import os import hdl reload(hdl) from hdl.models import SparseSlowModel from hdl.hdl import HDL from hdl.config import tstring, state_dir timestring = tstring() model_base_name = 'HDL_loga_' + timestring + '/layer_%s' m1 = SparseSlowModel() layer1_name = 'SparseSlowModel_patchsz020_N512_NN512_l2_subspacel1_dist_2012-05-24_17-33-06/model.model' fname = os.path.join(state_dir,layer1_name) m1.load(fname) m1.model_name = model_base_name % '1' model_sequence = [ m1, SparseSlowModel(patch_sz=None, N=512, T=48, sparse_cost='subspacel1', slow_cost='dist', perc_var=99.9, tstring=timestring, model_name=model_base_name % '2'), SparseSlowModel(patch_sz=None, N=256, T=48, sparse_cost='l1', slow_cost=None, perc_var=99.9, tstring=timestring, model_name=model_base_name % '3')] hdl_learner = HDL(model_sequence=model_sequence,datasource='PLoS09_Cars_Planes',output_function='proj_loga') hdl_learner.learn(layer_start=1)
reload(hdl) from hdl.models import SparseSlowModel from hdl.hdl import HDL from hdl.config import tstring timestring = tstring() model_base_name = 'HDL_loga_' + timestring + '/layer_%s' #model_sequence = [ # SparseSlowModel(patch_sz=16, N=200, sparse_cost='subspacel1', slow_cost='dist', tstring=timestring, model_name=model_base_name % '1'), # SparseSlowModel(patch_sz=None, N=300, sparse_cost='subspacel1', slow_cost='dist', perc_var=99., tstring=timestring, model_name=model_base_name % '2'), # SparseSlowModel(patch_sz=None, N=100, sparse_cost='l1', slow_cost=None, perc_var=99., tstring=timestring, model_name=model_base_name % '3')] #model_sequence = [ # SparseSlowModel(patch_sz=32, N=2048, sparse_cost='subspacel1', slow_cost='dist', tstring=timestring, model_name=model_base_name % '1'), # SparseSlowModel(patch_sz=32, N=2048, sparse_cost='subspacel1', slow_cost='dist', perc_var=99., tstring=timestring, model_name=model_base_name % '2'), # SparseSlowModel(patch_sz=32, N=2048, sparse_cost='l1', slow_cost=None, perc_var=99., tstring=timestring, model_name=model_base_name % '3')] # #hdl_learner = HDL(model_sequence=model_sequence,datasource='vid075-chunks',output_function='infer_loga') model_sequence = [ SparseSlowModel(patch_sz=48, N=512, T=48, sparse_cost='subspacel1', slow_cost=None, tstring=timestring, model_name=model_base_name % '1'), SparseSlowModel(patch_sz=None, N=256, T=48, sparse_cost='subspacel1', slow_cost=None, perc_var=99., tstring=timestring, model_name=model_base_name % '2'), SparseSlowModel(patch_sz=None, N=128, T=48, sparse_cost='l1', slow_cost=None, perc_var=99., tstring=timestring, model_name=model_base_name % '3')] hdl_learner = HDL(model_sequence=model_sequence,datasource='YouTubeFaces_aligned',output_function='proj_loga') hdl_learner.learn()