TDA2: TIDI TensorFlow MobileNet

Luca Rigazio61

Prodigy 50 points

Part Number: TDA2

I tried to port MobileNet as described here -- e2e.ti.com/.../2717341

When running inference with -- eve_test_dl_algo.out config_list.txt

I get a bunch of layers failing ~ as in here

any pointers would be greatly appreciated

thank you!

.luca

numFrames = 1
preProcType = 2
inData = preproc_2_224x224.y
outData = "./stats_tool_out.bin"
netBinFile = "tidl_net_mobilenet_1_224.bin"
paramsBinFile = "tidl_param_mobilenet_1_224.bin"
inWidth = 224
inHeight = 224
inNumChannels = 3
(tf1.1_env) luca@doppio tf-example eve_test_dl_algo.out config_list.txt

Processing config file tidl_config_mobileNet1.txt !
0, TIDL_DataLayer , 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 ,
1, TIDL_ConvolutionLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 ,
2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 ,
3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 ,
4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 ,
5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 ,
6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 ,
7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 ,
8, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 ,
9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 ,
10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 ,
11, TIDL_ConvolutionLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 ,
12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 ,
13, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 ,
14, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
15, TIDL_ConvolutionLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
16, TIDL_ConvolutionLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
17, TIDL_ConvolutionLayer , 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
18, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
19, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
20, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
21, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
22, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
23, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
24, TIDL_ConvolutionLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 ,
25, TIDL_ConvolutionLayer , 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 ,
26, TIDL_ConvolutionLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 ,
27, TIDL_ConvolutionLayer , 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 ,
28, TIDL_PoolingLayer , 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 ,
29, TIDL_InnerProductLayer , 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 ,
30, TIDL_SoftMaxLayer , 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 ,
31, TIDL_DataLayer , 0, 1 , -1 , 30 , x , x , x , x , x , x , x , 0 , 1 , 1 , 1 , 1001 , 0 , 0 , 0 , 0 ,
Layer ID ,inBlkWidth ,inBlkHeight ,inBlkPitch ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs ,numOutChs ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot
1 72 60 72 32 28 32 3 32 3 1 8 1 3 4 4 4320 896 1
2 40 30 40 32 28 32 1 1 1 1 1 1 1 4 4 1200 896 1
3 32 28 32 32 28 32 32 64 32 8 8 1 4 4 4 896 896 1
4 72 60 72 32 28 32 1 1 1 1 1 1 1 2 2 4320 896 1
5 32 28 32 32 28 32 64 128 64 8 8 1 8 2 2 896 896 1
6 40 30 40 32 28 32 1 1 1 1 1 1 1 2 2 1200 896 1
7 32 28 32 32 28 32 128 128 128 8 8 1 16 2 2 896 896 1
8 72 60 72 32 28 32 1 1 1 1 1 1 1 1 1 4320 896 1
9 32 28 32 32 28 32 128 256 128 8 8 1 16 1 1 896 896 1
10 40 30 40 32 28 32 1 1 1 1 1 1 1 1 1 1200 896 1
11 32 28 32 32 28 32 256 256 256 8 8 1 32 1 1 896 896 1
12 40 32 40 16 14 16 1 1 1 1 1 1 1 1 1 1280 224 1
13 16 14 16 16 14 16 256 512 256 8 8 1 32 1 1 224 224 1
14 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
15 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
16 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
17 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
18 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
19 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
20 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
21 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
22 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
23 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
24 40 18 40 16 7 16 1 1 1 1 1 1 1 1 1 720 112 1
25 16 7 16 16 7 16 512 1024 512 8 8 1 64 1 1 112 112 1
26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1
27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1

