def __init__(
self,
n_input: int,
n_batch: int = 0,
n_labels: int = 0,
n_hidden: int = 128,
n_latent: int = 10,
n_layers: int = 1,
dropout_rate: float = 0.1,
dispersion: str = "gene",
log_variational: bool = True,
reconstruction_loss: str = "zinb",
):
super().__init__(
n_input,
n_batch,
n_labels,
n_hidden,
n_latent,
n_layers,
dropout_rate,
dispersion,
log_variational,
reconstruction_loss,
)
self.decoder = LinearDecoderSCVI(
n_latent,
n_input,
n_cat_list=[n_batch],
n_layers=n_layers,
n_hidden=n_hidden,
)
def __init__(
self,
n_input: int,
n_batch: int = 0,
n_labels: int = 0,
n_hidden: int = 128,
n_latent: int = 10,
n_layers_encoder: int = 1,
dropout_rate: float = 0.1,
dispersion: str = "gene",
log_variational: bool = True,
reconstruction_loss: str = "nb",
use_batch_norm: bool = True,
bias: bool = False,
latent_distribution: str = "normal",
):
super().__init__(
n_input,
n_batch,
n_labels,
n_hidden,
n_latent,
n_layers_encoder,
dropout_rate,
dispersion,
log_variational,
reconstruction_loss,
latent_distribution,
)
self.use_batch_norm = use_batch_norm
self.z_encoder = Encoder(
n_input,
n_latent,
n_layers=n_layers_encoder,
n_hidden=n_hidden,
dropout_rate=dropout_rate,
distribution=latent_distribution,
)
self.decoder = LinearDecoderSCVI(
n_latent,
n_input,
n_cat_list=[n_batch],
use_batch_norm=use_batch_norm,
bias=bias,
)