'
('N',10), ('ntrain',300), ('ntest',150), ('overlap',.75), ('universe',SON([('image.bg_id','gray.tdl')])), ('query',[SON([('image.model_id',SON([('$in',uset(CAT,k))]))]) for k in tenway_cats]) ]) tenway_mixup_task = SON([ ('transform_average', SON([('transform_name','translation'),('max',True)])), ('N',10), ('ntrain',300), ('ntest',150), ('overlap',.75), ('universe',SON([('image.bg_id','gray.tdl')])), ('query',[SON([('image.model_id',SON([('$in',k)]))]) for k in mixup(CAT,tenway_cats)]) ]) car_plane_cats = [['cars'],['planes']] car_vs_plane_task = SON([ ('transform_average', SON([('transform_name','translation'),('max',True)])), ('N',10), ('ntrain',60), ('ntest',30), ('overlap',.75), ('universe',SON([('image.bg_id','gray.tdl')])), ('query',[SON([('image.model_id',SON([('$in',uset(CAT,k))]))]) for k in car_plane_cats]) ])
[ SON([("image.model_id", SON([("$in", CAT[cat1])]))]), SON([("image.model_id", SON([("$in", CAT[cat2])]))]), ], ), ] ) mtask = SON( [ ("transform_average", SON([("transform_name", "translation"), ("max", True)])), ("N", NUM_SPLITS), ("ntrain", NTRAIN), ("ntest", NTEST), ("overlap", OVERLAP), ("universe", SON([("image.bg_id", "gray.tdl")])), ("query", [SON([("image.model_id", SON([("$in", k)]))]) for k in mixup(CAT, [[cat1], [cat2]])]), ] ) t1 = copy.deepcopy(ctask) t1["universe"].update(trans_q) t1["task_label"] = cat1 + "/" + cat2 + " trans" task_set.append(t1) t2 = copy.deepcopy(ctask) t2["universe"].update(inrot_q) t2["task_label"] = cat1 + "/" + cat2 + " inrot" task_set.append(t2) t3 = copy.deepcopy(mtask) t3["universe"].update(trans_q)