[Upload Code]:add CAN_260 Version Code
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@ -247,7 +247,7 @@
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@ -3533,7 +3533,7 @@
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@ -2492,44 +2492,44 @@
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@ -1,7 +1,7 @@
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@ -11,10 +11,10 @@
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2346
CAN/XM-01/.ai/model_model2.tflite_c_graph.json
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CAN/XM-01/.ai/model_model2.tflite_c_graph.json
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CAN/XM-01/.ai/model_model2.tflite_c_info.json
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CAN/XM-01/.ai/model_model2.tflite_c_info.json
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CAN/XM-01/.ai/model_model2.tflite_report.json
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CAN/XM-01/.ai/model_model2.tflite_report.json
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@ -0,0 +1,811 @@
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@ -14,8 +14,8 @@ extern "C"
|
||||
int AiModel(uint8_t *input);
|
||||
int aiInit(void);
|
||||
|
||||
extern const uint8_t test[1024];
|
||||
extern float inputBuf[1024];
|
||||
extern float inputBuf[AI_MODEL_IN_1_SIZE] ;
|
||||
extern const uint8_t test[AI_MODEL_IN_1_SIZE];
|
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|
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extern float aiInData[AI_MODEL_IN_1_SIZE];
|
||||
extern float aiOutData[AI_MODEL_OUT_1_SIZE];
|
||||
|
||||
@ -22,10 +22,10 @@ AI_ALIGNED(32)
|
||||
ai_u8 activations[AI_MODEL_DATA_ACTIVATIONS_SIZE];
|
||||
|
||||
AI_ALIGNED(32)
|
||||
const uint8_t test[1024] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 46, 99, 64, 42, 20, 7, 0, 0, 3, 5, 37, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 9, 18, 46, 178, 171, 223, 198, 210, 147, 30, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 23, 56, 78, 79, 84, 62, 77, 109, 188, 138, 97, 61, 18, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 35, 60, 78, 55, 30, 35, 33, 35, 6, 0, 7, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 17, 25, 20, 16, 20, 5, 0, 5, 18, 11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 60, 32, 27, 23, 10, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 16, 46, 37, 46, 38, 12, 6, 0, 0, 0, 15, 4, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 7, 17, 51, 40, 45, 43, 49, 28, 15, 5, 6, 9, 11, 32, 11, 10, 37, 54, 15, 9, 24, 15, 10, 4, 4, 7, 10, 61, 0, 0, 0, 5, 12, 43, 52, 39, 61, 62, 36, 24, 13, 9, 5, 9, 18, 33, 30, 17, 55, 33, 37, 97, 100, 93, 37, 73, 53, 45, 24, 105, 0, 0, 0, 7, 23, 62, 85, 50, 58, 42, 38, 28, 18, 21, 11, 14, 20, 49, 59, 46, 68, 103, 118, 184, 72, 47, 24, 9, 26, 120, 0, 170, 0, 0, 4, 14, 53, 79, 88, 56, 80, 48, 43, 41, 23, 17, 13, 33, 39, 12, 6, 15, 45, 53, 31, 90, 105, 125, 59, 36, 32, 10, 9, 6, 0, 0, 3, 14, 25, 57, 83, 43, 26, 23, 16, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 39, 55, 26, 25, 24, 20, 17, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 29, 77, 58, 45, 29, 23, 38, 30, 8, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 14, 32, 45, 51, 46, 56, 49, 32, 31, 26, 29, 7, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 95, 96, 93, 99, 104, 108, 88, 63, 130, 64, 35, 13, 5, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 21, 64, 89, 90, 90, 94, 104, 99, 84, 72, 31, 19, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 24, 64, 154, 128, 150, 179, 150, 167, 120, 76, 68, 33, 12, 10, 7, 14, 0, 0, 5, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 34, 85, 119, 70, 75, 131, 160, 152, 88, 54, 40, 28, 8, 5, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 42, 79, 51, 46, 59, 73, 72, 72, 100, 75, 89, 74, 42, 12, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7, 15, 18, 18, 29, 40, 40, 36, 43, 56, 88, 57, 22, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 40, 46, 57, 52, 53, 56, 65, 35, 11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 36, 51, 85, 72, 73, 88, 67, 61, 49, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 19, 56, 55, 53, 28, 36, 39, 24, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 14, 35, 64, 79, 64, 89, 44, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 22, 24, 53, 95, 92, 69, 20, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 20, 73, 159, 109, 98, 34, 14, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 22, 55, 51, 69, 49, 49, 23, 11, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 33, 54, 64, 72, 66, 21, 13, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 18, 32, 35, 76, 64, 18, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 15, 25, 25, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
const uint8_t test[AI_MODEL_IN_1_SIZE] = {21, 6, 0, 5, 5, 8, 16, 35, 15, 57, 50, 37, 30, 31, 39, 37, 46, 56, 54, 55, 65, 88, 90, 85, 41, 21, 52, 20, 6, 7, 7, 10, 19, 46, 14, 44, 58, 66, 64, 42, 52, 70, 59, 55, 66, 66, 91, 102, 110, 97, 61, 24, 30, 5, 9, 12, 8, 13, 34, 39, 16, 73, 42, 36, 36, 31, 44, 44, 54, 55, 44, 53, 60, 78, 77, 76, 54, 26, 34, 37, 14, 18, 9, 12, 42, 42, 13, 24, 32, 26, 25, 33, 22, 28, 41, 39, 60, 64, 67, 64, 65, 66, 82, 55, 0, 19, 0, 0, 0, 0, 6, 20, 0, 7, 11, 18, 9, 5, 10, 17, 20, 18, 18, 33, 43, 70, 83, 99, 97, 130, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 10, 5, 0, 0, 0, 0, 0, 0, 0, 14, 12, 30, 25, 34, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 17, 40, 74, 56, 0, 0, 0, 7, 13, 18, 43, 147, 202, 137, 44, 15, 8, 0, 5, 5, 6, 6, 6, 7, 7, 7, 11, 22, 20, 24, 0, 0, 0, 0, 0, 0, 0, 20, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5};
|
||||
|
||||
AI_ALIGNED(32)
|
||||
float inputBuf[1024] = {0.0f};
|
||||
float inputBuf[AI_MODEL_IN_1_SIZE] = {0.0f};
|
||||
|
||||
void PictureCharArrayToFloat(const uint8_t *srcBuf, float *dstBuf, int len)
|
||||
{
|
||||
@ -38,7 +38,7 @@ void PictureCharArrayToFloat(const uint8_t *srcBuf, float *dstBuf, int len)
|
||||
#define CLIP_MIN 0.0f
|
||||
#define CLIP_MAX 300.0f
|
||||
#define EPSILON 1e-6f
|
||||
#define INPUT_SIZE 1024
|
||||
#define INPUT_SIZE AI_MODEL_IN_1_SIZE
|
||||
|
||||
// Preprocess a single sample (input: array of 1024 floats, output: array of 1024 floats)
|
||||
float clipped[INPUT_SIZE] = {0};
|
||||
@ -148,9 +148,9 @@ int AiModel(uint8_t *input)
|
||||
float max_confidence = 0.0f;
|
||||
|
||||
rt_kprintf("\nStart Test Code\n");
|
||||
PictureCharArrayToFloat(input, inputBuf, 1024);
|
||||
PictureCharArrayToFloat(input, inputBuf, AI_MODEL_IN_1_SIZE);
|
||||
|
||||
preprocess_data((const float *)inputBuf, aiInData, 1024);
|
||||
preprocess_data((const float *)inputBuf, aiInData, AI_MODEL_IN_1_SIZE);
|
||||
|
||||
Start_Tick = rt_tick_get();
|
||||
aiRun(aiInData, aiOutData);
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -135,7 +135,7 @@
|
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<SetRegEntry>
|
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<Number>0</Number>
|
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<Key>DLGUARM</Key>
|
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<Name>d</Name>
|
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<Name></Name>
|
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</SetRegEntry>
|
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<SetRegEntry>
|
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<Number>0</Number>
|
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@ -153,7 +153,40 @@
|
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<Name>-U-O142 -O2254 -S0 -C0 -N00("ARM CoreSight SW-DP") -D00(2BA01477) -L00(0) -TO18 -TC10000000 -TP21 -TDS8007 -TDT0 -TDC1F -TIEFFFFFFFF -TIP8 -FO7 -FD20000000 -FC800 -FN1 -FF0STM32F4xx_1024.FLM -FS08000000 -FL0100000 -FP0($$Device:STM32F405RGTx$CMSIS\Flash\STM32F4xx_1024.FLM)</Name>
|
||||
</SetRegEntry>
|
||||
</TargetDriverDllRegistry>
|
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<Breakpoint/>
|
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<Breakpoint>
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<Bp>
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<BreakByAccess>0</BreakByAccess>
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<BreakIfRCount>1</BreakIfRCount>
|
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<Filename>..\Core\Src\myEdge_ai_app.c</Filename>
|
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<ExecCommand></ExecCommand>
|
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<Expression>\\XM_01\../Core/Src/myEdge_ai_app.c\196</Expression>
|
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</Bp>
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<BreakByAccess>0</BreakByAccess>
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<BreakIfRCount>1</BreakIfRCount>
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<Filename>../Core/Src/main.c</Filename>
|
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<ExecCommand></ExecCommand>
|
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<Expression>\\XM_01\../Core/Src/main.c\114</Expression>
|
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</Bp>
|
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</Breakpoint>
|
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<WatchWindow1>
|
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<Ww>
|
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<count>0</count>
|
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@ -258,6 +291,18 @@
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
|
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<bDave2>0</bDave2>
|
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<PathWithFileName>..\Core\Src\myMattress_ctrl.c</PathWithFileName>
|
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<FilenameWithoutPath>myMattress_ctrl.c</FilenameWithoutPath>
|
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<RteFlg>0</RteFlg>
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<bShared>0</bShared>
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</File>
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<File>
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<GroupNumber>2</GroupNumber>
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<FileNumber>4</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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<bDave2>0</bDave2>
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<PathWithFileName>../Core/Src/main.c</PathWithFileName>
|
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<FilenameWithoutPath>main.c</FilenameWithoutPath>
|
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<RteFlg>0</RteFlg>
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@ -265,7 +310,7 @@
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</File>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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@ -277,7 +322,7 @@
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</File>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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@ -289,7 +334,7 @@
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</File>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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@ -301,7 +346,7 @@
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</File>
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<File>
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<GroupNumber>2</GroupNumber>
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<FileNumber>8</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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@ -311,18 +356,6 @@
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<RteFlg>0</RteFlg>
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<bShared>0</bShared>
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<GroupNumber>2</GroupNumber>
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<FileNumber>8</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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<bDave2>0</bDave2>
|
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<PathWithFileName>..\Core\Src\myMattress_ctrl.c</PathWithFileName>
|
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<FilenameWithoutPath>myMattress_ctrl.c</FilenameWithoutPath>
|
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<RteFlg>0</RteFlg>
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<bShared>0</bShared>
|
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</File>
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</Group>
|
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|
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<Group>
|
||||
@ -721,6 +754,14 @@
|
||||
</File>
|
||||
</Group>
|
||||
|
||||
<Group>
|
||||
<GroupName>::CMSIS</GroupName>
|
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<tvExp>0</tvExp>
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<tvExpOptDlg>0</tvExpOptDlg>
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<cbSel>0</cbSel>
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<RteFlg>1</RteFlg>
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</Group>
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<Group>
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<GroupName>Middlewares/RT-Thread/RTOS/shell</GroupName>
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<tvExp>0</tvExp>
|
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@ -728,7 +769,7 @@
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<cbSel>0</cbSel>
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<RteFlg>0</RteFlg>
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<File>
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<GroupNumber>9</GroupNumber>
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<FileNumber>38</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -740,7 +781,7 @@
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<bShared>0</bShared>
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</File>
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<File>
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<GroupNumber>9</GroupNumber>
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<FileNumber>39</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -752,7 +793,7 @@
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<bShared>0</bShared>
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<File>
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<GroupNumber>9</GroupNumber>
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<FileNumber>40</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -764,7 +805,7 @@
