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    How to convert from pytorch to nnb for spresense?

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    • N
      niciBume @KamilTomaszewski last edited by

      Hi @kamiltomaszewski thanks for the reply!

      The output of the dnnrt_lenet example is the following:

      nsh> dnnrt_lenet --s /mnt/sd0/sony_nabla.nnb
Load nnb file: /mnt/sd0/sony_nabla.nnb
Load pgm image: /mnt/sd0/0.pgm
Image Normalization (1.0/255.0): skipped
start dnn_runtime_forward()
up_hardfault: PANIC!!! Hard fault: 40000000
up_assert: Assertion failed at file:armv7-m/up_hardfault.c line: 148 task: sony_uav
up_registerdump: R0: 0d0f6e54 0d09969c 0d099918 00000000 00000015 0d04b770 0d03d6b0 0d04b6e0
up_registerdump: R8: 00000003 00000000 00000000 00000000 00000009 0d04b6b0 0d024ae5 00000000
up_registerdump: xPSR: 00000000 BASEPRI: 000000e0 CONTROL: 00000000
up_registerdump: EXC_RETURN: ffffffe9
up_dumpstate: sp:     0d03aba8
up_dumpstate: IRQ stack:
up_dumpstate:   base: 0d03ac00
up_dumpstate:   size: 00000800
up_dumpstate:   used: 00000148
up_stackdump: 0d03aba0: 000007c4 0d00257b 000000e0 00000000 00000000 00000009 0d04b6b0 0d024ae5
up_stackdump: 0d03abc0: 00000000 0d03abd0 0d001a9f 00000003 00000000 0d001aa7 0d001a85 0d00354f
up_stackdump: 0d03abe0: 000000e0 0d001a79 000000e0 0d04b5dc 0d04b770 0d03d6b0 0d04b6e0 0d000333
up_dumpstate: sp:     0d04b6b0
up_dumpstate: User stack:
up_dumpstate:   base: 0d04b720
up_dumpstate:   size: 000007c4
up_dumpstate:   used: 00000628
up_stackdump: 0d04b6a0: 00000000 80000000 80000010 0d024ae5 0d0f69a0 0d0f6900 0d04b770 0d020b7d
up_stackdump: 0d04b6c0: 00015419 00000000 0d04ba00 0d03d6b0 00000001 0d020899 00000000 00000001
up_stackdump: 0d04b6e0: 0d03d6b0 0d04b770 00000249 00015419 00000000 00000000 00000000 00000101
up_stackdump: 0d04b700: 00000000 00000000 00000000 00000000 00000000 0d004377 00000000 00000000
up_taskdump: Idle Task: PID=0 Stack Used=0 of 0
up_taskdump: hpwork: PID=1 Stack Used=576 of 2028
up_taskdump: lpwork: PID=2 Stack Used=352 of 2028
up_taskdump: lpwork: PID=3 Stack Used=352 of 2028
up_taskdump: lpwork: PID=4 Stack Used=352 of 2028
up_taskdump: cxd56_pm_task: PID=6 Stack Used=352 of 996
up_taskdump: init: PID=7 Stack Used=1008 of 8172
up_taskdump: sony_uav: PID=16 Stack Used=1576 of 1988

      This seems to be a nuttX error message, if I am not mistaking?

      It actually passes dnn_runtime_initialize but fails at dnn_runtime_forward(), where I trace it back to https://github.com/sonydevworld/spresense/blob/87f81d9c35c7d05d6a75e9177b45d6cbe8d8c063/sdk/modules/dnnrt/src/runtime/runtime_nnabla.c#L186

      Regarding the conversion, I tied your suggestion, yet with the same result. Would you know the build commands for the NNC?

      Best,

      Nic

      K 1 Reply Last reply Reply Quote
      • K
        KamilTomaszewski DeveloperWorld @niciBume last edited by

        @nicibume

        Could you please try the converter from Nnabla version 1.12.0?

        Best Regards,
        Kamil Tomaszewski

        N 2 Replies Last reply Reply Quote
        • N
          niciBume @KamilTomaszewski last edited by

          @kamiltomaszewski

          I downgraded Nnabla to 1.12.0 and it worked! Thanks a lot for the help!

