netket.nn.MaskedDense1D# class netket.nn.MaskedDense1D[source]# Bases: Module 1D linear transformation module with mask for autoregressive NN. Attributes precision: Any = None# numerical precision of the computation, see jax.lax.Precision for details. use_bias: bool = True# True). Type: whether to add a bias to the output (default features: int# output feature density, should be the last dimension. exclusive: bool# True if an output element does not depend on the input element at the same index. kernel_init: Callable[[Any, Sequence[int], Any], Union[ndarray, Array]]# initializer for the weight matrix. bias_init: Callable[[Any, Sequence[int], Any], Union[ndarray, Array]]# initializer for the bias. Methods __call__(inputs)[source]# Applies a masked linear transformation to the inputs. Parameters: inputs (Union[ndarray, Array]) – input data with dimensions (batch, length, features). Return type: Union[ndarray, Array] Returns: The transformed data.