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<bShared>0</bShared>
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</File>
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<File>
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<GroupNumber>9</GroupNumber>
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<FileNumber>41</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -776,7 +817,7 @@
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<bShared>0</bShared>
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</File>
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<File>
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<GroupNumber>9</GroupNumber>
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<FileNumber>42</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -796,7 +837,7 @@
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<cbSel>0</cbSel>
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<RteFlg>0</RteFlg>
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<File>
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<GroupNumber>10</GroupNumber>
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<GroupNumber>11</GroupNumber>
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<FileNumber>43</FileNumber>
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<FileType>2</FileType>
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<tvExp>0</tvExp>
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@ -808,7 +849,7 @@
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>10</GroupNumber>
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<GroupNumber>11</GroupNumber>
|
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<FileNumber>44</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
|
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@ -828,7 +869,7 @@
|
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<cbSel>0</cbSel>
|
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<RteFlg>0</RteFlg>
|
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<File>
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>45</FileNumber>
|
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<FileType>1</FileType>
|
||||
<tvExp>0</tvExp>
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@ -840,7 +881,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>46</FileNumber>
|
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<FileType>1</FileType>
|
||||
<tvExp>0</tvExp>
|
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@ -852,7 +893,7 @@
|
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<bShared>0</bShared>
|
||||
</File>
|
||||
<File>
|
||||
<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>47</FileNumber>
|
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<FileType>1</FileType>
|
||||
<tvExp>0</tvExp>
|
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@ -864,7 +905,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>48</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -876,7 +917,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>49</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -888,7 +929,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>50</FileNumber>
|
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<FileType>1</FileType>
|
||||
<tvExp>0</tvExp>
|
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@ -900,7 +941,7 @@
|
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<bShared>0</bShared>
|
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</File>
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>51</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -912,7 +953,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>52</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -924,7 +965,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>53</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -936,7 +977,7 @@
|
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<bShared>0</bShared>
|
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</File>
|
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<File>
|
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>54</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -948,7 +989,7 @@
|
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
|
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>55</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -960,7 +1001,7 @@
|
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<bShared>0</bShared>
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
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<GroupNumber>12</GroupNumber>
|
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<FileNumber>56</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -972,7 +1013,7 @@
|
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
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<GroupNumber>12</GroupNumber>
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<FileNumber>57</FileNumber>
|
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -984,7 +1025,7 @@
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
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<GroupNumber>12</GroupNumber>
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<FileNumber>58</FileNumber>
|
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<FileType>1</FileType>
|
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<tvExp>0</tvExp>
|
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@ -996,7 +1037,7 @@
|
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
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<GroupNumber>12</GroupNumber>
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<FileNumber>59</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
|
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@ -1008,7 +1049,7 @@
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<bShared>0</bShared>
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<GroupNumber>11</GroupNumber>
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<FileNumber>60</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -1020,7 +1061,7 @@
|
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<bShared>0</bShared>
|
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</File>
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<File>
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<GroupNumber>11</GroupNumber>
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<GroupNumber>12</GroupNumber>
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<FileNumber>61</FileNumber>
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<FileType>1</FileType>
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<tvExp>0</tvExp>
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@ -1033,12 +1074,4 @@
|
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</File>
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</Group>
|
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|
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<Group>
|
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<GroupName>::CMSIS</GroupName>
|
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<tvExp>0</tvExp>
|
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<tvExpOptDlg>0</tvExpOptDlg>
|
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<cbSel>0</cbSel>
|
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<RteFlg>1</RteFlg>
|
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</Group>
|
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|
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</ProjectOpt>
|
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|
||||
@ -360,7 +360,7 @@
|
||||
</VariousControls>
|
||||
</Aads>
|
||||
<LDads>
|
||||
<umfTarg>1</umfTarg>
|
||||
<umfTarg>0</umfTarg>
|
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<Ropi>0</Ropi>
|
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<Rwpi>0</Rwpi>
|
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<noStLib>0</noStLib>
|
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@ -397,6 +397,11 @@
|
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<FileType>1</FileType>
|
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<FilePath>..\Core\Src\myEdge_ai_app.c</FilePath>
|
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</File>
|
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<File>
|
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<FileName>myMattress_ctrl.c</FileName>
|
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<FileType>1</FileType>
|
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<FilePath>..\Core\Src\myMattress_ctrl.c</FilePath>
|
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</File>
|
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<File>
|
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<FileName>main.c</FileName>
|
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<FileType>1</FileType>
|
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@ -473,11 +478,6 @@
|
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<FileType>1</FileType>
|
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<FilePath>../Core/Src/stm32f4xx_hal_msp.c</FilePath>
|
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</File>
|
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<File>
|
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<FileName>myMattress_ctrl.c</FileName>
|
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<FileType>1</FileType>
|
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<FilePath>..\Core\Src\myMattress_ctrl.c</FilePath>
|
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</File>
|
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</Files>
|
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</Group>
|
||||
<Group>
|
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@ -1461,6 +1461,9 @@
|
||||
</File>
|
||||
</Files>
|
||||
</Group>
|
||||
<Group>
|
||||
<GroupName>::CMSIS</GroupName>
|
||||
</Group>
|
||||
<Group>
|
||||
<GroupName>Middlewares/RT-Thread/RTOS/shell</GroupName>
|
||||
<GroupOption>
|
||||
@ -3014,9 +3017,6 @@
|
||||
</File>
|
||||
</Files>
|
||||
</Group>
|
||||
<Group>
|
||||
<GroupName>::CMSIS</GroupName>
|
||||
</Group>
|
||||
</Groups>
|
||||
</Target>
|
||||
</Targets>
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -2,7 +2,7 @@
|
||||
******************************************************************************
|
||||
* @file model.h
|
||||
* @author AST Embedded Analytics Research Platform
|
||||
* @date 2025-05-20T15:23:57+0800
|
||||
* @date 2025-05-26T11:06:58+0800
|
||||
* @brief AI Tool Automatic Code Generator for Embedded NN computing
|
||||
******************************************************************************
|
||||
* @attention
|
||||
@ -23,7 +23,7 @@
|
||||
|
||||
/******************************************************************************/
|
||||
#define AI_MODEL_MODEL_NAME "model"
|
||||
#define AI_MODEL_ORIGIN_MODEL_NAME "model"
|
||||
#define AI_MODEL_ORIGIN_MODEL_NAME "model2"
|
||||
|
||||
/******************************************************************************/
|
||||
#define AI_MODEL_ACTIVATIONS_ALIGNMENT (4)
|
||||
@ -44,9 +44,9 @@ AI_DEPRECATED
|
||||
AI_MODEL_IN_1_SIZE_BYTES, \
|
||||
}
|
||||
#define AI_MODEL_IN_1_FORMAT (AI_BUFFER_FORMAT_FLOAT)
|
||||
#define AI_MODEL_IN_1_CHANNEL (1024)
|
||||
#define AI_MODEL_IN_1_SIZE (1024)
|
||||
#define AI_MODEL_IN_1_SIZE_BYTES (4096)
|
||||
#define AI_MODEL_IN_1_CHANNEL (260)
|
||||
#define AI_MODEL_IN_1_SIZE (260)
|
||||
#define AI_MODEL_IN_1_SIZE_BYTES (1040)
|
||||
|
||||
/******************************************************************************/
|
||||
#define AI_MODEL_OUT_NUM (1)
|
||||
@ -62,12 +62,12 @@ AI_DEPRECATED
|
||||
AI_MODEL_OUT_1_SIZE_BYTES, \
|
||||
}
|
||||
#define AI_MODEL_OUT_1_FORMAT (AI_BUFFER_FORMAT_FLOAT)
|
||||
#define AI_MODEL_OUT_1_CHANNEL (3)
|
||||
#define AI_MODEL_OUT_1_SIZE (3)
|
||||
#define AI_MODEL_OUT_1_SIZE_BYTES (12)
|
||||
#define AI_MODEL_OUT_1_CHANNEL (2)
|
||||
#define AI_MODEL_OUT_1_SIZE (2)
|
||||
#define AI_MODEL_OUT_1_SIZE_BYTES (8)
|
||||
|
||||
/******************************************************************************/
|
||||
#define AI_MODEL_N_NODES (35)
|
||||
#define AI_MODEL_N_NODES (21)
|
||||
|
||||
|
||||
AI_API_DECLARE_BEGIN
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
******************************************************************************
|
||||
* @file model_config.h
|
||||
* @author AST Embedded Analytics Research Platform
|
||||
* @date 2025-05-20T15:23:57+0800
|
||||
* @date 2025-05-26T11:06:58+0800
|
||||
* @brief AI Tool Automatic Code Generator for Custom Layers Implementation
|
||||
******************************************************************************
|
||||
* @attention
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
******************************************************************************
|
||||
* @file model_data.c
|
||||
* @author AST Embedded Analytics Research Platform
|
||||
* @date 2025-05-20T15:23:57+0800
|
||||
* @date 2025-05-26T11:06:58+0800
|
||||
* @brief AI Tool Automatic Code Generator for Embedded NN computing
|
||||
******************************************************************************
|
||||
* @attention
|
||||
@ -21,13 +21,13 @@
|
||||
AI_API_DECLARE_BEGIN
|
||||
ai_buffer g_model_data_map_activations[AI_MODEL_DATA_ACTIVATIONS_COUNT] = {
|
||||
AI_BUFFER_INIT(AI_FLAG_NONE, AI_BUFFER_FORMAT_U8,
|
||||
AI_BUFFER_SHAPE_INIT(AI_SHAPE_BCWH, 4, 1, 37120, 1, 1),
|
||||
37120, NULL, NULL), /* heap_overlay_pool */
|
||||
AI_BUFFER_SHAPE_INIT(AI_SHAPE_BCWH, 4, 1, 11904, 1, 1),
|
||||
11904, NULL, NULL), /* heap_overlay_pool */
|
||||
};
|
||||
ai_buffer g_model_data_map_weights[AI_MODEL_DATA_WEIGHTS_COUNT] = {
|
||||
AI_BUFFER_INIT(AI_FLAG_NONE, AI_BUFFER_FORMAT_U8,
|
||||
AI_BUFFER_SHAPE_INIT(AI_SHAPE_BCWH, 4, 1, 29372, 1, 1),
|
||||
29372, NULL, s_model_weights_array_u64), /* weights_array */
|
||||
AI_BUFFER_SHAPE_INIT(AI_SHAPE_BCWH, 4, 1, 14936, 1, 1),
|
||||
14936, NULL, s_model_weights_array_u64), /* weights_array */
|
||||
};
|
||||
|
||||
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
******************************************************************************
|
||||
* @file model_data.h
|
||||
* @author AST Embedded Analytics Research Platform
|
||||
* @date 2025-05-20T15:23:57+0800
|
||||
* @date 2025-05-26T11:06:58+0800
|
||||
* @brief AI Tool Automatic Code Generator for Embedded NN computing
|
||||
******************************************************************************
|
||||
* Copyright (c) 2025 STMicroelectronics.
