如何解决TFLite:微可变操作解析器未命名类型
我正在尝试使用 MicroMutableOpsResolver 类编译基于 TFLite 微型的 Arduino 草图(仅包含减少内存使用所需的操作)。
虽然在 TF lite 示例中看到类似的用法 - https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/micro_speech_test.cc
但是一直遇到下面的编译错误。
IMU_Classifier_TinyML:22:1: error: 'micro_op_resolver' does not name a type
micro_op_resolver.AddFullyConnected();
^~~~~~~~~~~~~~~~~
IMU_Classifier_TinyML:23:1: error: 'micro_op_resolver' does not name a type
micro_op_resolver.Addsoftmax();
^~~~~~~~~~~~~~~~~
IMU_Classifier_TinyML:24:1: error: 'micro_op_resolver' does not name a type
micro_op_resolver.AddRelu();
^~~~~~~~~~~~~~~~~
Using library Arduino_LSM9DS1 at version 1.1.0 in folder: /home/balaji/Arduino/libraries/Arduino_LSM9DS1
Using library Wire in folder: /home/balaji/.arduino15/packages/arduino/hardware/mbed/1.3.2/libraries/Wire (legacy)
Using library Arduino_TensorFlowLite at version 2.4.0-ALPHA in folder: /home/balaji/Arduino/libraries/Arduino_TensorFlowLite
exit status 1
'micro_op_resolver' does not name a type
代码片段如下所示:
#include <Arduino_LSM9DS1.h>
#include <TensorFlowLite.h>
#include <tensorflow/lite/micro/micro_mutable_op_resolver.h>
#include <tensorflow/lite/micro/kernels/micro_ops.h>
#include <tensorflow/lite/micro/micro_error_reporter.h>
#include <tensorflow/lite/micro/micro_interpreter.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <tensorflow/lite/version.h>
// Include the TFlite converted model header file
#include "model.h"
const float accelThreshold = 2.5;
const int numOfSamples = 119; // acceleration sample-rate
int samplesRead = numOfSamples;
tflite::MicroErrorReporter tfLiteErrorReporter;
/*Import only the required ops to reduce the memory usage*/
static tflite::MicroMutableOpResolver<3> micro_op_resolver;
micro_op_resolver.AddFullyConnected();
micro_op_resolver.Addsoftmax();
micro_op_resolver.AddRelu();
我是否缺少任何依赖项,或者这可能是由于 TF lite 版本不匹配造成的?
解决方法
至少像 micro_op_resolver.AddFullyConnected();
这样的函数调用必须放在函数体中。这样的东西应该编译:
#include <Arduino_LSM9DS1.h>
#include <TensorFlowLite.h>
#include <tensorflow/lite/micro/micro_mutable_op_resolver.h>
#include <tensorflow/lite/micro/kernels/micro_ops.h>
#include <tensorflow/lite/micro/micro_error_reporter.h>
#include <tensorflow/lite/micro/micro_interpreter.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <tensorflow/lite/version.h>
// Include the TFlite converted model header file
#include "model.h"
const float accelThreshold = 2.5;
const int numOfSamples = 119; // acceleration sample-rate
int samplesRead = numOfSamples;
tflite::MicroErrorReporter tfLiteErrorReporter;
/*Import only the required ops to reduce the memory usage*/
static tflite::MicroMutableOpResolver<3> micro_op_resolver;
void setup() {
micro_op_resolver.AddFullyConnected();
micro_op_resolver.AddSoftmax();
micro_op_resolver.AddRelu();
}
void loop() {
// put your main code here,to run repeatedly:
}
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