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#pragma once
#ifdef __GNUC__
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wunused-parameter"
#endif
//===- TFUtils.h - utilities for tensorflow C API ---------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
#ifndef LLVM_ANALYSIS_UTILS_TFUTILS_H
#define LLVM_ANALYSIS_UTILS_TFUTILS_H
#include "llvm/Config/llvm-config.h"
#ifdef LLVM_HAVE_TFLITE
#include "llvm/ADT/StringMap.h"
#include "llvm/Analysis/TensorSpec.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/Support/JSON.h"
#include <memory>
#include <vector>
namespace llvm {
/// Load a SavedModel, find the given inputs and outputs, and setup storage
/// for input tensors. The user is responsible for correctly dimensioning the
/// input tensors and setting their values before calling evaluate().
/// To initialize:
/// - construct the object
/// - initialize the input tensors using initInput. Indices must correspond to
/// indices in the InputNames used at construction.
/// To use:
/// - set input values by using getInput to get each input tensor, and then
/// setting internal scalars, for all dimensions (tensors are row-major:
/// https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/c/c_api.h#L205)
/// - call evaluate. The input tensors' values are not consumed after this, and
/// may still be read.
/// - use the outputs in the output vector
class TFModelEvaluatorImpl;
class EvaluationResultImpl;
class TFModelEvaluator final {
public:
/// The result of a model evaluation. Handles the lifetime of the output
/// tensors, which means that their values need to be used before
/// the EvaluationResult's dtor is called.
class EvaluationResult {
public:
EvaluationResult(const EvaluationResult &) = delete;
EvaluationResult &operator=(const EvaluationResult &Other) = delete;
EvaluationResult(EvaluationResult &&Other);
EvaluationResult &operator=(EvaluationResult &&Other);
~EvaluationResult();
/// Get a (const) pointer to the first element of the tensor at Index.
template <typename T> T *getTensorValue(size_t Index) {
return static_cast<T *>(getUntypedTensorValue(Index));
}
template <typename T> const T *getTensorValue(size_t Index) const {
return static_cast<T *>(getUntypedTensorValue(Index));
}
/// Get a (const) pointer to the untyped data of the tensor.
void *getUntypedTensorValue(size_t Index);
const void *getUntypedTensorValue(size_t Index) const;
private:
friend class TFModelEvaluator;
EvaluationResult(std::unique_ptr<EvaluationResultImpl> Impl);
std::unique_ptr<EvaluationResultImpl> Impl;
};
TFModelEvaluator(StringRef SavedModelPath,
const std::vector<TensorSpec> &InputSpecs,
const std::vector<TensorSpec> &OutputSpecs,
const char *Tags = "serve");
~TFModelEvaluator();
TFModelEvaluator(const TFModelEvaluator &) = delete;
TFModelEvaluator(TFModelEvaluator &&) = delete;
/// Evaluate the model, assuming it is valid. Returns std::nullopt if the
/// evaluation fails or the model is invalid, or an EvaluationResult
/// otherwise. The inputs are assumed to have been already provided via
/// getInput(). When returning std::nullopt, it also invalidates this object.
std::optional<EvaluationResult> evaluate();
/// Provides access to the input vector.
template <typename T> T *getInput(size_t Index) {
return static_cast<T *>(getUntypedInput(Index));
}
/// Returns true if the tensorflow model was loaded successfully, false
/// otherwise.
bool isValid() const { return !!Impl; }
/// Untyped access to input.
void *getUntypedInput(size_t Index);
private:
std::unique_ptr<TFModelEvaluatorImpl> Impl;
};
} // namespace llvm
#endif // LLVM_HAVE_TFLITE
#endif // LLVM_ANALYSIS_UTILS_TFUTILS_H
#ifdef __GNUC__
#pragma GCC diagnostic pop
#endif
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