Batch Predict Scenarios — batch_predict_scenarios • rminte

Run batch predictions with the LSTM model. This is a low-level function for advanced use cases where you need fine-grained control over batching.

For most use cases, prefer run_malaria_emulator() which handles model loading and batching automatically.

Usage

batch_predict_scenarios(
  model,
  X,
  device,
  predictor,
  batch_size = 32L,
  use_amp = FALSE
)

Arguments

model: A loaded PyTorch LSTM model (nn.Module).
X: A numpy array of input features with shape [B, T, F] (batch, timesteps, features).
device: A torch device object.
predictor: Character. Type of predictor ("prevalence" or "cases").
batch_size: Integer. Batch size for inference. Default 32.
use_amp: Logical. Use automatic mixed precision. Default FALSE.

Value

A numpy array of predictions with shape [B, T].

See also

run_malaria_emulator(), predict_full_sequence()