|
||||
@ -32,7 +32,7 @@ AI_DEPRECATED
|
||||
AI_API_DECLARE_BEGIN
|
||||
|
||||
|
||||
extern const ai_u64 s_model_weights_array_u64[3672];
|
||||
extern const ai_u64 s_model_weights_array_u64[1867];
|
||||
|
||||
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -2,7 +2,7 @@
|
||||
******************************************************************************
|
||||
* @file model_data_params.h
|
||||
* @author AST Embedded Analytics Research Platform
|
||||
* @date 2025-05-20T15:23:57+0800
|
||||
* @date 2025-05-26T11:06:58+0800
|
||||
* @brief AI Tool Automatic Code Generator for Embedded NN computing
|
||||
******************************************************************************
|
||||
* Copyright (c) 2025 STMicroelectronics.
|
||||
@ -28,18 +28,18 @@
|
||||
|
||||
|
||||
#define AI_MODEL_DATA_ACTIVATIONS_SIZES \
|
||||
{ 37120, }
|
||||
#define AI_MODEL_DATA_ACTIVATIONS_SIZE (37120)
|
||||
{ 11904, }
|
||||
#define AI_MODEL_DATA_ACTIVATIONS_SIZE (11904)
|
||||
#define AI_MODEL_DATA_ACTIVATIONS_COUNT (1)
|
||||
#define AI_MODEL_DATA_ACTIVATION_1_SIZE (37120)
|
||||
#define AI_MODEL_DATA_ACTIVATION_1_SIZE (11904)
|
||||
|
||||
|
||||
|
||||
#define AI_MODEL_DATA_WEIGHTS_SIZES \
|
||||
{ 29372, }
|
||||
#define AI_MODEL_DATA_WEIGHTS_SIZE (29372)
|
||||
{ 14936, }
|
||||
#define AI_MODEL_DATA_WEIGHTS_SIZE (14936)
|
||||
#define AI_MODEL_DATA_WEIGHTS_COUNT (1)
|
||||
#define AI_MODEL_DATA_WEIGHT_1_SIZE (29372)
|
||||
#define AI_MODEL_DATA_WEIGHT_1_SIZE (14936)
|
||||
|
||||
|
||||
|
||||
|
||||
@ -1,384 +1,264 @@
|
||||
ST Edge AI Core v2.0.0-20049
|
||||
Created date : 2025-05-20 15:23:59
|
||||
Parameters : generate --target stm32f4 --name model -m D:/Job_Work/Code/Z_Python/myEnv/model.tflite --compression high --verbosity 1 -O ram --workspace C:/Users/admin/AppData/Local/Temp/mxAI_workspace33740368255090013021409726810218586 --output C:/Users/admin/.stm32cubemx/model_output
|
||||
Created date : 2025-05-26 11:06:59
|
||||
Parameters : generate --target stm32f4 --name model -m D:/Job_Work/Code/Z_Python/myEnv/model2.tflite --compression high --verbosity 1 -O ram --workspace C:/Users/admin/AppData/Local/Temp/mxAI_workspace84040893089870013881319616322495011 --output C:/Users/admin/.stm32cubemx/model_output
|
||||
|
||||
Exec/report summary (generate)
|
||||
-------------------------------------------------------------------------------------------------------------
|
||||
model file : D:\Job_Work\Code\Z_Python\myEnv\model.tflite
|
||||
model file : D:\Job_Work\Code\Z_Python\myEnv\model2.tflite
|
||||
type : tflite
|
||||
c_name : model
|
||||
compression : high
|
||||
options : allocate-inputs, allocate-outputs
|
||||
optimization : ram
|
||||
target/series : stm32f4
|
||||
workspace dir : C:\Users\admin\AppData\Local\Temp\mxAI_workspace33740368255090013021409726810218586
|
||||
workspace dir : C:\Users\admin\AppData\Local\Temp\mxAI_workspace84040893089870013881319616322495011
|
||||
output dir : C:\Users\admin\.stm32cubemx\model_output
|
||||
model_fmt : float
|
||||
model_name : model
|
||||
model_hash : 0x391deb77460dcfce8d55e2fc3b80314e
|
||||
params # : 8,419 items (32.89 KiB)
|
||||
model_name : model2
|
||||
model_hash : 0x02dd23f831c7bbf9c5b10eba7342e3d2
|
||||
params # : 4,210 items (16.45 KiB)
|
||||
-------------------------------------------------------------------------------------------------------------
|
||||
input 1/1 : 'serving_default_input0', f32(1x1024), 4.00 KBytes, activations
|
||||
output 1/1 : 'nl_30', f32(1x3), 12 Bytes, activations
|
||||
macc : 957,040
|
||||
weights (ro) : 29,372 B (28.68 KiB) (1 segment) / -4,304(-12.8%) vs float model
|
||||
activations (rw) : 37,120 B (36.25 KiB) (1 segment) *
|
||||
ram (total) : 37,120 B (36.25 KiB) = 37,120 + 0 + 0
|
||||
input 1/1 : 'serving_default_input0', f32(1x260), 1.02 KBytes, activations
|
||||
output 1/1 : 'nl_20', f32(1x2), 8 Bytes, activations
|
||||
macc : 156,480
|
||||
weights (ro) : 14,936 B (14.59 KiB) (1 segment) / -1,904(-11.3%) vs float model
|
||||
activations (rw) : 11,904 B (11.62 KiB) (1 segment) *
|
||||
ram (total) : 11,904 B (11.62 KiB) = 11,904 + 0 + 0
|
||||
-------------------------------------------------------------------------------------------------------------
|
||||
(*) 'input'/'output' buffers can be used from the activations buffer
|
||||
|
||||
Model name - model
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
Model name - model2
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
m_id layer (type,original) oshape param/size macc connected to | c_size c_macc c_type
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
0 serving_default_input0 (Input, ) [b:1,c:1024] |
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
3 reshape_3 (Reshape, RESHAPE) [b:1,h:32,w:32,c:1] serving_default_input0 |
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
4 conv2d_4 (Conv2D, CONV_2D) [b:1,h:32,w:32,c:16] 160/640 147,472 reshape_3 | -640(-100.0%) -147,472(-100.0%)
|
||||
nl_4_nl (Nonlinearity, CONV_2D) [b:1,h:32,w:32,c:16] 16,384 conv2d_4 | -16,384(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
5 pool_5 (Pool, AVERAGE_POOL_2D) [b:1,h:16,w:16,c:16] 16,384 nl_4_nl | +640(+100.0%) +163,856(+1000.1%) Conv2D_[0]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
6 conv2d_6 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:16,w:16,c:16] 160/640 36,880 pool_5 | Conv2D_[1]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
7 conv2d_7 (Conv2D, CONV_2D) [b:1,h:16,w:16,c:16] 272/1,088 65,552 conv2d_6 | +4,096(+6.2%) Conv2D_/Nonlinearity_[2, 3]
|
||||
nl_7_nl (Nonlinearity, CONV_2D) [b:1,h:16,w:16,c:16] 4,096 conv2d_7 | -4,096(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
8 conv2d_8 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:16,w:16,c:16] 160/640 36,880 nl_7_nl | Conv2D_[4]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
9 conv2d_9 (Conv2D, CONV_2D) [b:1,h:16,w:16,c:16] 272/1,088 65,552 conv2d_8 | Conv2D_[5]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
10 eltwise_10 (Eltwise, ADD) [b:1,h:16,w:16,c:16] 4,096 pool_5 | +4,096(+100.0%) Eltwise/add_/Nonlinearity_[6, 7]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
0 serving_default_input0 (Input, ) [b:1,c:260] |
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
3 reshape_3 (Reshape, RESHAPE) [b:1,h:10,w:26,c:1] serving_default_input0 |
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
4 conv2d_4 (Conv2D, CONV_2D) [b:1,h:10,w:26,c:16] 160/640 37,456 reshape_3 | -640(-100.0%) -37,456(-100.0%)
|
||||
nl_4_nl (Nonlinearity, CONV_2D) [b:1,h:10,w:26,c:16] 4,160 conv2d_4 | -4,160(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
5 pool_5 (Pool, AVERAGE_POOL_2D) [b:1,h:5,w:13,c:16] 4,160 nl_4_nl | +640(+100.0%) +41,616(+1000.4%) Conv2D_[0]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
6 conv2d_6 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:5,w:13,c:16] 160/640 9,376 pool_5 | Conv2D_[1]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
7 conv2d_7 (Conv2D, CONV_2D) [b:1,h:5,w:13,c:16] 272/1,088 16,656 conv2d_6 | +1,040(+6.2%) Conv2D_/Nonlinearity_[2, 3]
|
||||
nl_7_nl (Nonlinearity, CONV_2D) [b:1,h:5,w:13,c:16] 1,040 conv2d_7 | -1,040(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
8 conv2d_8 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:5,w:13,c:16] 160/640 9,376 nl_7_nl | Conv2D_[4]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
9 conv2d_9 (Conv2D, CONV_2D) [b:1,h:5,w:13,c:16] 272/1,088 16,656 conv2d_8 | Conv2D_[5]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
10 eltwise_10 (Eltwise, ADD) [b:1,h:5,w:13,c:16] 1,040 pool_5 | +1,040(+100.0%) Eltwise/add_/Nonlinearity_[6, 7]
|
||||
conv2d_9 |
|
||||
nl_10_nl (Nonlinearity, ADD) [b:1,h:16,w:16,c:16] 4,096 eltwise_10 | -4,096(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
11 conv2d_11 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:16,w:16,c:16] 160/640 36,880 nl_10_nl | Conv2D_[8]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
12 conv2d_12 (Conv2D, CONV_2D) [b:1,h:16,w:16,c:16] 272/1,088 65,552 conv2d_11 | +4,096(+6.2%) Conv2D_/Nonlinearity_[9, 10]
|
||||
nl_12_nl (Nonlinearity, CONV_2D) [b:1,h:16,w:16,c:16] 4,096 conv2d_12 | -4,096(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
13 conv2d_13 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:16,w:16,c:16] 160/640 36,880 nl_12_nl | Conv2D_[11]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
14 conv2d_14 (Conv2D, CONV_2D) [b:1,h:16,w:16,c:16] 272/1,088 65,552 conv2d_13 | Conv2D_[12]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
