124073 - rpi5 aidge – dAIEdge-VLab Status

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rpi5

0000019c71638acf37948e8933e2246c7ee24eb06307d06986d991b6e014d767

aidge

124073 - rpi5 aidge

✅

Summary: Pipeline failed, but error.log is filled.

Model Details

model name : mnist-12-int8.onnx
model url : Download here

Logs Details

user.log

MODEL : mnist12int8.onnx

===============
ONNX Graph
===============

Input3 [1, 1, 28, 28]

===============
Aidge Graph
===============

  Node(name='Parameter194_scale', optype='Producer', children: [[1]])
  Node(name='Convolution110_DequantizeLinear_0', optype='Dequantizer', parents: [1], children: [[1]])
  Node(name='Convolution110_quant', optype='QLinearConv', parents: [1, 1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Convolution28_quant', optype='QLinearConv', parents: [1, 1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Parameter194_quantized', optype='Producer', children: [[1]])
  Node(name='Pooling66_quant', optype='MaxPooling2D', parents: [1], children: [[1], []])
  Node(name='Plus214_Output_0_zero_point', optype='Producer', children: [[1]])
  Node(name='Parameter193_reshape1_zero_point', optype='Producer', children: [[1]])
  Node(name='Times212_reshape0', optype='Reshape', parents: [1, 1], children: [[1]])
  Node(name='Convolution28_scale', optype='Producer', children: [[1]])
  Node(name='gemm_Add_quant', optype='QLinearAdd', parents: [1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Parameter5_scale', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_scale', optype='Producer', children: [[1]])
  Node(name='Parameter5_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter87_scale', optype='Producer', children: [[1]])
  Node(name='gemm_MatMul_quant', optype='QLinearMatMul', parents: [1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_shape', optype='Producer', children: [[1]])
  Node(name='Parameter193_reshape1_quantized', optype='Producer', children: [[1]])
  Node(name='ConvAddFusion_Add_B_Parameter6_quantized', optype='Producer', children: [[1]])
  Node(name='Input3_scale', optype='Producer', children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_zero_point', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_MatMul_scale', optype='Producer', children: [[1, 1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear', optype='Quantizer', parents: [1], children: [[1]])
  Node(name='Input3_zero_point', optype='Producer', children: [[1]])
  Node(name='Convolution110_zero_point', optype='Producer', children: [[1]])
  Node(name='Parameter87_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter193_reshape1_scale', optype='Producer', children: [[1]])
  Node(name='Convolution110_scale', optype='Producer', children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_scale', optype='Producer', children: [[1]])
  Node(name='Pooling66_Output_0_zero_point', optype='Producer', children: [[1]])
  Node(name='Parameter194_zero_point', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_MatMul_zero_point', optype='Producer', children: [[1, 1]])
  Node(name='Pooling66_Output_0_scale', optype='Producer', children: [[1]])
  Node(name='Parameter87_zero_point', optype='Producer', children: [[1]])
  Node(name='ConvAddFusion_Add_B_Parameter88_quantized', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_DequantizeLinear_0', optype='Dequantizer', parents: [1], children: [[]])
  Node(name='Pooling160', optype='MaxPooling2D', parents: [1], children: [[1], []])
  Node(name='Input3_Convolution28_QuantizeLinear', optype='Quantizer', parents: [0], children: [[1]])
  Node(name='Convolution28_zero_point', optype='Producer', children: [[1]])
  Node(name='Parameter5_zero_point', optype='Producer', children: [[1]])

===============
Supported nodes
===============

Native operators: 36 (5 types)
- Dequantizer: 2
- MaxPooling2D: 2
- Producer: 29
- Quantizer: 2
- Reshape: 1
Generic operators: 4 (3 types)
- QLinearAdd: 1
- QLinearConv: 2
- QLinearMatMul: 1
Native types coverage: 62.5% (5/8)
Native operators coverage: 90.0% (36/40)
  (defaultdict(<class 'int'>, {'Producer': 29, 'Reshape': 1, 'Quantizer': 2, 'Dequantizer': 2, 'MaxPooling2D': 2}), defaultdict(<class 'int'>, {'QLinearAdd': 1, 'QLinearMatMul': 1, 'QLinearConv': 2}))