          Cheers,
          Nic

          1 Reply Last reply Reply Quote
          • N
            niciBume @KamilTomaszewski last edited by

            @kamiltomaszewski

            Hmmm... while the example (exported it directly from NNC as .onnx and .nnb to ensure that the model works) .onnx -> .nnp -> .nnb now works on the Spresense. However, with Nnabla 1.12.0 my actual PyTorch -> .onnx model can not be converted to .nnp anymore. This is a step that actually worked with Nnabla 1.20.0. I traced this issue back to Nnabla 1.14.0, where PyTorch -> .onnx works again, but the .onnx -> .nnp -> .nnb conversion yields the same error on the MCU as previously stated.

            Is there a workaround for this?

            Best,
            Nic

            N 1 Reply Last reply Reply Quote
            • N
              niciBume @niciBume last edited by niciBume

              Forgot to add error print (and can't edit post anymore):

              $ nnabla_cli convert mnistcnn.onnx mnistcnn.nnp
2021-07-27 13:40:17,220 [nnabla][INFO]: Initializing CPU extension...
NNabla command line interface (Version:1.12.0, Build:200929110548)
Traceback (most recent call last):
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/cli/cli.py", line 141, in cli_main
    return_value = args.func(args)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/cli/convert.py", line 54, in convert_command
    nnabla.utils.converter.convert_files(args, args.files, output)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/commands.py", line 260, in convert_files
    nnp = _import_file(args, ifiles)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/commands.py", line 51, in _import_file
    return OnnxImporter(*ifiles).execute()
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/onnx/importer.py", line 3002, in execute
    return self.onnx_model_to_nnp_protobuf()
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/onnx/importer.py", line 2986, in onnx_model_to_nnp_protobuf
    self.onnx_graph_to_nnp_protobuf(pb)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/onnx/importer.py", line 2867, in onnx_graph_to_nnp_protobuf
    fl = self.convert_to_functions(n)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/onnx/importer.py", line 2857, in convert_to_functions
    ft(func_list, n)
  File "/home/niclas/anaconda3/envs/torch_nnp_test/lib/python3.6/site-packages/nnabla/utils/converter/onnx/importer.py", line 1315, in Gemm
    bias_shape = [1] * (len(shape) - len(bias_shape)) + bias_shape
TypeError: can only concatenate list (not "google.protobuf.pyext._message.RepeatedScalarContainer") to list
              K 1 Reply Last reply Reply Quote
              • K
                KamilTomaszewski DeveloperWorld @niciBume last edited by

                @nicibume I have another idea. Please use the latest version of NNabla, but update the NNabla C Runtime Library used by Spresense.

                To do this:

                1. Update NNabla C Runtime Library:
                $ cd externals/nnablart/nnabla-c-runtime
$ git fetch
$ git rebase origin/master
                1. Update nnablart Makefile:
                diff --git a/externals/nnablart/Makefile b/externals/nnablart/Makefile
index cb136a93..1182ad5b 100644
--- a/externals/nnablart/Makefile
+++ b/externals/nnablart/Makefile
@@ -56,7 +56,7 @@ CFLAGS += -std=c99
 
 CFLAGS := $(patsubst -O%,-O3,$(CFLAGS))
 
-CSRCS    =   accessor.c list.c shape.c
+CSRCS    =   accessor.c fixedpoint.c list.c shape.c
 ROOTDEPPATH  = --dep-path $(SRCDIR)/functions/utilities
 VPATH    = $(SRCDIR)/functions/utilities
 
@@ -73,7 +73,7 @@ CSRCS   += binary_tanh.c binary_sigmoid.c binary_connect_affine.c binary_weight_
 ROOTDEPPATH += --dep-path $(SRCDIR)/functions/implements/quantization
 VPATH   += $(SRCDIR)/functions/implements/quantization
 
-CSRCS   += add_scalar.c arithmetic.c arithmetic_generic.c div2.c mul2.c mul_scalar.c
+CSRCS   += add_scalar.c arithmetic.c arithmetic_fixed.c arithmetic_generic.c div2.c mul2.c mul_scalar.c
 CSRCS   += pow2.c pow_scalar.c r_div_scalar.c r_pow_scalar.c r_sub_scalar.c
 CSRCS   += sub2.c add2.c
 ROOTDEPPATH += --dep-path $(SRCDIR)/functions/implements/arithmetic
@@ -92,11 +92,11 @@ CSRCS   += pooling.c max_pooling.c sum_pooling.c average_pooling.c unpooling.c d
 ROOTDEPPATH += --dep-path $(SRCDIR)/functions/implements/neural_network
 VPATH   += $(SRCDIR)/functions/implements/neural_network
 