15 eltwise_15 (Eltwise, ADD) [b:1,h:16,w:16,c:16] 4,096 nl_10_nl | +4,096(+100.0%) Eltwise/add_/Nonlinearity_[13, 14]
|
||||
nl_10_nl (Nonlinearity, ADD) [b:1,h:5,w:13,c:16] 1,040 eltwise_10 | -1,040(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
11 conv2d_11 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:3,w:7,c:16] 160/640 3,040 nl_10_nl | Conv2D_[9]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
12 conv2d_12 (Conv2D, CONV_2D) [b:1,h:3,w:7,c:32] 544/2,176 10,784 conv2d_11 | +672(+6.2%) Conv2D_/Nonlinearity_[10, 11]
|
||||
nl_12_nl (Nonlinearity, CONV_2D) [b:1,h:3,w:7,c:32] 672 conv2d_12 | -672(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
13 conv2d_13 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:3,w:7,c:32] 320/1,280 6,080 nl_12_nl | Conv2D_[12]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
14 conv2d_14 (Conv2D, CONV_2D) [b:1,h:3,w:7,c:32] 1,056/4,224 21,536 conv2d_13 | Conv2D_[13]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
15 conv2d_15 (Conv2D, CONV_2D) [b:1,h:3,w:7,c:32] 544/2,176 10,784 nl_10_nl | Conv2D_[8]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
16 eltwise_16 (Eltwise, ADD) [b:1,h:3,w:7,c:32] 672 conv2d_15 | +672(+100.0%) Eltwise/add_/Nonlinearity_[14, 15]
|
||||
conv2d_14 |
|
||||
nl_15_nl (Nonlinearity, ADD) [b:1,h:16,w:16,c:16] 4,096 eltwise_15 | -4,096(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
16 conv2d_16 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:8,w:8,c:16] 160/640 9,232 nl_15_nl | Conv2D_[16]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
17 conv2d_17 (Conv2D, CONV_2D) [b:1,h:8,w:8,c:32] 544/2,176 32,800 conv2d_16 | +2,048(+6.2%) Conv2D_/Nonlinearity_[17, 18]
|
||||
nl_17_nl (Nonlinearity, CONV_2D) [b:1,h:8,w:8,c:32] 2,048 conv2d_17 | -2,048(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
18 conv2d_18 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:8,w:8,c:32] 320/1,280 18,464 nl_17_nl | Conv2D_[19]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
19 conv2d_19 (Conv2D, CONV_2D) [b:1,h:8,w:8,c:32] 1,056/4,224 65,568 conv2d_18 | Conv2D_[20]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
20 conv2d_20 (Conv2D, CONV_2D) [b:1,h:8,w:8,c:32] 544/2,176 32,800 nl_15_nl | Conv2D_[15]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
21 eltwise_21 (Eltwise, ADD) [b:1,h:8,w:8,c:32] 2,048 conv2d_20 | +2,048(+100.0%) Eltwise/add_/Nonlinearity_[21, 22]
|
||||
conv2d_19 |
|
||||
nl_21_nl (Nonlinearity, ADD) [b:1,h:8,w:8,c:32] 2,048 eltwise_21 | -2,048(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
22 conv2d_22 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:8,w:8,c:32] 320/1,280 18,464 nl_21_nl | Conv2D_[23]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
23 conv2d_23 (Conv2D, CONV_2D) [b:1,h:8,w:8,c:32] 1,056/4,224 65,568 conv2d_22 | +2,048(+3.1%) Conv2D_/Nonlinearity_[24, 25]
|
||||
nl_23_nl (Nonlinearity, CONV_2D) [b:1,h:8,w:8,c:32] 2,048 conv2d_23 | -2,048(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
24 conv2d_24 (Conv2D, DEPTHWISE_CONV_2D) [b:1,h:8,w:8,c:32] 320/1,280 18,464 nl_23_nl | Conv2D_[26]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
25 conv2d_25 (Conv2D, CONV_2D) [b:1,h:8,w:8,c:32] 1,056/4,224 65,568 conv2d_24 | Conv2D_[27]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
26 eltwise_26 (Eltwise, ADD) [b:1,h:8,w:8,c:32] 2,048 nl_21_nl | +2,048(+100.0%) Eltwise/add_/Nonlinearity_[28, 29]
|
||||
conv2d_25 |
|
||||
nl_26_nl (Nonlinearity, ADD) [b:1,h:8,w:8,c:32] 2,048 eltwise_26 | -2,048(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
27 pool_27 (Pool, MEAN) [b:1,h:1,w:1,c:32] 2,048 nl_26_nl | Pool_[30]
|
||||
reshape_27_reshape (Reshape, MEAN) [b:1,c:32] pool_27 |
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
28 arith_constant31 (Placeholder, ) [b:32,c:32] 1,024/4,096 | -3,392(-82.8%) +1,088(+100.0%) Dense_/Nonlinearity_[31, 32]
|
||||
arith_constant33 (Placeholder, ) [b:32] 32/128 | -128(-100.0%)
|
||||
gemm_28 (Gemm, FULLY_CONNECTED) [b:1,c:32] 1,056 reshape_27_reshape | -1,056(-100.0%)
|
||||
arith_constant31 |
|
||||
arith_constant33 |
|
||||
nl_28_nl (Nonlinearity, FULLY_CONNECTED) [b:1,c:32] 32 gemm_28 | -32(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
29 arith_constant30 (Placeholder, ) [b:3,c:32] 96/384 | -260(-67.7%) +99(+100.0%) Dense_[33]
|
||||
arith_constant32 (Placeholder, ) [b:3] 3/12 | -12(-100.0%)
|
||||
gemm_29 (Gemm, FULLY_CONNECTED) [b:1,c:3] 99 nl_28_nl | -99(-100.0%)
|
||||
arith_constant30 |
|
||||
arith_constant32 |
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
30 nl_30 (Nonlinearity, SOFTMAX) [b:1,c:3] 45 gemm_29 | Nonlinearity_[o][34]
|
||||
------ ------------------------------------------ ---------------------- ------------- --------- ------------------------ --- ---------------- -------------------- ------------------------------------
|
||||
model/c-model: macc=957,040/957,040 weights=33,676/29,372 -4,304(-12.8%) activations=--/37,120 io=--/0
|
||||
nl_16_nl (Nonlinearity, ADD) [b:1,h:3,w:7,c:32] 672 eltwise_16 | -672(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
17 pool_17 (Pool, MEAN) [b:1,h:1,w:1,c:32] 672 nl_16_nl | Pool_[16]
|
||||
reshape_17_reshape (Reshape, MEAN) [b:1,c:32] pool_17 |
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
18 arith_constant19 (Placeholder, ) [b:16,c:32] 512/2,048 | -1,664(-81.2%) +544(+100.0%) Dense_/Nonlinearity_[17, 18]
|
||||
arith_constant21 (Placeholder, ) [b:16] 16/64 | -64(-100.0%)
|
||||
gemm_18 (Gemm, FULLY_CONNECTED) [b:1,c:16] 528 reshape_17_reshape | -528(-100.0%)
|
||||
arith_constant19 |
|
||||
arith_constant21 |
|
||||
nl_18_nl (Nonlinearity, FULLY_CONNECTED) [b:1,c:16] 16 gemm_18 | -16(-100.0%)
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
19 arith_constant18 (Placeholder, ) [b:2,c:16] 32/128 | -40(-31.2%) +34(+100.0%) Dense_[19]
|
||||
arith_constant20 (Placeholder, ) [b:2] 2/8 | -8(-100.0%)
|
||||
gemm_19 (Gemm, FULLY_CONNECTED) [b:1,c:2] 34 nl_18_nl | -34(-100.0%)
|
||||
arith_constant18 |
|
||||
arith_constant20 |
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
20 nl_20 (Nonlinearity, SOFTMAX) [b:1,c:2] 30 gemm_19 | Nonlinearity_[o][20]
|
||||
------ ------------------------------------------ ---------------------- ------------- -------- ------------------------ --- ---------------- ------------------- ------------------------------------
|
||||
model/c-model: macc=156,480/156,480 weights=16,840/14,936 -1,904(-11.3%) activations=--/11,904 io=--/0
|
||||
|
||||
|
||||
|
||||
Generated C-graph summary
|
||||
------------------------------------------------------------------------------------------------------------------------
|
||||
model name : model
|
||||
model name : model2
|
||||
c-name : model
|
||||
c-node # : 35
|
||||
c-array # : 81
|
||||
activations size : 37120 (1 segment)
|
||||
weights size : 29372 (1 segment)
|
||||
macc : 957040
|
||||
c-node # : 21
|
||||
c-array # : 51
|
||||
activations size : 11904 (1 segment)
|
||||
weights size : 14936 (1 segment)
|
||||
macc : 156480
|
||||
inputs : ['serving_default_input0_output']
|
||||
outputs : ['nl_30_output']
|
||||
outputs : ['nl_20_output']
|
||||
|
||||
C-Arrays (81)
|
||||
------ ------------------------------- ------------ ------------------------- ------------------ ---------
|
||||
C-Arrays (51)
|
||||
------ ------------------------------- ----------- ------------------------- ------------------ ---------
|
||||
c_id name (*_array) item/size domain/mem-pool c-type comment
|
||||
------ ------------------------------- ------------ ------------------------- ------------------ ---------
|
||||
0 conv2d_11_output 4096/16384 activations/**default** float
|
||||
------ ------------------------------- ----------- ------------------------- ------------------ ---------
|
||||
0 conv2d_11_output 336/1344 activations/**default** float
|
||||
1 conv2d_11_weights 144/576 weights/weights const float
|
||||
2 conv2d_12_bias 16/64 weights/weights const float
|
||||
3 conv2d_12_output 4096/16384 activations/**default** float
|
||||
2 conv2d_12_bias 32/128 weights/weights const float
|
||||
3 conv2d_12_output 672/2688 activations/**default** float
|
||||
4 conv2d_12_scratch0 16/64 activations/**default** float
|
||||
5 conv2d_12_weights 256/1024 weights/weights const float
|
||||
6 conv2d_13_output 4096/16384 activations/**default** float
|
||||
7 conv2d_13_weights 144/576 weights/weights const float
|
||||
8 conv2d_14_bias 16/64 weights/weights const float
|
||||
9 conv2d_14_output 4096/16384 activations/**default** float
|
||||
10 conv2d_14_scratch0 16/64 activations/**default** float
|
||||
