Implementation file for the abstraction of a tensor type, and JSON loading utils. More...

#include "SerDes/TensorSpec.h"
#include "llvm/ADT/None.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/JSON.h"
#include <array>
#include <cassert>
#include <numeric>

Include dependency graph for TensorSpec.cpp:

Go to the source code of this file.

Namespaces
namespace	MLBridge

Macros
#define	TFUTILS_GETDATATYPE_IMPL(T, E) template <> TensorType TensorSpec::getDataType<T>() { return TensorType::E; }

#define	TFUTILS_GETNAME_IMPL(T, _) #T,

#define	PARSE_TYPE(T, E)

#define	_IMR_DBG_PRINTER(T, N)

Functions
StringRef	MLBridge::toString (TensorType TT)

llvm::Optional< TensorSpec >	MLBridge::getTensorSpecFromJSON (LLVMContext &Ctx, const json::Value &Value)

std::string	MLBridge::tensorValueToString (const char *Buffer, const TensorSpec &Spec)
	For debugging.

Detailed Description

Implementation file for the abstraction of a tensor type, and JSON loading utils.

Definition in file TensorSpec.cpp.

Macro Definition Documentation

◆ _IMR_DBG_PRINTER

#define _IMR_DBG_PRINTER	(		T,
			N )

Value:

  case TensorType::N: {                                                        \
    const T *TypedBuff = reinterpret_cast<const T *>(Buffer);                  \
    auto R = llvm::make_range(TypedBuff, TypedBuff + Spec.getElementCount());  \
    return llvm::join(                                                         \
        llvm::map_range(R, [](T V) { return std::to_string(V); }), ",");       \
  }

◆ PARSE_TYPE

#define PARSE_TYPE	(		T,
			E )

Value:

if (TensorType == #T) \

return TensorSpec::createSpec<T>(TensorName, TensorShape, TensorPort);

◆ TFUTILS_GETDATATYPE_IMPL

#define TFUTILS_GETDATATYPE_IMPL	(		T,
			E ) template <> TensorType TensorSpec::getDataType<T>() { return TensorType::E; }

Definition at line 31 of file TensorSpec.cpp.

◆ TFUTILS_GETNAME_IMPL

#define TFUTILS_GETNAME_IMPL	(		T,
			_ ) #T,

Namespaces