-CSRCS   += affine.c affine_generic.c
+CSRCS   += affine.c affine_fixed8.c affine_fixed16.c affine_generic.c
 ROOTDEPPATH += --dep-path $(SRCDIR)/functions/implements/neural_network/affine
 VPATH   += $(SRCDIR)/functions/implements/neural_network/affine
 
-CSRCS   += convolution.c convolution_generic.c convolution_float.c convolution_common.c
+CSRCS   += convolution.c convolution_generic.c convolution_float.c convolution_int8.c convolution_int16.c convolution_common.c
 CSRCS   += binary_connect_convolution.c binary_weight_convolution.c depthwise_convolution.c
 ROOTDEPPATH += --dep-path $(SRCDIR)/functions/implements/neural_network/convolution
 VPATH   += $(SRCDIR)/functions/implements/neural_network/convolution
diff --git a/externals/nnablart/nnabla-c-runtime b/externals/nnablart/nnabla-c-runtime
index c58c11dd..a5fb10ea 160000
--- a/externals/nnablart/nnabla-c-runtime
+++ b/externals/nnablart/nnabla-c-runtime
@@ -1 +1 @@
-Subproject commit c58c11ddd182e8ed04eb931bbf2a82f190874c9d
+Subproject commit a5fb10ea5f2e4915fc68823500d4308ab98eb473

                Please let me know if it worked for you.

                Best Regards,
                Kamil Tomaszewski

                N 1 Reply Last reply Reply Quote
                • N
                  niciBume @KamilTomaszewski last edited by

                  @kamiltomaszewski unfortunatelly it can't compile anymore. I'll dump the error:

                  /home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add_scalar.o): In function `exec_add_scalar_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add_scalar.c:80: undefined reference to `calc_scalar_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add_scalar.o): In function `saturate32_to_16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:93: undefined reference to `calc_add_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add_scalar.o): In function `exec_add_scalar_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add_scalar.c:91: undefined reference to `calc_scalar_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add_scalar.o): In function `saturate16_to_8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:71: undefined reference to `calc_add_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(div2.o): In function `exec_div2_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/div2.c:88: undefined reference to `calc_arithmetic_fixed8_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/div2.c:91: undefined reference to `calc_div_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(div2.o): In function `exec_div2_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/div2.c:99: undefined reference to `calc_arithmetic_fixed16_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/div2.c:102: undefined reference to `calc_div_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(mul2.o): In function `exec_mul2_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul2.c:96: undefined reference to `calc_arithmetic_fixed8_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul2.c:99: undefined reference to `calc_mul_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(mul2.o): In function `exec_mul2_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul2.c:107: undefined reference to `calc_arithmetic_fixed16_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul2.c:110: undefined reference to `calc_mul_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(mul_scalar.o): In function `exec_mul_scalar_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul_scalar.c:85: undefined reference to `calc_scalar_fixed8_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul_scalar.c:87: undefined reference to `calc_mul_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(mul_scalar.o): In function `exec_mul_scalar_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul_scalar.c:94: undefined reference to `calc_scalar_fixed16_largebuff'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/mul_scalar.c:96: undefined reference to `calc_mul_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(sub2.o): In function `exec_sub2_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/sub2.c:86: undefined reference to `equalize_bits_fixed16'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/sub2.c:87: undefined reference to `calc_arithmetic_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(sub2.o): In function `saturate32_to_16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:93: undefined reference to `calc_sub_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(sub2.o): In function `exec_sub2_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/sub2.c:96: undefined reference to `equalize_bits_fixed8'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/sub2.c:97: undefined reference to `calc_arithmetic_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(sub2.o): In function `saturate16_to_8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:71: undefined reference to `calc_sub_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add2.o): In function `exec_add2_fixed16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add2.c:87: undefined reference to `equalize_bits_fixed16'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add2.c:88: undefined reference to `calc_arithmetic_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add2.o): In function `saturate32_to_16':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:93: undefined reference to `calc_add_fixed16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add2.o): In function `exec_add2_fixed8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add2.c:97: undefined reference to `equalize_bits_fixed8'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/add2.c:98: undefined reference to `calc_arithmetic_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(add2.o): In function `saturate16_to_8':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/arithmetic/../../utilities/fixedpoint.h:71: undefined reference to `calc_add_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(affine.o): In function `allocate_affine_local_context':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/affine/affine.c:111: undefined reference to `exec_affine_fixed16'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/affine/affine.c:111: undefined reference to `exec_affine_fixed8'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(convolution.o): In function `allocate_convolution_local_context':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/convolution.c:40: undefined reference to `exec_convolution_int8'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/convolution.c:40: undefined reference to `exec_convolution_int16'
/home/nicolas/spresense/nuttx/../externals/nnablart/libnnablart.a(depthwise_convolution.o): In function `allocate_depthwise_convolution_local_context':
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/depthwise_convolution.c:160: undefined reference to `exec_convolution_int16'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/depthwise_convolution.c:160: undefined reference to `exec_convolution_int8'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/depthwise_convolution.c:53: undefined reference to `exec_convolution_int8'
/home/nicolas/spresense/externals/nnablart/nnabla-c-runtime/src/functions/implements/neural_network/convolution/depthwise_convolution.c:53: undefined reference to `exec_convolution_int16'
make[2]: *** [Makefile:185: nuttx] Error 1
make[2]: Leaving directory '/home/nicolas/spresense/nuttx/arch/arm/src'
make[1]: *** [tools/Makefile.unix:464: pass2] Error 2
make[1]: Leaving directory '/home/nicolas/spresense/nuttx'
make: *** [Makefile:99: all] Error 2

