Neural Network Tools for STM32 family v1.7.0 (stm.ai v8.1.0-19520)
Created date          : 2023-10-05 18:02:55
Parameters            : generate --name plantnetwork -m /home/repex/Scrivania/Tesi/proj/Sender/ImpedanceModulusPhaseModels/2023-05-01_19-46-03_SinglePlantSearch_Plant4TrainingAndTest1HiddenLayerMoreEpochs/models/model_1.onnx --type onnx --compression lossless --verbosity 1 --workspace /tmp/mxAI_workspace4433740248456811468386660838800 --output /home/repex/.stm32cubemx/plantnetwork_output --allocate-inputs --series stm32wl --allocate-outputs

Exec/report summary (generate)
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model file         :   /home/repex/Scrivania/Tesi/proj/Sender/ImpedanceModulusPhaseModels/2023-05-01_19-46-03_SinglePlantSearch_Plant4TrainingAndTest1HiddenLayerMoreEpochs/models/model_1.onnx   
type               :   onnx                                                                                                                                                                       
c_name             :   plantnetwork                                                                                                                                                               
compression        :   lossless                                                                                                                                                                   
options            :   allocate-inputs, allocate-outputs                                                                                                                                          
optimization       :   balanced                                                                                                                                                                   
target/series      :   stm32wl                                                                                                                                                                    
workspace dir      :   /tmp/mxAI_workspace4433740248456811468386660838800                                                                                                                         
output dir         :   /home/repex/.stm32cubemx/plantnetwork_output                                                                                                                               
model_fmt          :   float                                                                                                                                                                      
model_name         :   model_1                                                                                                                                                                    
model_hash         :   7b9fec4aaa9d1d03ff61b1f82a203c61                                                                                                                                           
params #           :   381 items (1.49 KiB)                                                                                                                                                       
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input 1/1          :   'Input' (domain:activations/**default**)                                                                                                                                   
                   :   2 items, 8 B, ai_float, float, (1,2)                                                                                                                                       
output 1/1         :   'Status' (domain:activations/**default**)                                                                                                                                  
                   :   1 items, 4 B, ai_float, float, (1,1)                                                                                                                                       
macc               :   666                                                                                                                                                                        
weights (ro)       :   1,524 B (1.49 KiB) (1 segment)                                                                                                                                             
activations (rw)   :   388 B (388 B) (1 segment) *                                                                                                                                                
ram (total)        :   388 B (388 B) = 388 + 0 + 0                                                                                                                                                
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(*) 'input'/'output' buffers can be used from the activations buffer

Model name - model_1 ['Input'] ['Status']
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
m_id   layer (type,original)                                       oshape            param/size     macc                      connected to   | c_size          c_macc          c_type                   
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
1      onnxMatMul_12 (Placeholder, MatMul)                         [h:2,h:2,c:95]    190/760                                                 | -760(-100.0%)                   
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
2      InputLayer_bias (Placeholder, Add)                          [c:95]            95/380                                                  | +760(+200.0%)   +285(+100.0%)   dense_of32[0]            
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
4      onnxMatMul_13 (Placeholder, MatMul)                         [h:95,h:95,c:1]   95/380                                                  |                 +95(+100.0%)    dense_of32[2]            
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
5      Output_bias (Placeholder, Add)                              [c:1]             1/4                                                     |                 +1(+100.0%)     eltwise/sum_of32[o][3]   
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
0      Input (Input, )                                             [c:2]                                                                     |                                 
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
1      _InputLayer_MatMul_output_0 (Gemm, MatMul)                  [c:95]                            285                             Input   |                 -285(-100.0%)   
                                                                                                                             onnxMatMul_12   | 
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
2      _InputLayer_Add_output_0 (Eltwise, Add)                     [c:95]                             95                   InputLayer_bias   |                 -95(-100.0%)    
                                                                                                               _InputLayer_MatMul_output_0   | 
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
3      _Activation0_LeakyRelu_output_0 (Nonlinearity, LeakyRelu)   [c:95]                             95          _InputLayer_Add_output_0   |                 +190(+200.0%)   nl_of32[1]               
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
4      _Output_MatMul_output_0 (Gemm, MatMul)                      [c:1]                              96   _Activation0_LeakyRelu_output_0   |                 -96(-100.0%)    
                                                                                                                             onnxMatMul_13   | 
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
5      Status (Eltwise, Add)                                       [c:1]                               1                       Output_bias   |                 -1(-100.0%)     
                                                                                                                   _Output_MatMul_output_0   | 
------ ----------------------------------------------------------- ----------------- ------------ ------ --------------------------------- --- --------------- --------------- ------------------------ 
model/c-model: macc=572/666 +94(+16.4%) weights=1,524/1,524  activations=--/388 io=--/0



Generated C-graph summary
------------------------------------------------------------------------------------------------------------------------
model name            : model_1
c-name                : plantnetwork
c-node #              : 4
c-array #             : 9
activations size      : 388 (1 segment)
weights size          : 1524 (1 segment)
macc                  : 666
inputs                : ['Input_output']
outputs               : ['Status_output']