11 conv2d_14_weights 256/1024 weights/weights const float
|
||||
12 conv2d_16_output 1024/4096 activations/**default** float
|
||||
13 conv2d_16_weights 144/576 weights/weights const float
|
||||
14 conv2d_17_bias 32/128 weights/weights const float
|
||||
15 conv2d_17_output 2048/8192 activations/**default** float
|
||||
16 conv2d_17_scratch0 16/64 activations/**default** float
|
||||
17 conv2d_17_weights 512/2048 weights/weights const float
|
||||
18 conv2d_18_bias 32/128 weights/weights const float
|
||||
19 conv2d_18_output 2048/8192 activations/**default** float
|
||||
20 conv2d_18_weights 288/1152 weights/weights const float
|
||||
21 conv2d_19_bias 32/128 weights/weights const float
|
||||
22 conv2d_19_output 2048/8192 activations/**default** float
|
||||
23 conv2d_19_scratch0 32/128 activations/**default** float
|
||||
24 conv2d_19_weights 1024/4096 weights/weights const float
|
||||
25 conv2d_20_bias 32/128 weights/weights const float
|
||||
26 conv2d_20_output 2048/8192 activations/**default** float
|
||||
27 conv2d_20_scratch0 16/64 activations/**default** float
|
||||
28 conv2d_20_weights 512/2048 weights/weights const float
|
||||
29 conv2d_22_output 2048/8192 activations/**default** float
|
||||
30 conv2d_22_weights 288/1152 weights/weights const float
|
||||
31 conv2d_23_bias 32/128 weights/weights const float
|
||||
32 conv2d_23_output 2048/8192 activations/**default** float
|
||||
33 conv2d_23_scratch0 32/128 activations/**default** float
|
||||
34 conv2d_23_weights 1024/4096 weights/weights const float
|
||||
35 conv2d_24_output 2048/8192 activations/**default** float
|
||||
36 conv2d_24_weights 288/1152 weights/weights const float
|
||||
37 conv2d_25_bias 32/128 weights/weights const float
|
||||
38 conv2d_25_output 2048/8192 activations/**default** float
|
||||
39 conv2d_25_scratch0 32/128 activations/**default** float
|
||||
40 conv2d_25_weights 1024/4096 weights/weights const float
|
||||
41 conv2d_4_bias 16/64 weights/weights const float
|
||||
42 conv2d_4_output 4096/16384 activations/**default** float
|
||||
43 conv2d_4_scratch0 9/36 activations/**default** float
|
||||
44 conv2d_4_scratch1 1024/4096 activations/**default** float
|
||||
45 conv2d_4_weights 144/576 weights/weights const float
|
||||
46 conv2d_6_bias 16/64 weights/weights const float
|
||||
47 conv2d_6_output 4096/16384 activations/**default** float
|
||||
48 conv2d_6_weights 144/576 weights/weights const float
|
||||
49 conv2d_7_bias 16/64 weights/weights const float
|
||||
50 conv2d_7_output 4096/16384 activations/**default** float
|
||||
51 conv2d_7_scratch0 16/64 activations/**default** float
|
||||
52 conv2d_7_weights 256/1024 weights/weights const float
|
||||
53 conv2d_8_output 4096/16384 activations/**default** float
|
||||
54 conv2d_8_weights 144/576 weights/weights const float
|
||||
55 conv2d_9_bias 16/64 weights/weights const float
|
||||
56 conv2d_9_output 4096/16384 activations/**default** float
|
||||
57 conv2d_9_scratch0 16/64 activations/**default** float
|
||||
58 conv2d_9_weights 256/1024 weights/weights const float
|
||||
59 eltwise_10_output 4096/16384 activations/**default** float
|
||||
60 eltwise_15_output 4096/16384 activations/**default** float
|
||||
61 eltwise_21_output 2048/8192 activations/**default** float
|
||||
62 eltwise_26_output 2048/8192 activations/**default** float
|
||||
63 gemm_28_bias 32/128 weights/weights const float
|
||||
64 gemm_28_output 32/128 activations/**default** float
|
||||
65 gemm_28_weights 1024/576 weights/weights const lut4_float
|
||||
66 gemm_29_bias 3/12 weights/weights const float
|
||||
67 gemm_29_output 3/12 activations/**default** float
|
||||
68 gemm_29_weights 96/112 weights/weights const lut4_float
|
||||
69 nl_10_nl_output 4096/16384 activations/**default** float
|
||||
70 nl_12_nl_output 4096/16384 activations/**default** float
|
||||
71 nl_15_nl_output 4096/16384 activations/**default** float
|
||||
72 nl_17_nl_output 2048/8192 activations/**default** float
|
||||
73 nl_21_nl_output 2048/8192 activations/**default** float
|
||||
74 nl_23_nl_output 2048/8192 activations/**default** float
|
||||
75 nl_26_nl_output 2048/8192 activations/**default** float
|
||||
76 nl_28_nl_output 32/128 activations/**default** float
|
||||
77 nl_30_output 3/12 activations/**default** float /output
|
||||
78 nl_7_nl_output 4096/16384 activations/**default** float
|
||||
79 pool_27_output 32/128 activations/**default** float
|
||||
80 serving_default_input0_output 1024/4096 activations/**default** float /input
|
||||
------ ------------------------------- ------------ ------------------------- ------------------ ---------
|
||||
5 conv2d_12_weights 512/2048 weights/weights const float
|
||||
6 conv2d_13_bias 32/128 weights/weights const float
|
||||
7 conv2d_13_output 672/2688 activations/**default** float
|
||||
8 conv2d_13_weights 288/1152 weights/weights const float
|
||||
9 conv2d_14_bias 32/128 weights/weights const float
|
||||
10 conv2d_14_output 672/2688 activations/**default** float
|
||||
11 conv2d_14_scratch0 32/128 activations/**default** float
|
||||
12 conv2d_14_weights 1024/4096 weights/weights const float
|
||||
13 conv2d_15_bias 32/128 weights/weights const float
|
||||
14 conv2d_15_output 672/2688 activations/**default** float
|
||||
15 conv2d_15_scratch0 16/64 activations/**default** float
|
||||
16 conv2d_15_weights 512/2048 weights/weights const float
|
||||
17 conv2d_4_bias 16/64 weights/weights const float
|
||||
18 conv2d_4_output 1040/4160 activations/**default** float
|
||||
19 conv2d_4_scratch0 9/36 activations/**default** float
|
||||
20 conv2d_4_scratch1 832/3328 activations/**default** float
|
||||
21 conv2d_4_weights 144/576 weights/weights const float
|
||||
22 conv2d_6_bias 16/64 weights/weights const float
|
||||
23 conv2d_6_output 1040/4160 activations/**default** float
|
||||
24 conv2d_6_weights 144/576 weights/weights const float
|
||||
25 conv2d_7_bias 16/64 weights/weights const float
|
||||
26 conv2d_7_output 1040/4160 activations/**default** float
|
||||
27 conv2d_7_scratch0 16/64 activations/**default** float
|
||||
28 conv2d_7_weights 256/1024 weights/weights const float
|
||||
29 conv2d_8_output 1040/4160 activations/**default** float
|
||||
30 conv2d_8_weights 144/576 weights/weights const float
|
||||
31 conv2d_9_bias 16/64 weights/weights const float
|
||||
32 conv2d_9_output 1040/4160 activations/**default** float
|
||||
33 conv2d_9_scratch0 16/64 activations/**default** float
|
||||
34 conv2d_9_weights 256/1024 weights/weights const float
|
||||
35 eltwise_10_output 1040/4160 activations/**default** float
|
||||
36 eltwise_16_output 672/2688 activations/**default** float
|
||||
37 gemm_18_bias 16/64 weights/weights const float
|
||||
38 gemm_18_output 16/64 activations/**default** float
|
||||
39 gemm_18_weights 512/320 weights/weights const lut4_float
|
||||
40 gemm_19_bias 2/8 weights/weights const float
|
||||
41 gemm_19_output 2/8 activations/**default** float
|
||||
42 gemm_19_weights 32/80 weights/weights const lut4_float
|
||||
43 nl_10_nl_output 1040/4160 activations/**default** float
|
||||
44 nl_12_nl_output 672/2688 activations/**default** float
|
||||
45 nl_16_nl_output 672/2688 activations/**default** float
|
||||
46 nl_18_nl_output 16/64 activations/**default** float
|
||||
47 nl_20_output 2/8 activations/**default** float /output
|
||||
48 nl_7_nl_output 1040/4160 activations/**default** float
|
||||
49 pool_17_output 32/128 activations/**default** float
|
||||
50 serving_default_input0_output 260/1040 activations/**default** float /input
|
||||
------ ------------------------------- ----------- ------------------------- ------------------ ---------
|
||||
|
||||
C-Layers (35)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
C-Layers (21)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
c_id name (*_layer) id layer_type macc rom tensors shape (array id)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
0 conv2d_4 5 Conv2D 180240 640 I: serving_default_input0_output f32(1x1024) (80)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
0 conv2d_4 5 Conv2D 45776 640 I: serving_default_input0_output f32(1x260) (50)
|
||||
S: conv2d_4_scratch0
|
||||
S: conv2d_4_scratch1
|
||||
W: conv2d_4_weights f32(16x3x3x1) (45)
|
||||
W: conv2d_4_bias f32(16) (41)
|
||||
O: conv2d_4_output f32(1x16x16x16) (42)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
1 conv2d_6 6 Conv2D 36880 640 I: conv2d_4_output f32(1x16x16x16) (42)
|
||||
W: conv2d_6_weights f32(16x3x3x1) (48)
|
||||
W: conv2d_6_bias f32(16) (46)
|
||||