                  However, I want to inform you that the urgency of this problem is not too high (at least on my side) ^^
                  As my team and I are pursuing a different workaround altogether.

                  Best,
                  Nic

                  K 1 Reply Last reply Reply Quote
                  • K
                    KamilTomaszewski DeveloperWorld @niciBume last edited by

                    @niciBume You get these errors because you didn't make the changes I showed in step 2 to the spresense/externals/nnablart/Makefile.

                    This adds missing files to the Makefile that were added in the new version of the NNabla C Runtime library.

                    You can use the code from step 2 as .patch and apply it to your Spresense SDK repository.

                    Best Regards,
                    Kamil Tomaszewski

                    N 1 Reply Last reply Reply Quote
                    • N
                      niciBume @KamilTomaszewski last edited by

                      @kamiltomaszewski oh, my bad. I misinterpreted step 2. Applied the patch and it compiles once again. During inference however, the error is again the same as in:

                      @nicibume said in How to convert from pytorch to nnb for spresense?:

                      Hi @kamiltomaszewski thanks for the reply!

                      The output of the dnnrt_lenet example is the following:

                      nsh> dnnrt_lenet --s /mnt/sd0/sony_nabla.nnb
Load nnb file: /mnt/sd0/sony_nabla.nnb
Load pgm image: /mnt/sd0/0.pgm
Image Normalization (1.0/255.0): skipped
start dnn_runtime_forward()
up_hardfault: PANIC!!! Hard fault: 40000000
up_assert: Assertion failed at file:armv7-m/up_hardfault.c line: 148 task: sony_uav
up_registerdump: R0: 0d0f6e54 0d09969c 0d099918 00000000 00000015 0d04b770 0d03d6b0 0d04b6e0
up_registerdump: R8: 00000003 00000000 00000000 00000000 00000009 0d04b6b0 0d024ae5 00000000
up_registerdump: xPSR: 00000000 BASEPRI: 000000e0 CONTROL: 00000000
up_registerdump: EXC_RETURN: ffffffe9
up_dumpstate: sp:     0d03aba8
up_dumpstate: IRQ stack:
up_dumpstate:   base: 0d03ac00
up_dumpstate:   size: 00000800
up_dumpstate:   used: 00000148
up_stackdump: 0d03aba0: 000007c4 0d00257b 000000e0 00000000 00000000 00000009 0d04b6b0 0d024ae5
up_stackdump: 0d03abc0: 00000000 0d03abd0 0d001a9f 00000003 00000000 0d001aa7 0d001a85 0d00354f
up_stackdump: 0d03abe0: 000000e0 0d001a79 000000e0 0d04b5dc 0d04b770 0d03d6b0 0d04b6e0 0d000333
up_dumpstate: sp:     0d04b6b0
up_dumpstate: User stack:
up_dumpstate:   base: 0d04b720
up_dumpstate:   size: 000007c4
up_dumpstate:   used: 00000628
up_stackdump: 0d04b6a0: 00000000 80000000 80000010 0d024ae5 0d0f69a0 0d0f6900 0d04b770 0d020b7d
up_stackdump: 0d04b6c0: 00015419 00000000 0d04ba00 0d03d6b0 00000001 0d020899 00000000 00000001
up_stackdump: 0d04b6e0: 0d03d6b0 0d04b770 00000249 00015419 00000000 00000000 00000000 00000101
up_stackdump: 0d04b700: 00000000 00000000 00000000 00000000 00000000 0d004377 00000000 00000000
up_taskdump: Idle Task: PID=0 Stack Used=0 of 0
up_taskdump: hpwork: PID=1 Stack Used=576 of 2028
up_taskdump: lpwork: PID=2 Stack Used=352 of 2028
up_taskdump: lpwork: PID=3 Stack Used=352 of 2028
up_taskdump: lpwork: PID=4 Stack Used=352 of 2028
up_taskdump: cxd56_pm_task: PID=6 Stack Used=352 of 996
up_taskdump: init: PID=7 Stack Used=1008 of 8172
up_taskdump: sony_uav: PID=16 Stack Used=1576 of 1988

