A MLModelRunner that asks for advice from an external agent, or host. More...

#include "llvm/Analysis/InteractiveModelRunner.h"

Inheritance diagram for llvm::InteractiveModelRunner:

Public Member Functions
	InteractiveModelRunner (LLVMContext &Ctx, const std::vector< TensorSpec > &Inputs, const TensorSpec &Advice, StringRef OutboundName, StringRef InboundName)

void	switchContext (StringRef Name) override

virtual	~InteractiveModelRunner ()

Public Member Functions inherited from llvm::MLModelRunner
	MLModelRunner (const MLModelRunner &)=delete

MLModelRunner &	operator= (const MLModelRunner &)=delete

virtual	~MLModelRunner ()=default

template<typename T >
T	evaluate ()

template<typename T , typename I >
T *	getTensor (I FeatureID)

template<typename T , typename I >
const T *	getTensor (I FeatureID) const

void *	getTensorUntyped (size_t Index)

const void *	getTensorUntyped (size_t Index) const

Kind	getKind () const

virtual void	switchContext (StringRef Name)

Static Public Member Functions
static bool	classof (const MLModelRunner *R)

Additional Inherited Members
Public Types inherited from llvm::MLModelRunner
enum class	Kind : int { Unknown , Release , Development , NoOp , Interactive }

Protected Member Functions inherited from llvm::MLModelRunner
	MLModelRunner (LLVMContext &Ctx, Kind Type, size_t NumInputs)

virtual void *	evaluateUntyped ()=0

void	setUpBufferForTensor (size_t Index, const TensorSpec &Spec, void *Buffer)

Protected Attributes inherited from llvm::MLModelRunner
LLVMContext &	Ctx

const Kind	Type

Detailed Description

A MLModelRunner that asks for advice from an external agent, or host.

It uses 2 files - ideally named pipes - one to send data to that agent, and one to receive advice. The data exchange uses the training logger (Utils/TrainingLogger.h) format. Specifically, the compiler will send the log header, set the context, and send observations; the host is expected to reply with a tensor value after each observation as a binary buffer that's conforming to the shape of the advice. Interleaved, the data closely resembles the training log for a log where we don't capture the reward signal.

Note that the correctness of the received data is the responsibility of the host. In particular, if insufficient data were sent, the compiler will block when waiting for an advice.

Note that the host can either open the pipes RW, or open first the pipe to the compiler - i.e. the "Inbound" - and then the "Outbound", to avoid deadlock. This is because the compiler first tries to open the inbound (which will hang until there's a writer on the other end).

Definition at line 38 of file InteractiveModelRunner.h.

Constructor & Destructor Documentation

◆ InteractiveModelRunner()

InteractiveModelRunner::InteractiveModelRunner	(	LLVMContext &	Ctx,
		const std::vector< TensorSpec > &	Inputs,
		const TensorSpec &	Advice,
		StringRef	OutboundName,
		StringRef	InboundName
	)

Definition at line 26 of file InteractiveModelRunner.cpp.

References llvm::MLModelRunner::Ctx, llvm::LLVMContext::emitError(), I, llvm::MLModelRunner::setUpBufferForTensor(), and llvm::size().

◆ ~InteractiveModelRunner()

InteractiveModelRunner::~InteractiveModelRunner ( )

virtual

Definition at line 53 of file InteractiveModelRunner.cpp.

References llvm::sys::fs::closeFile(), and llvm::sys::fs::convertFDToNativeFile().

Member Function Documentation

◆ classof()

static bool llvm::InteractiveModelRunner::classof ( const MLModelRunner * R )

inlinestatic

Definition at line 45 of file InteractiveModelRunner.h.

References llvm::MLModelRunner::Interactive.

◆ switchContext()

void llvm::InteractiveModelRunner::switchContext ( StringRef Name )

inlineoverridevirtual

Reimplemented from llvm::MLModelRunner.

Definition at line 48 of file InteractiveModelRunner.h.

References Name.

The documentation for this class was generated from the following files:

include/llvm/Analysis/InteractiveModelRunner.h
lib/Analysis/InteractiveModelRunner.cpp

Public Member Functions

Static Public Member Functions