I failed to initialize AI by using msh command, ai_error_type:51, ai_error_code:65

[Fire Liang]

I have written my neural network code and converted it into C language code using STM32CubeMX AI tool. I copied the generated three source code (Network. c, network_data.c and Network_data_ams.c) and the relevant header files into my original project. Compile successfully without error message. However, after downloading my code to my hardware device, I failed to initialize AI by using msh command, ai_error_type:51, ai_error_code:65.

Here is the relevant AI execution code I added with the msh command.

/* Global handle to reference the instantiated C-model */
static ai_handle network = AI_HANDLE_NULL;
 
/* Global c-array to handle the activations buffer */
AI_ALIGNED(32)
static ai_u8 activations[AI_NETWORK_1_DATA_ACTIVATIONS_SIZE];
 
AI_ALIGNED(32)
static ai_float in_data[AI_NETWORK_1_IN_1_SIZE];
 
AI_ALIGNED(32)
static ai_float out_data[AI_NETWORK_1_OUT_1_SIZE];
 
/* Array of pointer to manage the model's input/output tensors */
static ai_buffer *ai_input;
static ai_buffer *ai_output;
static ai_buffer_format fmt_input;
static ai_buffer_format fmt_output;
 
#define NSIZE 3
 
void buf_print(void)
{
	rt_kprintf("in_data:");
	for (int i=0; i<AI_NETWORK_1_IN_1_SIZE; i++)
	{
		rt_kprintf("%.2f ",((ai_float*)in_data)[i]);
	}
	rt_kprintf("\n");
	rt_kprintf("out_data:");
	for (int i=0; i<AI_NETWORK_1_OUT_1_SIZE; i++)
	{
		rt_kprintf("%.2f ",((ai_float*)out_data)[i]);
	}
	rt_kprintf("\n");
}
 
void aiPrintBufInfo(const ai_buffer *buffer)
{
	rt_kprintf("(%lu, %lu, %lu, %lu)", AI_BUFFER_SHAPE_ELEM(buffer, AI_SHAPE_BATCH),
			  	  	  	  	  	  	 AI_BUFFER_SHAPE_ELEM(buffer, AI_SHAPE_HEIGHT),
	                                 AI_BUFFER_SHAPE_ELEM(buffer, AI_SHAPE_WIDTH),
	                                 AI_BUFFER_SHAPE_ELEM(buffer, AI_SHAPE_CHANNEL));
	rt_kprintf(" buffer_size:%d ", (int)AI_BUFFER_SIZE(buffer));
}
 
void aiPrintDataType(const ai_buffer_format fmt)
{
    if (AI_BUFFER_FMT_GET_TYPE(fmt) == AI_BUFFER_FMT_TYPE_FLOAT)
    	rt_kprintf("float%d ", (int)AI_BUFFER_FMT_GET_BITS(fmt));
    else if (AI_BUFFER_FMT_GET_TYPE(fmt) == AI_BUFFER_FMT_TYPE_BOOL) {
    	rt_kprintf("bool%d ", (int)AI_BUFFER_FMT_GET_BITS(fmt));
    } else { /* integer type */
    	rt_kprintf("%s%d ", AI_BUFFER_FMT_GET_SIGN(fmt)?"i":"u",
            (int)AI_BUFFER_FMT_GET_BITS(fmt));
    }
}
 
void aiPrintDataInfo(const ai_buffer *buffer,const ai_buffer_format fmt)
{
	  if (buffer->data)
		  rt_kprintf(" @0x%X/%d \n",
	        (int)buffer->data,
	        (int)AI_BUFFER_BYTE_SIZE(AI_BUFFER_SIZE(buffer), fmt)
	    );
	  else
		  rt_kprintf(" (User Domain)/%d \n",
	        (int)AI_BUFFER_BYTE_SIZE(AI_BUFFER_SIZE(buffer), fmt)
	    );
}
 
void aiPrintNetworkInfo(const ai_network_report report)
{
	rt_kprintf("Model name      : %s\n", report.model_name);
	rt_kprintf(" model signature : %s\n", report.model_signature);
	rt_kprintf(" model datetime     : %s\r\n", report.model_datetime);
	rt_kprintf(" compile datetime   : %s\r\n", report.compile_datetime);
	rt_kprintf(" runtime version    : %d.%d.%d\r\n",
	      report.runtime_version.major,
	      report.runtime_version.minor,
	      report.runtime_version.micro);
	if (report.tool_revision[0])
		rt_kprintf(" Tool revision      : %s\r\n", (report.tool_revision[0])?report.tool_revision:"");
	rt_kprintf(" tools version      : %d.%d.%d\r\n",
	      report.tool_version.major,
	      report.tool_version.minor,
	      report.tool_version.micro);
	rt_kprintf(" complexity         : %lu MACC\r\n", (unsigned long)report.n_macc);
	rt_kprintf(" c-nodes            : %d\r\n", (int)report.n_nodes);
 
