我正在尝试获取一个TensorFlow Lite示例以在具有ARM Cortex-A72处理器的计算机上运行。不幸的是,由于缺少有关如何使用C ++ API的示例,因此我无法部署测试模型。我将尝试解释到目前为止我所取得的成就。
创建tflite模型
我创建了一个简单的线性回归模型并将其转换为近似函数f(x) = 2x - 1
。我从一些教程中获得了此代码段,但现在找不到了。
import tensorflow as tf
import numpy as np
from tensorflow import keras
from tensorflow.contrib import lite
model = keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])
model.compile(optimizer='sgd', loss='mean_squared_error')
xs = np.array([ -1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
ys = np.array([ -3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
model.fit(xs, ys, epochs=500)
print(model.predict([10.0]))
keras_file = 'linear.h5'
keras.models.save_model(model, keras_file)
converter = lite.TocoConverter.from_keras_model_file(keras_file)
tflite_model = converter.convert()
open('linear.tflite', 'wb').write(tflite_model)
这将创建一个名为的二进制文件linear.tflite
,我应该可以加载它。
为我的机器编译TensorFlow Lite
TensorFlow Lite随附一个脚本,用于在具有aarch64架构的计算机上进行编译。即使必须稍加修改Makefile,我仍按照此处的指南进行操作。请注意,我是在目标系统上本地编译的。这创建了一个名为的静态库libtensorflow-lite.a
。
问题:推论
我尝试按照此处站点上的教程进行操作,只是将加载和运行模型中的代码段粘贴在一起,例如
class FlatBufferModel {
// Build a model based on a file. Return a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromFile(
const char* filename,
ErrorReporter* error_reporter);
// Build a model based on a pre-loaded flatbuffer. The caller retains
// ownership of the buffer and should keep it alive until the returned object
// is destroyed. Return a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromBuffer(
const char* buffer,
size_t buffer_size,
ErrorReporter* error_reporter);
};
tflite::FlatBufferModel model("./linear.tflite");
tflite::ops::builtin::BuiltinOpResolver resolver;
std::unique_ptr<tflite::Interpreter> interpreter;
tflite::InterpreterBuilder(*model, resolver)(&interpreter);
// Resize input tensors, if desired.
interpreter->AllocateTensors();
float* input = interpreter->typed_input_tensor<float>(0);
// Fill `input`.
interpreter->Invoke();
float* output = interpreter->typed_output_tensor<float>(0);
当试图通过编译
g++ demo.cpp libtensorflow-lite.a
我遇到了很多错误。日志:
root@localhost:/inference# g++ demo.cpp libtensorflow-lite.a
demo.cpp:3:15: error: ‘unique_ptr’ in namespace ‘std’ does not name a template type
static std::unique_ptr<FlatBufferModel> BuildFromFile(
^~~~~~~~~~
demo.cpp:10:15: error: ‘unique_ptr’ in namespace ‘std’ does not name a template type
static std::unique_ptr<FlatBufferModel> BuildFromBuffer(
^~~~~~~~~~
demo.cpp:16:1: error: ‘tflite’ does not name a type
tflite::FlatBufferModel model("./linear.tflite");
^~~~~~
demo.cpp:18:1: error: ‘tflite’ does not name a type
tflite::ops::builtin::BuiltinOpResolver resolver;
^~~~~~
demo.cpp:19:6: error: ‘unique_ptr’ in namespace ‘std’ does not name a template type
std::unique_ptr<tflite::Interpreter> interpreter;
^~~~~~~~~~
demo.cpp:20:1: error: ‘tflite’ does not name a type
tflite::InterpreterBuilder(*model, resolver)(&interpreter);
^~~~~~
demo.cpp:23:1: error: ‘interpreter’ does not name a type
interpreter->AllocateTensors();
^~~~~~~~~~~
demo.cpp:25:16: error: ‘interpreter’ was not declared in this scope
float* input = interpreter->typed_input_tensor<float>(0);
^~~~~~~~~~~
demo.cpp:25:48: error: expected primary-expression before ‘float’
float* input = interpreter->typed_input_tensor<float>(0);
^~~~~
demo.cpp:28:1: error: ‘interpreter’ does not name a type
interpreter->Invoke();
^~~~~~~~~~~
demo.cpp:30:17: error: ‘interpreter’ was not declared in this scope
float* output = interpreter->typed_output_tensor<float>(0);
^~~~~~~~~~~
demo.cpp:30:50: error: expected primary-expression before ‘float’
float* output = interpreter->typed_output_tensor<float>(0);
我是C ++的新手,所以这里可能缺少明显的东西。但是,似乎其他人也对C ++ API感到麻烦(请参见GitHub问题)。是否有人也偶然发现并运行了它?
我要介绍的最重要方面是:
1.)我在哪里以及如何定义签名,以便模型知道将什么视为输入和输出?
2.)我必须包括哪些标题?
谢谢!
编辑
感谢@Alex Cohn,链接器能够找到正确的标头。我还意识到,我可能不需要重新定义flatbuffers类,因此我得到了以下代码(标记了小更改):
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/kernels/register.h"
#include "tensorflow/lite/model.h"
#include "tensorflow/lite/tools/gen_op_registration.h"
auto model = tflite::FlatBufferModel::BuildFromFile("linear.tflite"); //CHANGED
tflite::ops::builtin::BuiltinOpResolver resolver;
std::unique_ptr<tflite::Interpreter> interpreter;
tflite::InterpreterBuilder(*model, resolver)(&interpreter);
// Resize input tensors, if desired.
interpreter->AllocateTensors();
float* input = interpreter->typed_input_tensor<float>(0);
// Fill `input`.
interpreter->Invoke();
float* output = interpreter->typed_output_tensor<float>(0);
这样可以大大减少错误的数量,但是我不确定如何解决其余的错误:
root@localhost:/inference# g++ demo.cpp -I/tensorflow
demo.cpp:10:34: error: expected ‘)’ before ‘,’ token
tflite::InterpreterBuilder(*model, resolver)(&interpreter);
^
demo.cpp:10:44: error: expected initializer before ‘)’ token
tflite::InterpreterBuilder(*model, resolver)(&interpreter);
^
demo.cpp:13:1: error: ‘interpreter’ does not name a type
interpreter->AllocateTensors();
^~~~~~~~~~~
demo.cpp:18:1: error: ‘interpreter’ does not name a type
interpreter->Invoke();
^~~~~~~~~~~
我该如何解决这些问题?看来我必须定义自己的解析器,但是我不知道该怎么做。
这是最小的包括:
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/kernels/register.h"
#include "tensorflow/lite/model.h"
#include "tensorflow/lite/tools/gen_op_registration.h"
这些将包括其他标头,例如<memory>
define std::unique_ptr
。
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