Processing Frame Number : 0

Layer 1 : Out Q : 95997 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11
Layer 2 : Out Q : 7608233 , Failing at 0, 1, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 3 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 20.47, Sparsity : 20.31
Layer 4 : Out Q : 157 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 5 : Out Q : 126194 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 24.56, Sparsity : 4.39
Layer 6 : Out Q : 9566000 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 7 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 50.97, Sparsity : 0.81
Layer 8 : Out Q : 205 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 9 : Out Q : 246241 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 10 : Out Q : 78632959 , Failing at 0, 2, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 11 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 12 : Out Q : 1469 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 13 : Out Q : 2961619 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 14 : Out Q : 729951977 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 15 : Out Q : 502695931 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 16 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 17 : Out Q : 3499 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 18 : Out Q : 333160 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 19 : Out Q : 808651178 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 20 : Out Q : 63449855 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 21 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.01
Layer 22 : Out Q : 1103 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 23 : Out Q : 2998754 , Failing at 0, 0, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 24 : Out Q : 427423464 , Failing at 0, 2, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.23, 0.23, Sparsity : 0.00
Layer 25 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.59, Sparsity : 0.39
Layer 26 : Out Q : 67 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 27 : Out Q : 39868 , Failing at 0, 1, 0, 0 ref,out = 255,0
TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 28 : Out Q : 409849294 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 29 : Out Q : 1 , [0][0] - outData - 0 outputRef - 127
TIDL_InnerProductLayer, FAILED!!!!!! #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 30 :-------Max Index 1000 : 0 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00
End of config list found !

over 7 years ago

0 kumar.desappan over 7 years ago

TI__Mastermind 22145 points

Hi,
Did you get the expeted result during the import step?

0 Luca Rigazio61 over 7 years ago in reply to kumar.desappan

Prodigy 50 points

Hi Kumar, yes it appears import was successful, see next -- any suggestions?

luca@doppio tf-example tidl_model_import.out tidl_import_mobileNet1.txt

TF Model File : mobilenet_1_224.pb
Num of Layer Detected : 276
0, TIDL_DataLayer 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 , 0 ,
1, TIDL_ConvolutionLayer 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 , 10838016 ,
2, TIDL_ConvolutionLayer 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 , 3612672 ,
3, TIDL_ConvolutionLayer 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 , 25690112 ,
4, TIDL_ConvolutionLayer 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 , 1806336 ,
5, TIDL_ConvolutionLayer 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 , 25690112 ,
6, TIDL_ConvolutionLayer 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 3612672 ,
7, TIDL_ConvolutionLayer 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 51380224 ,
8, TIDL_ConvolutionLayer 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 , 903168 ,
9, TIDL_ConvolutionLayer 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 , 25690112 ,
10, TIDL_ConvolutionLayer 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 1806336 ,
11, TIDL_ConvolutionLayer 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 51380224 ,
12, TIDL_ConvolutionLayer 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 , 451584 ,
13, TIDL_ConvolutionLayer 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 , 25690112 ,
14, TIDL_ConvolutionLayer 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 ,
15, TIDL_ConvolutionLayer 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 ,
16, TIDL_ConvolutionLayer 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 ,
17, TIDL_ConvolutionLayer 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 ,
18, TIDL_ConvolutionLayer 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 ,
19, TIDL_ConvolutionLayer 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 ,
20, TIDL_ConvolutionLayer 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 ,
21, TIDL_ConvolutionLayer 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 ,
22, TIDL_ConvolutionLayer 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 ,
23, TIDL_ConvolutionLayer 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 ,
24, TIDL_ConvolutionLayer 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 , 225792 ,
25, TIDL_ConvolutionLayer 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 , 25690112 ,
26, TIDL_ConvolutionLayer 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 451584 ,
27, TIDL_ConvolutionLayer 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 51380224 ,
28, TIDL_PoolingLayer 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 , 50176 ,
29, TIDL_InnerProductLayer 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 , 1025024 ,
30, TIDL_SoftMaxLayer 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 , 1001 ,
Total Giga Macs : 0.5688