	rt_kprintf(" map_activations    : %d\r\n", report.map_activations.size);
	  for (int idx=0; idx<report.map_activations.size;idx++) {
	      const ai_buffer *buffer = &report.map_activations.buffer[idx];
	      rt_kprintf("  [%d] ", idx);
	      aiPrintBufInfo(buffer);
	      rt_kprintf("\r\n");
	  }
 
	rt_kprintf(" map_weights        : %d\r\n", report.map_weights.size);
	  for (int idx=0; idx<report.map_weights.size;idx++) {
	      const ai_buffer *buffer = &report.map_weights.buffer[idx];
	      rt_kprintf("  [%d] ", idx);
	      aiPrintBufInfo(buffer);
	      rt_kprintf("\r\n");
	  }
}
 
/*
 * Bootstrap
 */
int aiInit(void) {
  ai_error err;
 
  /* Create and initialize the c-model */
  const ai_handle acts[] = { activations };
  err = ai_network_1_create_and_init(&network, acts, NULL);
  if (err.type != AI_ERROR_NONE) {
	  rt_kprintf("ai_error_type:%d,ai_error_code:%d\r\n",err.type,err.code);
	  return -1;
  }
 
  ai_network_report report;
  if (ai_network_1_get_report(network, &report) != true) {
      rt_kprintf("ai get report error\n");
      return -1;
  }
 
  aiPrintNetworkInfo(report);
 
  /* Reteive pointers to the model's input/output tensors */
  ai_input = ai_network_1_inputs_get(network, NULL);
  ai_output = ai_network_1_outputs_get(network, NULL);
  //
  fmt_input = AI_BUFFER_FORMAT(ai_input);
  fmt_output = AI_BUFFER_FORMAT(ai_output);
 
  rt_kprintf(" n_inputs/n_outputs : %u/%u\r\n", report.n_inputs,
            report.n_outputs);
  rt_kprintf("input :");
  aiPrintBufInfo(ai_input);
  aiPrintDataType(fmt_input);
  aiPrintDataInfo(ai_input, fmt_input);
  //
  rt_kprintf("output :");
  aiPrintBufInfo(ai_output);
  aiPrintDataType(fmt_output);
  aiPrintDataInfo(ai_output, fmt_output);
  return 0;
}
 
 
int acquire_and_process_data(float *in_data,float *feature)
{
	for(int i=0;i<32;i++)
	{
	in_data[i] = feature[i];
	}
	return 0;
}
/*
 * Run inference
 */
int aiRun(const void *in_data, void *out_data) {
  ai_i32 n_batch;
  ai_error err;
 
  /* 1 - Update IO handlers with the data payload */
  ai_input[0].data = AI_HANDLE_PTR(in_data);
  ai_output[0].data = AI_HANDLE_PTR(out_data);
 
  /* 2 - Perform the inference */
  n_batch = ai_network_1_run(network, &ai_input[0], &ai_output[0]);
  if (n_batch != 1) {
	  err = ai_network_1_get_error(network);
	  rt_kprintf("ai_error_type:%d,ai_error_code:%d\r\n",err.type,err.code);
  };
 
  return 0;
}
 
extern float features34[DEC_WAVE_NUM][34];//input_data
 
void test_ai(void)
{
	aiInit();
	buf_print();
//	acquire_and_process_data(in_data, features34[0]);
//	aiRun(in_data, out_data);
//	buf_print();
}
MSH_CMD_EXPORT(test_ai,"test DNN_small_low")

I checked a lot of relevant information online, indicating that hardware CRC was not enabled, but I still confirmed that my hardware CRC was configured through msh command.

rt_uint16_t CheckCRC16(rt_uint8_t *buf, rt_uint16_t len)
{
	static struct hwcrypto_crc_cfg crc16ModbusConfig={
		.last_val = 0xffff,
		.poly = 0x8005,
		.width = 16,
		.flags = CRC_FLAG_REFIN|CRC_FLAG_REFOUT,
		.xorout = 0x0000,
	};
	static struct rt_hwcrypto_device* cryptoDev = RT_NULL;
	struct rt_hwcrypto_ctx* ctx = rt_hwcrypto_crc_create(cryptoDev,HWCRYPTO_CRC_CRC16);
	if(cryptoDev==RT_NULL)
		cryptoDev = rt_hwcrypto_dev_default();	
	rt_hwcrypto_crc_cfg(ctx,&crc16ModbusConfig);
	rt_free(ctx);
	return 0;
//	rt_uint32_t result = rt_hwcrypto_crc_update(ctx, buf, len);
//	return result;
}
MSH_CMD_EXPORT(CheckCRC16,"initialization CRCr")

However, I use __HAL_RCC_CRC_CLK_ENABLE(); The debug runtime does not execute a breakpoint at this point. I cannot solve my problem.

Please help me, thanks!

[FuShenXiao]

I also encounter this problem these days. Already enable the CRC and ai_error_type:51, ai_error_code:65. Have you solved this?

BR