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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.