from cle.cle.train import Training from cle.cle.train.ext import (EpochCount, GradientClipping, Monitoring, Picklize) from cle.cle.train.opt import RMSProp from cle.cle.utils import flatten, OrderedDict from cle.datasets.music import Music data_path = '/home/junyoung/data/music/MuseData.pickle' save_path = '/home/junyoung/repos/cle/saved/' batch_size = 10 nlabel = 105 debug = 1 model = Model() train_data = Music(name='train', path=data_path, nlabel=nlabel) valid_data = Music(name='valid', path=data_path, nlabel=nlabel) # Choose the random initialization method init_W = InitCell('randn') init_U = InitCell('ortho') init_b = InitCell('zeros') x, y, mask = train_data.theano_vars() # You must use THEANO_FLAGS="compute_test_value=raise" python -m ipdb if debug: x.tag.test_value = np.zeros((10, batch_size, nlabel), dtype=np.float32) y.tag.test_value = np.zeros((10, batch_size, nlabel), dtype=np.float32) mask.tag.test_value = np.ones((10, batch_size), dtype=np.float32)
) from cle.cle.train.opt import RMSProp from cle.cle.utils import init_tparams, sharedX from cle.cle.utils.compat import OrderedDict from cle.datasets.music import Music data_path = '/home/junyoung/data/music/MuseData.pickle' save_path = '/home/junyoung/repos/cle/saved/' batch_size = 10 nlabel = 105 debug = 1 model = Model() train_data = Music(name='train', path=data_path, nlabel=nlabel) valid_data = Music(name='valid', path=data_path, nlabel=nlabel) # Choose the random initialization method init_W = InitCell('randn') init_U = InitCell('ortho') init_b = InitCell('zeros') x, y, mask = train_data.theano_vars() # You must use THEANO_FLAGS="compute_test_value=raise" python -m ipdb if debug: x.tag.test_value = np.zeros((10, batch_size, nlabel), dtype=np.float32)
from cle.cle.utils import OrderedDict from cle.datasets.music import Music #data_path = '/data/lisa/data/music/MuseData.pickle' #save_path = '/u/chungjun/repos/cle/saved/' data_path = '/home/junyoung/data/music/MuseData.pickle' save_path = '/home/junyoung/repos/cle/saved/' batch_size = 10 nlabel = 105 debug = 0 model = Model() trdata = Music(name='train', path=data_path, nlabel=nlabel) valdata = Music(name='valid', path=data_path, nlabel=nlabel) # Choose the random initialization method init_W = InitCell('randn') init_U = InitCell('ortho') init_b = InitCell('zeros') model.inputs = trdata.theano_vars() x, y, mask = model.inputs # You must use THEANO_FLAGS="compute_test_value=raise" python -m ipdb if debug: x.tag.test_value = np.zeros((10, batch_size, nlabel), dtype=np.float32)