Method __init__

models/float/encoder.py:199–226

(self, size, w_dim=512)

class EncoderApp(nn.Module):
	def __init__(self, size, w_dim=512):
		super(EncoderApp, self).__init__()

		channels = {
			4: 512,
			8: 512,
			16: 512,
			32: 512,
			64: 256,
			128: 128,
			256: 64,
			512: 32,
			1024: 16
		}

		self.w_dim = w_dim
		log_size = int(math.log(size, 2))

		self.convs = nn.ModuleList()
		self.convs.append(ConvLayer(3, channels[size], 1))

		in_channel = channels[size]
		for i in range(log_size, 2, -1):
			out_channel = channels[2 ** (i - 1)]
			self.convs.append(ResBlock(in_channel, out_channel))
			in_channel = out_channel

		self.convs.append(EqualConv2d(in_channel, self.w_dim, 4, padding=0, bias=False))

	def forward(self, x):