C-Arrays (9)
------ ---------------------------------------- ----------- ------------------------- ------------- --------- --------- 
c_id   name (*_array)                           item/size   domain/mem-pool           c-type        fmt       comment   
------ ---------------------------------------- ----------- ------------------------- ------------- --------- --------- 
0      Input_output                             2/8         activations/**default**   float         float32   /input    
1      _InputLayer_MatMul_output_0_output       95/380      activations/**default**   float         float32             
2      _Activation0_LeakyRelu_output_0_output   95/380      activations/**default**   float         float32             
3      _Output_MatMul_output_0_output           1/4         activations/**default**   float         float32             
4      Status_output                            1/4         activations/**default**   float         float32   /output   
5      _InputLayer_MatMul_output_0_weights      190/760     weights/weights           const float   float32             
6      _InputLayer_MatMul_output_0_bias         95/380      weights/weights           const float   float32             
7      _Output_MatMul_output_0_weights          95/380      weights/weights           const float   float32             
8      Output_bias                              1/4         weights/weights           const float   float32             
------ ---------------------------------------- ----------- ------------------------- ------------- --------- --------- 

C-Layers (4)
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 
c_id   name (*_layer)                    id   layer_type     macc   rom    tensors                                     shape (array id)   
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 
0      _InputLayer_MatMul_output_0       2    dense          285    1140   I: Input_output                             (1,2) (0)          
                                                                           W: _InputLayer_MatMul_output_0_weights      (2,95) (5)         
                                                                           W: _InputLayer_MatMul_output_0_bias         (95,) (6)          
                                                                           O: _InputLayer_MatMul_output_0_output       (1,95) (1)         
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 
1      _Activation0_LeakyRelu_output_0   3    nl             285    0      I: _InputLayer_MatMul_output_0_output       (1,95) (1)         
                                                                           O: _Activation0_LeakyRelu_output_0_output   (1,95) (2)         
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 
2      _Output_MatMul_output_0           4    dense          95     380    I: _Activation0_LeakyRelu_output_0_output   (1,95) (2)         
                                                                           W: _Output_MatMul_output_0_weights          (95,1) (7)         
                                                                           O: _Output_MatMul_output_0_output           (1,1) (3)          
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 
3      Status                            5    eltwise/sum    1      4      I: Output_bias (const)                      (1,) (8)           
                                                                           I: _Output_MatMul_output_0_output (const)   (1,1) (3)          
                                                                           O: Status_output                            (1,1) (4)          
------ --------------------------------- ---- -------------- ------ ------ ------------------------------------------- ------------------ 



Number of operations per c-layer
------- ------ -------------------------------------- ----- -------------- -------- ---------- 
c_id    m_id   name (type)                              #op           type   #param   sparsity 
------- ------ -------------------------------------- ----- -------------- -------- ---------- 
0       2      _InputLayer_MatMul_output_0 (dense)      285   smul_f32_f32      285     0.0000 
1       3      _Activation0_LeakyRelu_output_0 (nl)     285     op_f32_f32          
2       4      _Output_MatMul_output_0 (dense)           95   smul_f32_f32       95     0.0000 
3       5      Status (eltwise/sum)                       1     op_f32_f32        1     0.0000 
------- ------ -------------------------------------- ----- -------------- -------- ---------- 
total                                                   666                     381     0.0000 

Number of operation types
---------------- ----- ----------- 
operation type       #           % 
---------------- ----- ----------- 
smul_f32_f32       380       57.1% 
op_f32_f32         286       42.9% 

Complexity report (model)
------ --------------------------------- ------------------------- ------------------------- ------ 
m_id   name                              c_macc                    c_rom                     c_id   
------ --------------------------------- ------------------------- ------------------------- ------ 
2      InputLayer_bias                   ||||||||||||||||  42.8%   ||||||||||||||||  74.8%   [0]    
4      onnxMatMul_13                     ||||||            14.3%   ||||||            24.9%   [2]    
5      Output_bias                       |                  0.2%   |                  0.3%   [3]    
3      _Activation0_LeakyRelu_output_0   ||||||||||||||||  42.8%   |                  0.0%   [1]    
------ --------------------------------- ------------------------- ------------------------- ------ 
macc=666 weights=1,524 act=388 ram_io=0
 
 Requested memory size per segment ("stm32wl" series)
 ----------------------------- -------- -------- ------- ----- 
 module                            text   rodata    data   bss 
 ----------------------------- -------- -------- ------- ----- 
 NetworkRuntime810_CM4_GCC.a      9,152        0       0     0 
 plantnetwork.o                     512       60   1,268   136 
 plantnetwork_data.o                 56       48      88     0 
 lib (toolchain)*                 1,448        0       0     0 
 ----------------------------- -------- -------- ------- ----- 
 RT total**                      11,168      108   1,356   136 
 ----------------------------- -------- -------- ------- ----- 
 *weights*                            0    1,528       0     0 
 *activations*                        0        0       0   388 
 *io*                                 0        0       0     0 
 ----------------------------- -------- -------- ------- ----- 
 TOTAL                           11,168    1,636   1,356   524 
 ----------------------------- -------- -------- ------- ----- 
 *  toolchain objects (libm/libgcc*)
 ** RT - AI runtime objects (kernels+infrastructure)
  
  Summary per memory device type
  --------------------------------------------
  .\device      FLASH       %     RAM       % 
  --------------------------------------------
  RT total     12,632   89.2%   1,492   79.4% 
  --------------------------------------------
  TOTAL        14,160           1,880         
  --------------------------------------------


Generated files (7)
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/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork_config.h        
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork.h               
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork.c               
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork_data_params.h   
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork_data_params.c   
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork_data.h          
/home/repex/.stm32cubemx/plantnetwork_output/plantnetwork_data.c          
