def __init__(self, input_ch, e_ch,
h_k_szs, h_dils,
causality=True,
use_glu=False):
super(SeqEncoder, self).__init__()
h_io_chs = [e_ch]*len(h_k_szs)
self.front_1x1 = nn.Conv1d(input_ch, e_ch,1)
self.h_block = HighwayDCBlock(h_io_chs, h_k_szs, h_dils, causality=causality, use_glu=use_glu)
self.mid_1x1 = nn.Sequential(nn.Conv1d(e_ch,e_ch,1), nn.ReLU(),
nn.Conv1d(e_ch,e_ch,1), nn.ReLU())
self.last_1x1 = nn.Sequential(nn.Conv1d(e_ch,e_ch,1))
def __init__(self, input_ch, e_ch,
h_io_chs=[1,1,1,1,1,1,1],
h_k_szs=[2,2,2,2,2,1,1],
h_dils=[1,2,4,8,16,1,1],
use_glu=False):
super(SeqClassifier, self).__init__()
h_io_chs[:] = [n * e_ch for n in h_io_chs]
self.front_1x1 = nn.Conv1d(input_ch, e_ch,1)
self.h_block = HighwayDCBlock(h_io_chs, h_k_szs, h_dils, causality=True, use_glu=use_glu)
self.last_1x1 = nn.Sequential(nn.Conv1d(e_ch,e_ch,1), nn.ReLU(),
nn.Conv1d(e_ch,e_ch,1), nn.ReLU())
self.classifier = nn.Sequential(nn.Conv1d(e_ch,e_ch,1), nn.ReLU(),
nn.Conv1d(e_ch,e_ch,1))#nn.Conv1d(e_ch,1,1))
def __init__(self, input_dim, e_ch, #d_ch=256,
#h_io_chs=[256, 256, 256, 256, 256, 256, 256],
d_ch,
h_io_chs=[1,1,1,1,1,1,1],
h_k_szs=[2,2,2,2,2,1,1],
h_dils=[1,2,4,8,16,1,1],
# h_dils=[1,2,4,1,2,4,1,2,4,1,1,1,1], #이것도 Receptive Field가 20인데 왜 안되는걸까??????
use_glu=False):
super(SeqFeatEnc, self).__init__()
h_io_chs[:] = [n * d_ch for n in h_io_chs]
# Layers:
self.mlp = nn.Sequential(nn.Conv1d(input_dim,e_ch,1),
nn.ReLU(),
nn.Conv1d(e_ch,d_ch,1))
self.h_block = HighwayDCBlock(h_io_chs, h_k_szs, h_dils, causality=True, use_glu=use_glu)
return None