                      This seems to be a nuttX error message, if I am not mistaking?

                      It actually passes dnn_runtime_initialize but fails at dnn_runtime_forward(), where I trace it back to https://github.com/sonydevworld/spresense/blob/87f81d9c35c7d05d6a75e9177b45d6cbe8d8c063/sdk/modules/dnnrt/src/runtime/runtime_nnabla.c#L186

                      Regarding the conversion, I tied your suggestion, yet with the same result. Would you know the build commands for the NNC?

                      Best,

                      Nic

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                      • K
                        KamilTomaszewski DeveloperWorld @niciBume last edited by

                        @nicibume Could you please modify the spresense/externals/nnablart/nnabla-c-runtime/src/runtime/runtime.c file as shown below?

                        diff --git a/src/runtime/runtime.c b/src/runtime/runtime.c
index 6236510..2b45247 100644
--- a/src/runtime/runtime.c
+++ b/src/runtime/runtime.c
@@ -375,6 +375,9 @@ rt_return_value_t rt_forward(rt_context_pointer context) {
   rt_context_t *c = context;
 
   for (i = 0; i < c->num_of_functions; i++) {
+    printf("c->functions[i].func.exec_func %p\n", c->functions[i].func.exec_func);
+    printf("c->functions[i].info->type %d\n", c->functions[i].info->type);
+    usleep(1000);
     ret = c->functions[i].func.exec_func(&(c->functions[i].func));
     if (ret != RT_FUNCTION_ERROR_NOERROR) {
       switch (ret) {

                        This adds 2 extra logs. Please send me an output from your serial console after making the change.

                        Best Regards,
                        Kamil Tomaszewski

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                        • N
                          niciBume @KamilTomaszewski last edited by

                          @kamiltomaszewski sorry for the late response, I must have missed the notification. I inserted your prints:

                          nsh> sony_uav /mnt/sd0/sony_nabla.nnb
Load nnb file: /mnt/sd0/sony_nabla.nnb
Load pgm image: /mnt/sd0/0.pgm
Image Normalization (1.0/255.0): enabled
INIT SUCCSESS!!!
start dnn_runtime_forward()
c->functions[i].func.exec_func 0xd02ff21
c->functions[i].info->type 126
c->functions[i].func.exec_func 0xd02ff21
c->functions[i].info->type 126
c->functions[i].func.exec_func 0xd0256cd
c->functions[i].info->type 265
up_hardfault: PANIC!!! Hard fault: 40000000
up_assert: Assertion failed at file:armv7-m/up_hardfault.c line: 148 task: sony_uav
up_registerdump: R0: 0d103114 6c46694f 0d10aa14 0d000305 1e8005f3 00000004 0d103114 0d045674
up_registerdump: R8: 0d045650 00000000 00000000 00000000 00008000 0d057b90 0d0256fd 0d025718
up_registerdump: xPSR: 21000000 BASEPRI: 000000e0 CONTROL: 00000000
up_registerdump: EXC_RETURN: ffffffe9
up_dumpstate: sp:     0d046ba8
up_dumpstate: IRQ stack:
up_dumpstate:   base: 0d046c00
up_dumpstate:   size: 00000800
up_dumpstate:   used: 00000148
up_stackdump: 0d046ba0: 000007cc 0d0027db 000000e0 00000000 00000000 00008000 0d057b90 0d0256fd
up_stackdump: 0d046bc0: 0d025718 0d046bd0 0d001c67 00000003 00000000 0d001c6f 0d001c4d 0d0037af
up_stackdump: 0d046be0: 000000e0 0d001c41 000000e0 0d057abc 00000004 0d103114 0d045674 0d000333
up_dumpstate: sp:     0d057b90
up_dumpstate: User stack:
up_dumpstate:   base: 0d057cb8
up_dumpstate:   size: 000007cc
up_dumpstate:   used: 00000620
up_stackdump: 0d057b80: 00000000 00000000 00000000 0d102a74 00000000 00000000 00000000 00000000
up_stackdump: 0d057ba0: 00000000 00000000 00000014 0d050430 00000000 0d0057e3 0d050430 0a050730
up_stackdump: 0d057bc0: 0d050970 00000000 35323635 0d057c38 000000e0 0d057c38 00000000 0d04a840
up_stackdump: 0d057be0: 00000e18 00000000 00000000 0d00591f 00000000 0000000f 0d057c38 0d057c38
up_stackdump: 0d057c00: 00000002 00000000 0d045674 0d045650 00000000 0d0059c9 00000000 00000000
up_stackdump: 0d057c20: 0d057c38 0d0b54d0 00000002 00000040 0d045674 0d045650 00000000 00000000
up_stackdump: 0d057c40: 00000000 0d02af61 0d103100 0d0b54d0 0d0496d8 0d057c80 00000002 0d024cad
up_stackdump: 0d057c60: 00038553 00000000 0d0496d8 0d0b5760 00000000 0d024965 00000000 00000001
up_stackdump: 0d057c80: 0d0496d8 0d0b54d0 00000025 00038553 00000000 00000000 00000101 00000000
up_stackdump: 0d057ca0: 00000000 00000000 00000000 0d0045db 00000000 00000000 deadbeef 0d057cc8
up_taskdump: Idle Task: PID=0 Stack Used=0 of 0
up_taskdump: hpwork: PID=1 Stack Used=576 of 2028
up_taskdump: lpwork: PID=2 Stack Used=352 of 2028
up_taskdump: lpwork: PID=3 Stack Used=352 of 2028
up_taskdump: lpwork: PID=4 Stack Used=352 of 2028
up_taskdump: cxd56_pm_task: PID=6 Stack Used=352 of 996
up_taskdump: init: PID=7 Stack Used=1056 of 8172
up_taskdump: sony_uav: PID=9 Stack Used=1568 of 1996

                          To compare, this is the output of a NNC exported .nnb:

                          nsh> sony_uav
Load nnb file: /mnt/sd0/lenet-5.nnb
Load pgm image: /mnt/sd0/0.pgm
Image Normalization (1.0/255.0): enabled
INIT SUCCSESS!!!
start dnn_runtime_forward()
c->functions[i].func.exec_func 0xd0256cd
c->functions[i].info->type 1
c->functions[i].func.exec_func 0xd02b285
c->functions[i].info->type 14
c->functions[i].func.exec_func 0xd031aed
c->functions[i].info->type 5
c->functions[i].func.exec_func 0xd0256cd
c->functions[i].info->type 1
c->functions[i].func.exec_func 0xd031aed
c->functions[i].info->type 5
c->functions[i].func.exec_func 0xd02b575
c->functions[i].info->type 13
c->functions[i].func.exec_func 0xd025141
c->functions[i].info->type 0
c->functions[i].func.exec_func 0xd02b285
c->functions[i].info->type 14
c->functions[i].func.exec_func 0xd025141
c->functions[i].info->type 0
c->functions[i].func.exec_func 0xd02b679
c->functions[i].info->type 16
Done with forward! 
output[0]=0.999999
output[1]=0.000000
output[2]=0.000000
output[3]=0.000000
output[4]=0.000000
output[5]=0.000000
output[6]=0.000000
output[7]=0.000000
output[8]=0.000000
output[9]=0.000001
inference time=0.272

                          Best,
                          Nic

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                          • K
                            KamilTomaszewski DeveloperWorld @niciBume last edited by

                            @nicibume Could you please share this model (sony_nabla.nnb) with me?

                            My e-mail address: kamil.tomaszewski@sony.com

                            Best Regards,
                            Kamil Tomaszewski

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