O: conv2d_6_output f32(1x16x16x16) (47)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
2 conv2d_7 7 Conv2D 65552 1088 I: conv2d_6_output f32(1x16x16x16) (47)
|
||||
W: conv2d_4_weights f32(16x3x3x1) (21)
|
||||
W: conv2d_4_bias f32(16) (17)
|
||||
O: conv2d_4_output f32(1x5x13x16) (18)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
1 conv2d_6 6 Conv2D 9376 640 I: conv2d_4_output f32(1x5x13x16) (18)
|
||||
W: conv2d_6_weights f32(16x3x3x1) (24)
|
||||
W: conv2d_6_bias f32(16) (22)
|
||||
O: conv2d_6_output f32(1x5x13x16) (23)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
2 conv2d_7 7 Conv2D 16656 1088 I: conv2d_6_output f32(1x5x13x16) (23)
|
||||
S: conv2d_7_scratch0
|
||||
W: conv2d_7_weights f32(16x1x1x16) (52)
|
||||
W: conv2d_7_bias f32(16) (49)
|
||||
O: conv2d_7_output f32(1x16x16x16) (50)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
3 nl_7_nl 7 Nonlinearity 4096 0 I: conv2d_7_output f32(1x16x16x16) (50)
|
||||
O: nl_7_nl_output f32(1x16x16x16) (78)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
4 conv2d_8 8 Conv2D 36880 640 I: nl_7_nl_output f32(1x16x16x16) (78)
|
||||
W: conv2d_8_weights f32(16x3x3x1) (54)
|
||||
W: conv2d_6_bias f32(16) (46)
|
||||
O: conv2d_8_output f32(1x16x16x16) (53)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
5 conv2d_9 9 Conv2D 65552 1088 I: conv2d_8_output f32(1x16x16x16) (53)
|
||||
W: conv2d_7_weights f32(16x1x1x16) (28)
|
||||
W: conv2d_7_bias f32(16) (25)
|
||||
O: conv2d_7_output f32(1x5x13x16) (26)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
3 nl_7_nl 7 Nonlinearity 1040 0 I: conv2d_7_output f32(1x5x13x16) (26)
|
||||
O: nl_7_nl_output f32(1x5x13x16) (48)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
4 conv2d_8 8 Conv2D 9376 640 I: nl_7_nl_output f32(1x5x13x16) (48)
|
||||
W: conv2d_8_weights f32(16x3x3x1) (30)
|
||||
W: conv2d_6_bias f32(16) (22)
|
||||
O: conv2d_8_output f32(1x5x13x16) (29)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
5 conv2d_9 9 Conv2D 16656 1088 I: conv2d_8_output f32(1x5x13x16) (29)
|
||||
S: conv2d_9_scratch0
|
||||
W: conv2d_9_weights f32(16x1x1x16) (58)
|
||||
W: conv2d_9_bias f32(16) (55)
|
||||
O: conv2d_9_output f32(1x16x16x16) (56)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
6 eltwise_10 10 Eltwise/add 4096 0 I: conv2d_4_output f32(1x16x16x16) (42)
|
||||
I: conv2d_9_output f32(1x16x16x16) (42)
|
||||
O: eltwise_10_output f32(1x16x16x16) (59)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
7 nl_10_nl 10 Nonlinearity 4096 0 I: eltwise_10_output f32(1x16x16x16) (59)
|
||||
O: nl_10_nl_output f32(1x16x16x16) (69)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
8 conv2d_11 11 Conv2D 36880 640 I: nl_10_nl_output f32(1x16x16x16) (69)
|
||||
W: conv2d_9_weights f32(16x1x1x16) (34)
|
||||
W: conv2d_9_bias f32(16) (31)
|
||||
O: conv2d_9_output f32(1x5x13x16) (32)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
6 eltwise_10 10 Eltwise/add 1040 0 I: conv2d_4_output f32(1x5x13x16) (18)
|
||||
I: conv2d_9_output f32(1x5x13x16) (18)
|
||||
O: eltwise_10_output f32(1x5x13x16) (35)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
7 nl_10_nl 10 Nonlinearity 1040 0 I: eltwise_10_output f32(1x5x13x16) (35)
|
||||
O: nl_10_nl_output f32(1x5x13x16) (43)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
8 conv2d_15 15 Conv2D 10784 2176 I: nl_10_nl_output f32(1x5x13x16) (43)
|
||||
S: conv2d_15_scratch0
|
||||
W: conv2d_15_weights f32(32x1x1x16) (16)
|
||||
W: conv2d_15_bias f32(32) (13)
|
||||
O: conv2d_15_output f32(1x3x7x32) (14)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
9 conv2d_11 11 Conv2D 3040 640 I: nl_10_nl_output f32(1x5x13x16) (43)
|
||||
W: conv2d_11_weights f32(16x3x3x1) (1)
|
||||
W: conv2d_6_bias f32(16) (46)
|
||||
O: conv2d_11_output f32(1x16x16x16) (0)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
9 conv2d_12 12 Conv2D 65552 1088 I: conv2d_11_output f32(1x16x16x16) (0)
|
||||
W: conv2d_6_bias f32(16) (22)
|
||||
O: conv2d_11_output f32(1x3x7x16) (0)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
10 conv2d_12 12 Conv2D 10784 2176 I: conv2d_11_output f32(1x3x7x16) (0)
|
||||
S: conv2d_12_scratch0
|
||||
W: conv2d_12_weights f32(16x1x1x16) (5)
|
||||
W: conv2d_12_bias f32(16) (2)
|
||||
O: conv2d_12_output f32(1x16x16x16) (3)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
10 nl_12_nl 12 Nonlinearity 4096 0 I: conv2d_12_output f32(1x16x16x16) (3)
|
||||
O: nl_12_nl_output f32(1x16x16x16) (70)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
11 conv2d_13 13 Conv2D 36880 640 I: nl_12_nl_output f32(1x16x16x16) (70)
|
||||
W: conv2d_13_weights f32(16x3x3x1) (7)
|
||||
W: conv2d_6_bias f32(16) (46)
|
||||
O: conv2d_13_output f32(1x16x16x16) (6)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
12 conv2d_14 14 Conv2D 65552 1088 I: conv2d_13_output f32(1x16x16x16) (6)
|
||||
W: conv2d_12_weights f32(32x1x1x16) (5)
|
||||
W: conv2d_12_bias f32(32) (2)
|
||||
O: conv2d_12_output f32(1x3x7x32) (3)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
11 nl_12_nl 12 Nonlinearity 672 0 I: conv2d_12_output f32(1x3x7x32) (3)
|
||||
O: nl_12_nl_output f32(1x3x7x32) (44)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
12 conv2d_13 13 Conv2D 6080 1280 I: nl_12_nl_output f32(1x3x7x32) (44)
|
||||
W: conv2d_13_weights f32(32x3x3x1) (8)
|
||||
W: conv2d_13_bias f32(32) (6)
|
||||
O: conv2d_13_output f32(1x3x7x32) (7)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
13 conv2d_14 14 Conv2D 21536 4224 I: conv2d_13_output f32(1x3x7x32) (7)
|
||||
S: conv2d_14_scratch0
|
||||
W: conv2d_14_weights f32(16x1x1x16) (11)
|
||||
W: conv2d_14_bias f32(16) (8)
|
||||
O: conv2d_14_output f32(1x16x16x16) (9)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
13 eltwise_15 15 Eltwise/add 4096 0 I: nl_10_nl_output f32(1x16x16x16) (69)
|
||||
I: conv2d_14_output f32(1x16x16x16) (69)
|
||||
O: eltwise_15_output f32(1x16x16x16) (60)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
14 nl_15_nl 15 Nonlinearity 4096 0 I: eltwise_15_output f32(1x16x16x16) (60)
|
||||
O: nl_15_nl_output f32(1x16x16x16) (71)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
15 conv2d_20 20 Conv2D 32800 2176 I: nl_15_nl_output f32(1x16x16x16) (71)
|
||||
S: conv2d_20_scratch0
|
||||
W: conv2d_20_weights f32(32x1x1x16) (28)
|
||||
W: conv2d_20_bias f32(32) (25)
|
||||
O: conv2d_20_output f32(1x8x8x32) (26)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
16 conv2d_16 16 Conv2D 9232 640 I: nl_15_nl_output f32(1x16x16x16) (71)
|
||||
W: conv2d_16_weights f32(16x3x3x1) (13)
|
||||
W: conv2d_6_bias f32(16) (46)
|
||||
O: conv2d_16_output f32(1x8x8x16) (12)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
17 conv2d_17 17 Conv2D 32800 2176 I: conv2d_16_output f32(1x8x8x16) (12)
|
||||
S: conv2d_17_scratch0
|
||||
W: conv2d_17_weights f32(32x1x1x16) (17)
|
||||
W: conv2d_17_bias f32(32) (14)
|
||||
O: conv2d_17_output f32(1x8x8x32) (15)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
18 nl_17_nl 17 Nonlinearity 2048 0 I: conv2d_17_output f32(1x8x8x32) (15)
|
||||
O: nl_17_nl_output f32(1x8x8x32) (72)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
19 conv2d_18 18 Conv2D 18464 1280 I: nl_17_nl_output f32(1x8x8x32) (72)
|
||||
W: conv2d_18_weights f32(32x3x3x1) (20)
|
||||
W: conv2d_18_bias f32(32) (18)
|
||||
O: conv2d_18_output f32(1x8x8x32) (19)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
20 conv2d_19 19 Conv2D 65568 4224 I: conv2d_18_output f32(1x8x8x32) (19)
|
||||
S: conv2d_19_scratch0
|
||||
W: conv2d_19_weights f32(32x1x1x32) (24)
|
||||
W: conv2d_19_bias f32(32) (21)
|
||||
O: conv2d_19_output f32(1x8x8x32) (22)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
21 eltwise_21 21 Eltwise/add 2048 0 I: conv2d_20_output f32(1x8x8x32) (26)
|
||||
I: conv2d_19_output f32(1x8x8x32) (26)
|
||||
O: eltwise_21_output f32(1x8x8x32) (61)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
22 nl_21_nl 21 Nonlinearity 2048 0 I: eltwise_21_output f32(1x8x8x32) (61)
|
||||
O: nl_21_nl_output f32(1x8x8x32) (73)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
23 conv2d_22 22 Conv2D 18464 1280 I: nl_21_nl_output f32(1x8x8x32) (73)
|
||||
W: conv2d_22_weights f32(32x3x3x1) (30)
|
||||
W: conv2d_18_bias f32(32) (18)
|
||||
O: conv2d_22_output f32(1x8x8x32) (29)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
24 conv2d_23 23 Conv2D 65568 4224 I: conv2d_22_output f32(1x8x8x32) (29)
|
||||
S: conv2d_23_scratch0
|
||||
W: conv2d_23_weights f32(32x1x1x32) (34)
|
||||
W: conv2d_23_bias f32(32) (31)
|
||||
O: conv2d_23_output f32(1x8x8x32) (32)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
