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) )