Removed sde_type from FlowMatchingSimformer as unused

Author: nMaax

sbi/inference/trainers/vfpe/simformer.py

@@ -139,7 +139,6 @@ def __init__(
             str,
             MaskedVectorFieldEstimatorBuilder,
         ] = "simformer",
-        sde_type: Literal["vp", "ve", "subvp"] = "ve",
         posterior_latent_idx: Optional[list | Tensor] = None,
         posterior_observed_idx: Optional[list | Tensor] = None,
         device: str = "cpu",
@@ -159,7 +158,6 @@ def __init__(
             or a callable that implements the `MaskedVectorFieldEstimatorBuilder`
             protocol. If a callable, `__call__` must accept `inputs`, and return
             a `MaskedConditionalVectorFieldEstimator`.
-            sde_type: Type of SDE to use. Must be one of ['vp', 've', 'subvp'].
             posterior_latent_idx: List or Tensor of indexes identifying which
             variables are latent (to be infered),
             i.e, which variables identify $\theta$.
@@ -182,7 +180,6 @@ def __init__(
             logging_level=logging_level,
             summary_writer=summary_writer,
             show_progress_bars=show_progress_bars,
-            sde_type=sde_type,
             **kwargs,
         )
 

sbi/neural_nets/factory.py

@@ -710,7 +710,6 @@ def simformer_flow_nn(
 
     Args:
         model (str): Name of the model architecture to use. Default is "simformer".
-        sde_type (str): Type of stochastic differential equation (SDE) to use.
         hidden_features (int): Number of hidden features in each layer. Default is 100.
         num_heads (int): Number of attention heads in the transformer layers.
         num_layers (int): Number of transformer layers. Default is 8.