25 nl_23_nl 23 Nonlinearity 2048 0 I: conv2d_23_output f32(1x8x8x32) (32)
|
||||
O: nl_23_nl_output f32(1x8x8x32) (74)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
26 conv2d_24 24 Conv2D 18464 1280 I: nl_23_nl_output f32(1x8x8x32) (74)
|
||||
W: conv2d_24_weights f32(32x3x3x1) (36)
|
||||
W: conv2d_18_bias f32(32) (18)
|
||||
O: conv2d_24_output f32(1x8x8x32) (35)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
27 conv2d_25 25 Conv2D 65568 4224 I: conv2d_24_output f32(1x8x8x32) (35)
|
||||
S: conv2d_25_scratch0
|
||||
W: conv2d_25_weights f32(32x1x1x32) (40)
|
||||
W: conv2d_25_bias f32(32) (37)
|
||||
O: conv2d_25_output f32(1x8x8x32) (38)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
28 eltwise_26 26 Eltwise/add 2048 0 I: nl_21_nl_output f32(1x8x8x32) (73)
|
||||
I: conv2d_25_output f32(1x8x8x32) (73)
|
||||
O: eltwise_26_output f32(1x8x8x32) (62)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
29 nl_26_nl 26 Nonlinearity 2048 0 I: eltwise_26_output f32(1x8x8x32) (62)
|
||||
O: nl_26_nl_output f32(1x8x8x32) (75)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
30 pool_27 27 Pool 2048 0 I: nl_26_nl_output f32(1x8x8x32) (75)
|
||||
O: pool_27_output f32(1x1x1x32) (79)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
31 gemm_28 28 Dense 1056 704 I: pool_27_output f32(1x1x1x32) (79)
|
||||
W: gemm_28_weights c4(32x32) (65)
|
||||
W: gemm_28_bias f32(32) (63)
|
||||
O: gemm_28_output f32(1x32) (64)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
32 nl_28_nl 28 Nonlinearity 32 0 I: gemm_28_output f32(1x32) (64)
|
||||
O: nl_28_nl_output f32(1x32) (76)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
33 gemm_29 29 Dense 99 124 I: nl_28_nl_output f32(1x32) (76)
|
||||
W: gemm_29_weights c4(3x32) (68)
|
||||
W: gemm_29_bias f32(3) (66)
|
||||
O: gemm_29_output f32(1x3) (67)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
34 nl_30 30 Nonlinearity 45 0 I: gemm_29_output f32(1x3) (67)
|
||||
O: nl_30_output f32(1x3) (77)
|
||||
------ ---------------- ---- --------------- -------- ------ ---------------------------------- ----------------------
|
||||
W: conv2d_14_weights f32(32x1x1x32) (12)
|
||||
W: conv2d_14_bias f32(32) (9)
|
||||
O: conv2d_14_output f32(1x3x7x32) (10)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
14 eltwise_16 16 Eltwise/add 672 0 I: conv2d_15_output f32(1x3x7x32) (14)
|
||||
I: conv2d_14_output f32(1x3x7x32) (14)
|
||||
O: eltwise_16_output f32(1x3x7x32) (36)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
15 nl_16_nl 16 Nonlinearity 672 0 I: eltwise_16_output f32(1x3x7x32) (36)
|
||||
O: nl_16_nl_output f32(1x3x7x32) (45)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
16 pool_17 17 Pool 672 0 I: nl_16_nl_output f32(1x3x7x32) (45)
|
||||
O: pool_17_output f32(1x1x1x32) (49)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
17 gemm_18 18 Dense 528 384 I: pool_17_output f32(1x1x1x32) (49)
|
||||
W: gemm_18_weights c4(16x32) (39)
|
||||
W: gemm_18_bias f32(16) (37)
|
||||
O: gemm_18_output f32(1x16) (38)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
18 nl_18_nl 18 Nonlinearity 16 0 I: gemm_18_output f32(1x16) (38)
|
||||
O: nl_18_nl_output f32(1x16) (46)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
19 gemm_19 19 Dense 34 88 I: nl_18_nl_output f32(1x16) (46)
|
||||
W: gemm_19_weights c4(2x16) (42)
|
||||
W: gemm_19_bias f32(2) (40)
|
||||
O: gemm_19_output f32(1x2) (41)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
20 nl_20 20 Nonlinearity 30 0 I: gemm_19_output f32(1x2) (41)
|
||||
O: nl_20_output f32(1x2) (47)
|
||||
------ ---------------- ---- --------------- ------- ------ ---------------------------------- ---------------------
|
||||
|
||||
|
||||
|
||||
@ -386,102 +266,78 @@ Number of operations per c-layer
|
||||
------- ------ -------------------------- --------- --------------
|
||||
c_id m_id name (type) #op type
|
||||
------- ------ -------------------------- --------- --------------
|
||||
0 5 conv2d_4 (Conv2D) 180,240 smul_f32_f32
|
||||
1 6 conv2d_6 (Conv2D) 36,880 smul_f32_f32
|
||||
2 7 conv2d_7 (Conv2D) 65,552 smul_f32_f32
|
||||
3 7 nl_7_nl (Nonlinearity) 4,096 op_f32_f32
|
||||
4 8 conv2d_8 (Conv2D) 36,880 smul_f32_f32
|
||||
5 9 conv2d_9 (Conv2D) 65,552 smul_f32_f32
|
||||
6 10 eltwise_10 (Eltwise/add) 4,096 op_f32_f32
|
||||
7 10 nl_10_nl (Nonlinearity) 4,096 op_f32_f32
|
||||
8 11 conv2d_11 (Conv2D) 36,880 smul_f32_f32
|
||||
9 12 conv2d_12 (Conv2D) 65,552 smul_f32_f32
|
||||
10 12 nl_12_nl (Nonlinearity) 4,096 op_f32_f32
|
||||
11 13 conv2d_13 (Conv2D) 36,880 smul_f32_f32
|
||||
12 14 conv2d_14 (Conv2D) 65,552 smul_f32_f32
|
||||
13 15 eltwise_15 (Eltwise/add) 4,096 op_f32_f32
|
||||
14 15 nl_15_nl (Nonlinearity) 4,096 op_f32_f32
|
||||
15 20 conv2d_20 (Conv2D) 32,800 smul_f32_f32
|
||||
16 16 conv2d_16 (Conv2D) 9,232 smul_f32_f32
|
||||
17 17 conv2d_17 (Conv2D) 32,800 smul_f32_f32
|
||||
18 17 nl_17_nl (Nonlinearity) 2,048 op_f32_f32
|
||||
19 18 conv2d_18 (Conv2D) 18,464 smul_f32_f32
|
||||
20 19 conv2d_19 (Conv2D) 65,568 smul_f32_f32
|
||||
21 21 eltwise_21 (Eltwise/add) 2,048 op_f32_f32
|
||||
22 21 nl_21_nl (Nonlinearity) 2,048 op_f32_f32
|
||||
23 22 conv2d_22 (Conv2D) 18,464 smul_f32_f32
|
||||
24 23 conv2d_23 (Conv2D) 65,568 smul_f32_f32
|
||||
25 23 nl_23_nl (Nonlinearity) 2,048 op_f32_f32
|
||||
26 24 conv2d_24 (Conv2D) 18,464 smul_f32_f32
|
||||
27 25 conv2d_25 (Conv2D) 65,568 smul_f32_f32
|
||||
28 26 eltwise_26 (Eltwise/add) 2,048 op_f32_f32
|
||||
29 26 nl_26_nl (Nonlinearity) 2,048 op_f32_f32
|
||||
30 27 pool_27 (Pool) 2,048 smul_f32_f32
|
||||
31 28 gemm_28 (Dense) 1,056 smul_f32_f4
|
||||
32 28 nl_28_nl (Nonlinearity) 32 op_f32_f32
|
||||
33 29 gemm_29 (Dense) 99 smul_f32_f4
|
||||
34 30 nl_30 (Nonlinearity) 45 op_f32_f32
|
||||
0 5 conv2d_4 (Conv2D) 45,776 smul_f32_f32
|
||||
1 6 conv2d_6 (Conv2D) 9,376 smul_f32_f32
|
||||
2 7 conv2d_7 (Conv2D) 16,656 smul_f32_f32
|
||||
3 7 nl_7_nl (Nonlinearity) 1,040 op_f32_f32
|
||||
4 8 conv2d_8 (Conv2D) 9,376 smul_f32_f32
|
||||
5 9 conv2d_9 (Conv2D) 16,656 smul_f32_f32
|
||||
6 10 eltwise_10 (Eltwise/add) 1,040 op_f32_f32
|
||||
7 10 nl_10_nl (Nonlinearity) 1,040 op_f32_f32
|
||||
8 15 conv2d_15 (Conv2D) 10,784 smul_f32_f32
|
||||
9 11 conv2d_11 (Conv2D) 3,040 smul_f32_f32
|
||||
10 12 conv2d_12 (Conv2D) 10,784 smul_f32_f32
|
||||
11 12 nl_12_nl (Nonlinearity) 672 op_f32_f32
|
||||
12 13 conv2d_13 (Conv2D) 6,080 smul_f32_f32
|
||||
13 14 conv2d_14 (Conv2D) 21,536 smul_f32_f32
|
||||
14 16 eltwise_16 (Eltwise/add) 672 op_f32_f32
|
||||
15 16 nl_16_nl (Nonlinearity) 672 op_f32_f32
|
||||
16 17 pool_17 (Pool) 672 smul_f32_f32
|
||||
17 18 gemm_18 (Dense) 528 smul_f32_f4
|
||||
18 18 nl_18_nl (Nonlinearity) 16 op_f32_f32
|
||||
19 19 gemm_19 (Dense) 34 smul_f32_f4
|
||||
20 20 nl_20 (Nonlinearity) 30 op_f32_f32
|
||||
------- ------ -------------------------- --------- --------------
|
||||
total 957,040
|
||||
total 156,480
|
||||
|
||||
Number of operation types
|
||||
---------------- --------- -----------
|
||||
operation type # %
|
||||
---------------- --------- -----------
|
||||
smul_f32_f32 918,944 96.0%
|
||||
op_f32_f32 36,941 3.9%
|
||||
smul_f32_f4 1,155 0.1%
|
||||
smul_f32_f32 150,736 96.3%
|
||||
op_f32_f32 5,182 3.3%
|
||||
smul_f32_f4 562 0.4%
|
||||
|
||||
Complexity report (model)
|
||||
------ ------------------ ------------------------- ------------------------- ----------
|
||||
m_id name c_macc c_rom c_id
|
||||
------ ------------------ ------------------------- ------------------------- ----------
|
||||
5 pool_5 |||||||||||||||| 18.8% ||| 2.2% [0]
|
||||
6 conv2d_6 |||| 3.9% ||| 2.2% [1]
|
||||
7 conv2d_7 |||||| 7.3% |||| 3.7% [2, 3]
|
||||
8 conv2d_8 |||| 3.9% ||| 2.2% [4]
|
||||
9 conv2d_9 |||||| 6.8% |||| 3.7% [5]
|
||||
10 eltwise_10 | 0.9% | 0.0% [6, 7]
|
||||
11 conv2d_11 |||| 3.9% ||| 2.2% [8]
|
||||
12 conv2d_12 |||||| 7.3% |||| 3.7% [9, 10]
|
||||
13 conv2d_13 |||| 3.9% ||| 2.2% [11]
|
||||
14 conv2d_14 |||||| 6.8% |||| 3.7% [12]
|
||||
15 eltwise_15 | 0.9% | 0.0% [13, 14]
|
||||
16 conv2d_16 | 1.0% ||| 2.2% [16]
|
||||
17 conv2d_17 ||| 3.6% |||||||| 7.4% [17, 18]
|
||||
18 conv2d_18 || 1.9% ||||| 4.4% [19]
|
||||
19 conv2d_19 |||||| 6.9% |||||||||||||||| 14.4% [20]
|
||||
20 conv2d_20 ||| 3.4% |||||||| 7.4% [15]
|
||||
21 eltwise_21 | 0.4% | 0.0% [21, 22]
|
||||
22 conv2d_22 || 1.9% ||||| 4.4% [23]
|
||||
23 conv2d_23 |||||| 7.1% |||||||||||||||| 14.4% [24, 25]
|
||||
24 conv2d_24 || 1.9% ||||| 4.4% [26]
|
||||
25 conv2d_25 |||||| 6.9% |||||||||||||||| 14.4% [27]
|
||||
26 eltwise_26 | 0.4% | 0.0% [28, 29]
|
||||
27 pool_27 | 0.2% | 0.0% [30]