Processing config file ./tempDir/qunat_stats_config.txt !
0, TIDL_DataLayer , 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 ,
1, TIDL_ConvolutionLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 ,
2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 ,
3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 ,
4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 ,
5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 ,
6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 ,
7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 ,
8, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 ,
9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 ,
10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 ,
11, TIDL_ConvolutionLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 ,
12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 ,
13, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 ,
14, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
15, TIDL_ConvolutionLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
16, TIDL_ConvolutionLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
17, TIDL_ConvolutionLayer , 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
18, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
19, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
20, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
21, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
22, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
23, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 ,
24, TIDL_ConvolutionLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 ,
25, TIDL_ConvolutionLayer , 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 ,
26, TIDL_ConvolutionLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 ,
27, TIDL_ConvolutionLayer , 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 ,
28, TIDL_PoolingLayer , 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 ,
29, TIDL_InnerProductLayer , 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 ,
30, TIDL_SoftMaxLayer , 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 ,
31, TIDL_DataLayer , 0, 1 , -1 , 30 , x , x , x , x , x , x , x , 0 , 1 , 1 , 1 , 1001 , 0 , 0 , 0 , 0 ,
Layer ID ,inBlkWidth ,inBlkHeight ,inBlkPitch ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs ,numOutChs ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot
1 72 60 72 32 28 32 3 32 3 1 8 1 3 4 4 4320 896 1
2 40 30 40 32 28 32 1 1 1 1 1 1 1 4 4 1200 896 1
3 32 28 32 32 28 32 32 64 32 8 8 1 4 4 4 896 896 1
4 72 60 72 32 28 32 1 1 1 1 1 1 1 2 2 4320 896 1
5 32 28 32 32 28 32 64 128 64 8 8 1 8 2 2 896 896 1
6 40 30 40 32 28 32 1 1 1 1 1 1 1 2 2 1200 896 1
7 32 28 32 32 28 32 128 128 128 8 8 1 16 2 2 896 896 1
8 72 60 72 32 28 32 1 1 1 1 1 1 1 1 1 4320 896 1
9 32 28 32 32 28 32 128 256 128 8 8 1 16 1 1 896 896 1
10 40 30 40 32 28 32 1 1 1 1 1 1 1 1 1 1200 896 1
11 32 28 32 32 28 32 256 256 256 8 8 1 32 1 1 896 896 1
12 40 32 40 16 14 16 1 1 1 1 1 1 1 1 1 1280 224 1
13 16 14 16 16 14 16 256 512 256 8 8 1 32 1 1 224 224 1
14 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
15 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
16 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
17 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
18 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
19 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
20 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
21 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
22 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1
23 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1
24 40 18 40 16 7 16 1 1 1 1 1 1 1 1 1 720 112 1
25 16 7 16 16 7 16 512 1024 512 8 8 1 64 1 1 112 112 1
26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1
27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1

Processing Frame Number : 0

Image reading is Not Supported. OpenCV not Enabled
Layer 1 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11
Layer 2 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 3 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 20.47, Sparsity : 20.31
Layer 4 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 5 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 24.56, Sparsity : 4.39
Layer 6 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 7 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 50.97, Sparsity : 0.81
Layer 8 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 9 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 10 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 11 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 12 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 13 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 14 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 15 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 16 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 17 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 18 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 19 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 20 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 21 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.01
Layer 22 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 23 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 24 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.23, 0.23, Sparsity : 0.00
Layer 25 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.59, Sparsity : 0.39
Layer 26 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 27 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 28 : Out Q : 1 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 29 : Out Q : 1 , TIDL_InnerProductLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 30 :-------Max Index 1000 : 0 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00
End of config list found !

0 Luca Rigazio61 over 7 years ago in reply to Luca Rigazio61

Prodigy 50 points

also something interesting happened ~ if I use the "ref" script it seems to be working

is there any difference between these two scripts? which one is the correct one to use?

thank you!

.luca

--

eve_test_dl_algo_ref.out config_list.txt

...
26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1
27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1

Processing Frame Number : 0

Layer 1 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11
Layer 2 : Out Q : 10877 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 3 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 20.47, Sparsity : 20.31
Layer 4 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 5 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 24.56, Sparsity : 4.39
Layer 6 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00
Layer 7 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 50.97, Sparsity : 0.81
Layer 8 : Out Q : 10879 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 9 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 10 : Out Q : 10879 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00
Layer 11 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 12 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 13 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02
Layer 14 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 15 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 16 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 17 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 18 : Out Q : 10878 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 19 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20
Layer 20 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 21 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.01
Layer 22 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00
Layer 23 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 24 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.23, 0.23, Sparsity : 0.00
Layer 25 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.59, Sparsity : 0.39
Layer 26 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00
Layer 27 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00
Layer 28 : Out Q : 14700 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 29 : Out Q : 1418 , TIDL_InnerProductLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00
Layer 30 :-------Max Index 896 : 63 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00
End of config list found !

0 kumar.desappan over 7 years ago in reply to Luca Rigazio61

TI__Mastermind 22145 points

Can you let me know the source of this "eve_test_dl_algo_ref.out".
I dont see it part of the relese package? are you referering quant stats tool.

0 kumar.desappan over 7 years ago in reply to kumar.desappan

TI__Mastermind 22145 points

Since we haven't heard back, we hope you could find solution.
Closing the thread.

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