|---| | [ View source on GitHub](https://github.com/tensorflow/probability/blob/v0.25.0/tensorflow_probability/python/experimental/auto_batching/__init__.py) | TensorFlow Probability auto-batching package. ## Modules [`allocation_strategy`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/allocation_strategy) module: Live variable analysis. [`dsl`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/dsl) module: Python-embedded DSL frontend for authoring autobatchable IR programs. [`frontend`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/frontend) module: AutoGraph-based auto-batching frontend. [`instructions`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/instructions) module: Instruction language for auto-batching virtual machine. [`liveness`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/liveness) module: Live variable analysis. [`lowering`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/lowering) module: Lowering the full IR to stack machine instructions. [`numpy_backend`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/numpy_backend) module: Numpy backend for auto-batching VM. [`stack_optimization`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/stack_optimization) module: Optimizing stack usage (pushes and pops). [`stackless`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/stackless) module: A stackless auto-batching VM. [`tf_backend`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/tf_backend) module: TensorFlow (graph) backend for auto-batching VM. [`type_inference`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/type_inference) module: Type inference pass on functional control flow graph. [`virtual_machine`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/virtual_machine) module: The auto-batching VM itself. [`xla`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/xla) module: XLA utilities. ## Classes [`class Context`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/Context): Context object for auto-batching multiple Python functions together. [`class NumpyBackend`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/NumpyBackend): Implements the Numpy backend ops for a PC auto-batching VM. [`class TensorFlowBackend`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/TensorFlowBackend): Implements the TF backend ops for a PC auto-batching VM. [`class TensorType`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/TensorType): TensorType(dtype, shape) [`class Type`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/Type): Type(tensors,) ## Functions [`truthy(...)`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/auto_batching/truthy): Normalizes Tensor ranks for use in `if` conditions.