from sals.models import sgd_optimizer from sals.models import FCLayer, GeneralModel, ConvLayer from sals.utils.DataHelper import DataMan_msra from sals.utils.FunctionHelper import * import numpy as np import theano import theano.tensor as T import time if __name__ == '__main__': file_msra = '../data/msra_flatten.pkl' msra = DataMan_msra() if not os.path.isfile(file_msra): msra.convert2pkl(file_msra) cpudata = msra.load() msra.share2gpumem(cpudata) bs = 200 imL = 48 filterL = 5 recfield = 2 nfilter1 = 32 x = T.matrix(name='x', dtype=theano.config.floatX) y = T.matrix(name='y', dtype=theano.config.floatX) layer0 = x.reshape((bs, 3, imL, imL)) conv1 = ConvLayer(input = layer0, image_shape = (bs, 3, imL, imL),
from sals.models import sgd_optimizer from sals.models import FCLayer, GeneralModel, ConvLayer from sals.utils.DataHelper import DataMan_msra from sals.utils.FunctionHelper import * import numpy as np import theano import theano.tensor as T import time if __name__ == '__main__': msra = DataMan_msra('../data/msra_norm3.pkl') cpudata = msra.load() msra.share2gpumem(cpudata) bs = 1000 imL = 48 filterL = 5 recfield = 2 nfilter1 = 32 nfilter2 = 32 filterL2= 5 x = T.matrix(name='x', dtype=theano.config.floatX) y = T.matrix(name='y', dtype=theano.config.floatX) layer0 = x.reshape((bs, 3, imL, imL)) conv1 = ConvLayer(input = layer0, image_shape = (bs, 3, imL, imL), filter_shape =(nfilter1, 3, filterL, filterL), pool_shape = (recfield, recfield),