|
||||
28 arith_constant31 | 0.1% ||| 2.4% [31, 32]
|
||||
29 arith_constant30 | 0.0% | 0.4% [33]
|
||||
30 nl_30 | 0.0% | 0.0% [34]
|
||||
5 pool_5 |||||||||||||||| 29.3% ||| 4.3% [0]
|
||||
6 conv2d_6 |||| 6.0% ||| 4.3% [1]
|
||||
7 conv2d_7 |||||| 11.3% |||| 7.3% [2, 3]
|
||||
8 conv2d_8 |||| 6.0% ||| 4.3% [4]
|
||||
9 conv2d_9 |||||| 10.6% |||| 7.3% [5]
|
||||
10 eltwise_10 | 1.3% | 0.0% [6, 7]
|
||||
11 conv2d_11 | 1.9% ||| 4.3% [9]
|
||||
12 conv2d_12 |||| 7.3% |||||||| 14.6% [10, 11]
|
||||
13 conv2d_13 || 3.9% ||||| 8.6% [12]
|
||||
14 conv2d_14 |||||||| 13.8% |||||||||||||||| 28.3% [13]
|
||||
15 conv2d_15 |||| 6.9% |||||||| 14.6% [8]
|
||||
16 eltwise_16 | 0.9% | 0.0% [14, 15]
|
||||
17 pool_17 | 0.4% | 0.0% [16]
|
||||
18 arith_constant19 | 0.3% || 2.6% [17, 18]
|
||||
19 arith_constant18 | 0.0% | 0.6% [19]
|
||||
20 nl_20 | 0.0% | 0.0% [20]
|
||||
------ ------------------ ------------------------- ------------------------- ----------
|
||||
macc=957,040 weights=29,372 act=37,120 ram_io=0
|
||||
macc=156,480 weights=14,936 act=11,904 ram_io=0
|
||||
|
||||
Requested memory size by section - "stm32f4" target
|
||||
------------------------------ -------- -------- -------- --------
|
||||
------------------------------ -------- -------- ------- --------
|
||||
module text rodata data bss
|
||||
------------------------------ -------- -------- -------- --------
|
||||
------------------------------ -------- -------- ------- --------
|
||||
NetworkRuntime1000_CM4_GCC.a 16,116 0 0 0
|
||||
model.o 1,684 280 10,716 432
|
||||
model.o 1,176 168 6,708 304
|
||||
model_data.o 48 16 88 0
|
||||
lib (toolchain)* 614 24 0 0
|
||||
------------------------------ -------- -------- -------- --------
|
||||
RT total** 18,462 320 10,804 432
|
||||
------------------------------ -------- -------- -------- --------
|
||||
weights 0 29,376 0 0
|
||||
activations 0 0 0 37,120
|
||||
------------------------------ -------- -------- ------- --------
|
||||
RT total** 17,954 208 6,796 304
|
||||
------------------------------ -------- -------- ------- --------
|
||||
weights 0 14,936 0 0
|
||||
activations 0 0 0 11,904
|
||||
io 0 0 0 0
|
||||
------------------------------ -------- -------- -------- --------
|
||||
TOTAL 18,462 29,696 10,804 37,552
|
||||
------------------------------ -------- -------- -------- --------
|
||||
------------------------------ -------- -------- ------- --------
|
||||
TOTAL 17,954 15,144 6,796 12,208
|
||||
------------------------------ -------- -------- ------- --------
|
||||
* toolchain objects (libm/libgcc*)
|
||||
** RT AI runtime objects (kernels+infrastructure)
|
||||
|
||||
@ -489,9 +345,9 @@ macc=957,040 weights=29,372 act=37,120 ram_io=0
|
||||
---------------------------------------------------
|
||||
FLASH (ro) %* RAM (rw) %
|
||||
---------------------------------------------------
|
||||
RT total 29,586 50.2% 11,236 23.2%
|
||||
RT total 24,958 62.6% 7,100 37.4%
|
||||
---------------------------------------------------
|
||||
TOTAL 58,962 48,356
|
||||
TOTAL 39,894 19,004
|
||||
---------------------------------------------------
|
||||
* rt/total
|
||||
|
||||
|
||||
@ -108,7 +108,7 @@ ProjectManager.ToolChainLocation=
|
||||
ProjectManager.UAScriptAfterPath=
|
||||
ProjectManager.UAScriptBeforePath=
|
||||
ProjectManager.UnderRoot=false
|
||||
ProjectManager.functionlistsort=1-SystemClock_Config-RCC-false-HAL-false,2-MX_GPIO_Init-GPIO-false-HAL-true,3-MX_USART2_UART_Init-USART2-false-HAL-true,3-MX_X_CUBE_AI_Init-STMicroelectronics.X-CUBE-AI.10.0.0-false-HAL-false,4-MX_X_CUBE_AI_Process-STMicroelectronics.X-CUBE-AI.10.0.0-false-HAL-false
|
||||
ProjectManager.functionlistsort=1-SystemClock_Config-RCC-false-HAL-false,2-MX_GPIO_Init-GPIO-false-HAL-true,3-MX_USART6_UART_Init-USART6-true-HAL-false,4-MX_X_CUBE_AI_Init-STMicroelectronics.X-CUBE-AI.10.0.0-false-HAL-false,5-MX_X_CUBE_AI_Process-STMicroelectronics.X-CUBE-AI.10.0.0-false-HAL-false
|
||||
RCC.48MHZClocksFreq_Value=84000000
|
||||
RCC.AHBFreq_Value=168000000
|
||||
RCC.APB1CLKDivider=RCC_HCLK_DIV4
|
||||
@ -151,7 +151,7 @@ RealThread.X-CUBE-RT-Thread_Nano.4.1.1.RTOSJjRTAaThread_Checked=true
|
||||
RealThread.X-CUBE-RT-Thread_Nano.4.1.1.RT_USING_CONSOLE=1
|
||||
RealThread.X-CUBE-RT-Thread_Nano.4.1.1.RT_USING_FINSH=1
|
||||
RealThread.X-CUBE-RT-Thread_Nano.4.1.1_SwParameter=RTAaThreadCcRTOSJjshell\:true;RTAaThreadCcRTOSJjlibcpu\:true;RTAaThreadCcRTOSJjkernel\:true;
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ActivationBufferSizeList=48356
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ActivationBufferSizeList=19004
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ActivationBuffers=pool0
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ActivationNames=pool0
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ActivationSizes=AI_MODEL_DATA_ACTIVATION_1_SIZE
|
||||
@ -169,14 +169,14 @@ STMicroelectronics.X-CUBE-AI.10.0.0.MaximumSizeOfInputLayer=1
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.MaximumSizeOfOutputLayer=1
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelActualCompression-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=0.0
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelCompression-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=High
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelFlashOccupation-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=59596
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelFlashOccupation-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=40532
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelHashList=c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelKind-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=TFLITE
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelMacc-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=957040
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelMacc-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=156480
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelName-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=model
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelNameList=model
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelRamOccupation-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=48356
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelStructureFile-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=D\:\\Job_Work\\Code\\Z_Python\\myEnv\\model.tflite
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelRamOccupation-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=19004
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelStructureFile-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=D\:\\Job_Work\\Code\\Z_Python\\myEnv\\model2.tflite
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ModelType-c35f95d1c3769e6590a83616504880a40e4284009f187f8d3c6d958dcc42b13d=STM32Cube.AI MCU runtime
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.ReadyForCodeGeneration=true
|
||||
STMicroelectronics.X-CUBE-AI.10.0.0.StackSize=0x800
|
||||
|
||||
@ -62,6 +62,7 @@
|
||||
| 2025-05-23 | 增加UART的传感器处理部分的功能函数 | |
|
||||
| 2025-05-24 | 完成传感器采集逻辑，现在1024完成 | |
|
||||
| | 左翻置信率低 怀疑垫体问题 | |
|
||||
| 2025-05-26 | CAN版本260点增加模型完成 | |
|
||||
|
||||
---
|
||||
|
||||
|
||||
@ -1822,7 +1822,7 @@
|
||||
<Name>Build</Name>
|
||||
<Buttons>
|
||||
<Len>970</Len>
|
||||
<Data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ata>
|
||||
<Data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ata>
|
||||
</Buttons>
|
||||
<OriginalItems>
|
||||
<Len>583</Len>
|
||||
@ -3687,9 +3687,9 @@
|
||||
</Doc>
|
||||
<Doc>
|
||||
<Name>..\Core\Src\mySensor_deal.c</Name>
|
||||
<ColumnNumber>7</ColumnNumber>
|
||||
<ColumnNumber>28</ColumnNumber>
|
||||
<TopLine>85</TopLine>
|
||||
<CurrentLine>90</CurrentLine>
|
||||
<CurrentLine>101</CurrentLine>
|
||||
<Folding>1</Folding>
|
||||
<ContractedFolders></ContractedFolders>
|
||||
<PaneID>0</PaneID>
|
||||
|
||||
|
Can't render this file because it is too large.
|
8306
资料/测试数据/260点.csv
Normal file
8306
资料/测试数据/260点.csv
Normal file
File diff suppressed because it is too large
Load Diff
BIN
资料/算法文件/原始文件/model_functional.keras
Normal file
BIN
资料/算法文件/原始文件/model_functional.keras
Normal file
Binary file not shown.
BIN
资料/算法文件/原始文件/sleep_posture_binary_mcu.keras
Normal file
BIN
资料/算法文件/原始文件/sleep_posture_binary_mcu.keras
Normal file
Binary file not shown.
BIN
资料/算法文件/转换文件/model2.tflite
Normal file
BIN
资料/算法文件/转换文件/model2.tflite
Normal file
Binary file not shown.
Loading…
Reference in New Issue
Block a user