Posted at

raspberry pi 1でtensorflow lite その13


概要

raspberry pi 1でtensorflow liteやってみた。

kerasモデルからtfliteファイルを作ってラズパイで、実行。

データセットは、fizzbuzz.


Makefileを書く。

CXXFLAGS ?= -I../tensorflow -I../tensorflow/tensorflow/lite/tools/make/downloads/flatbuffers/include

LDFLAGS ?= -L../tensorflow/tensorflow/lite/tools/make/gen/rpi_armv6l/lib

.PHONY: all clean

all: lite2

lite2: main.cpp
g++ --std=c++11 main.cpp -O2 $(CXXFLAGS) $(LDFLAGS) -ltensorflow-lite -lstdc++ -lpthread -ldl -lm -o lite2

clean:
rm -f lite2


Makeして実行。

#include <vector>

#include <chrono>
#include <iostream>
#include "tensorflow/lite/model.h"
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/kernels/register.h"
#include <iostream>
#include <fstream>
#include <stdlib.h>
using namespace std;

bool is_error(TfLiteStatus const & status)
{
return status != kTfLiteOk;
}
int main(int argc, char const * argv[])
{
std::string a = "fizzbuzz.tflite";
TfLiteStatus status;
std::unique_ptr<tflite::FlatBufferModel> model;
std::unique_ptr<tflite::Interpreter> interpreter;
std::cout << "0: Loading model: " << a << std::endl;
model = tflite::FlatBufferModel::BuildFromFile(a.c_str());
if (!model)
{
std::cerr << "0: Failed to load the model." << std::endl;
return -1;
}
std::cout << "1: The model was loaded successful." << std::endl;
tflite::ops::builtin::BuiltinOpResolver resolver;
tflite::InterpreterBuilder(* model, resolver)(& interpreter);
std::cout << "2: interpreter was build successful." << std::endl;
status = interpreter->AllocateTensors();
if (is_error(status))
{
std::cerr << "2: Failed to allocate the memory for tensors." << std::endl;
return -1;
}
std::cout << "3: The model was allocated successful." << std::endl;
float * in = interpreter->typed_input_tensor<float>(0);
float * out = interpreter->typed_output_tensor<float>(0);
int i;
for (i = 1; i < 100; i++)
{
in[0] = i & 0x1 ? 1.0f : 0.0f;
in[1] = (i >> 1) & 0x1 ? 1.0f : 0.0f;
in[2] = (i >> 2) & 0x1 ? 1.0f : 0.0f;
in[3] = (i >> 3) & 0x1 ? 1.0f : 0.0f;
in[4] = (i >> 4) & 0x1 ? 1.0f : 0.0f;
in[5] = (i >> 5) & 0x1 ? 1.0f : 0.0f;
in[6] = (i >> 6) & 0x1 ? 1.0f : 0.0f;
status = interpreter->Invoke();
if (is_error(status))
{
std::cerr << "3: Failed to invoke the interpreter." << std::endl;
return -1;
}
if (out[0] > 0.5f) std::printf ("%2d ", i);
if (out[1] > 0.5f) std::printf ("fizz ");
if (out[2] > 0.5f) std::printf ("buzz ");
if (out[3] > 0.5f) std::printf ("fizzbuzz ");

}
cout << "ok" << endl;
return 0;
}


結果

0: Loading model: fizzbuzz.tflite

1: The model was loaded successful.
2: interpreter was build successful.
3: The model was allocated successful.
1 2 fizz 4 buzz fizz 7 8 fizz buzz 11 fizz 13 14 fizzbuzz 16 17 fizz 19 buzz fizz 22 23 fizz buzz 26 fizz 28 29 fizzbuzz 31 32 fizz 34 buzz fizz 37 38 fizz buzz 41 fizz 43 44 fizzbuzz 46 47 fizz 49 buzz fizz 52 53 fizz buzz 56 fizz 58 59 fizzbuzz 61 62 fizz 64 buzz fizz 67 68 fizz buzz 71 fizz 73 74 fizzbuzz 76 77 fizz 79 buzz fizz 82 83 fizz buzz 86 fizz 88 89 fizzbuzz 91 92 fizz 94 buzz fizz 97 98 fizz ok

以上。