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TensorFlow Probability auto-batching package.
Modules
allocation_strategy module: Live variable analysis.
dsl module: Python-embedded DSL frontend for authoring autobatchable IR programs.
frontend module: AutoGraph-based auto-batching frontend.
instructions module: Instruction language for auto-batching virtual machine.
liveness module: Live variable analysis.
lowering module: Lowering the full IR to stack machine instructions.
numpy_backend module: Numpy backend for auto-batching VM.
stack_optimization module: Optimizing stack usage (pushes and pops).
stackless module: A stackless auto-batching VM.
tf_backend module: TensorFlow (graph) backend for auto-batching VM.
type_inference module: Type inference pass on functional control flow graph.
virtual_machine module: The auto-batching VM itself.
xla module: XLA utilities.
Classes
class Context: Context object for auto-batching multiple Python functions together.
class NumpyBackend: Implements the Numpy backend ops for a PC auto-batching VM.
class TensorFlowBackend: Implements the TF backend ops for a PC auto-batching VM.
class TensorType: TensorType(dtype, shape)
class Type: Type(tensors,)
Functions
truthy(...): Normalizes Tensor ranks for use in if conditions.