def __init__(self, in_dim, h_dim, n_res_layers, res_h_dim):
super(Decoder, self).__init__()
self.inverse_conv_stack = nn.Sequential(
nn.ConvTranspose2d(64, 64, 2, 1),
ResidualStack(64, 64, res_h_dim, n_res_layers),
nn.ConvTranspose2d(64, 64, 3, 2), nn.ConvTranspose2d(64, 32, 4, 2),
nn.ConvTranspose2d(32, 3, 8, 4, padding=(1, 2)))
def __init__(self, in_dim, h_dim, n_res_layers, res_h_dim,
n_dimension_changes):
super(Decoder, self).__init__()
kernel = 4
stride = 2
upsample_modules = [
*(nn.ConvTranspose2d(h_dim // 2,
h_dim // 2,
kernel_size=kernel,
stride=stride,
padding=1), nn.ReLU())
] * (n_dimension_changes - 2)
self.inverse_conv_stack = nn.Sequential(
nn.ConvTranspose2d(in_dim,
h_dim,
kernel_size=kernel - 1,
stride=stride - 1,
padding=1),
ResidualStack(h_dim, h_dim, res_h_dim, n_res_layers),
nn.ConvTranspose2d(h_dim,
h_dim // 2,
kernel_size=kernel,
stride=stride,
padding=1), nn.ReLU(), *upsample_modules,
nn.ConvTranspose2d(h_dim // 2,
3,
kernel_size=kernel,
stride=stride,
padding=1))
def __init__(self, in_dim, h_dim, n_res_layers, res_h_dim):
super(Decoder, self).__init__()
kernel = 4
stride = 2
self.inverse_conv_stack = nn.Sequential(
nn.ConvTranspose1d(h_dim,
h_dim,
kernel_size=kernel - 1,
stride=stride - 1,
padding=1),
ResidualStack(h_dim, h_dim, res_h_dim, n_res_layers),
nn.ConvTranspose1d(h_dim,
h_dim,
kernel_size=kernel - 1,
stride=stride - 1,
padding=1), nn.ReLU(),
nn.ConvTranspose1d(h_dim,
h_dim // 2,
kernel_size=kernel,
stride=stride,
padding=1), nn.ReLU(),
nn.ConvTranspose1d(h_dim // 2,
in_dim,
kernel_size=kernel,
stride=stride,
padding=1))
def __init__(self, in_dim, h_dim, res_h_dim, n_res_layers):
super(Encoder, self).__init__()
self.conv_stack = nn.Sequential(
nn.Conv2d(in_dim, 32, 8, 4), nn.ReLU(), nn.Conv2d(32, 32, 4, 2),
nn.ReLU(), nn.Conv2d(32, 64, 3, 2),
ResidualStack(64, 64, res_h_dim, n_res_layers))
def __init__(self, channels, h_dim, n_res_layers, res_h_dim):
super(Encoder, self).__init__()
kernel = 4
stride = 2
self.conv_stack = nn.Sequential(
nn.Conv2d(channels, h_dim // 2, kernel_size=kernel,
stride=stride, padding=1),
nn.ReLU(),
nn.Conv2d(h_dim // 2, h_dim, kernel_size=kernel,
stride=stride, padding=1),
nn.ReLU(),
nn.Conv2d(h_dim, h_dim, kernel_size=kernel-1,
stride=stride-1, padding=1),
ResidualStack(
h_dim, h_dim, res_h_dim, n_res_layers)
)