===============\Graph manipulation
===============

Remove flatten
Fuse batchnorm
Expand metaop
Fuse to metaop

===============
New Aidge Graph
===============

  Node(name='Convolution110_DequantizeLinear_0_MulDeQuant', optype='Mul', parents: [1, 1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuant', optype='Clip', parents: [1, 1, 1], children: [[1]])
  Node(name='Pooling66_Output_0_zero_point', optype='Producer', children: [[1]])
  Node(name='Convolution110_DequantizeLinear_0_SubDeQuant', optype='Sub', parents: [1, 1], children: [[1]])
  Node(name='ConvAddFusion_Add_B_Parameter6_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter5_scale', optype='Producer', children: [[1]])
  Node(name='Convolution110_DequantizeLinear_0_CastIn', optype='Cast', parents: [1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuantMin', optype='Producer', children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_shape', optype='Producer', children: [[1]])
  Node(name='Convolution28_quant', optype='QLinearConv', parents: [1, 1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Pooling160', optype='MaxPooling2D', parents: [1], children: [[1], []])
  Node(name='Input3_zero_point', optype='Producer', children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_zero_point', optype='Producer', children: [[1]])
  Node(name='Pooling66_quant', optype='MaxPooling2D', parents: [1], children: [[1], []])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_CastOut', optype='Cast', parents: [1], children: [[1]])
  Node(name='Convolution110_quant', optype='QLinearConv', parents: [1, 1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='gemm_MatMul_quant', optype='QLinearMatMul', parents: [1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Plus214_Output_0_scale', optype='Producer', children: [[1]])
  Node(name='ZeroPoint_1', optype='Producer', children: [[1]])
  Node(name='Parameter193_reshape1_zero_point', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_CastIn', optype='Cast', parents: [0], children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_CastOut', optype='Cast', parents: [1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_RoundQuant', optype='Round', parents: [1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuantMax', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_RoundQuant', optype='Round', parents: [1], children: [[1]])
  Node(name='ZeroPoint_2', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_ClipQuantMin', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_ClipQuantMax', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_DequantizeLinear_0_MulDeQuant', optype='Mul', parents: [1, 1], children: [[]])
  Node(name='Parameter193_reshape1_quantized', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_ClipQuant', optype='Clip', parents: [1, 1, 1], children: [[1]])
  Node(name='ZeroPoint', optype='Producer', children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_scale', optype='Producer', children: [[1]])
  Node(name='Parameter194_zero_point', optype='Producer', children: [[1]])
  Node(name='ZeroPoint', optype='Producer', children: [[1]])
  Node(name='ScalingFactor', optype='Producer', children: [[1]])
  Node(name='Pooling66_Output_0_scale', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_DequantizeLinear_0_SubDeQuant', optype='Sub', parents: [1, 1], children: [[1]])
  Node(name='Input3_scale', optype='Producer', children: [[1]])
  Node(name='Input3_Convolution28_QuantizeLinear_AddQuant', optype='Add', parents: [1, 1], children: [[1]])
  Node(name='gemm_Add_quant', optype='QLinearAdd', parents: [1, 1, 1, 1, 1, 1, 1, 1], children: [[1]])
  Node(name='Plus214_Output_0_zero_point', optype='Producer', children: [[1]])
  [[33mWARNING[0m] - Aidge currently only supports layerwise scaling and not channelwise for
[[33mWARNING[0m]   QLinearConv[Weight DequantizeLinear] node. This node will be filled by a
[[33mWARNING[0m]   GenericOperator.
[[94mNOTICE[0m] - Loaded node [[1m[3mConvolution28_quant[0m] of type [[1m[3mQLinearConv[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* auto_pad : b'SAME_UPPER'
[[94mNOTICE[0m]   	* dilations : [1, 1]
[[94mNOTICE[0m]   	* group : 1
[[94mNOTICE[0m]   	* kernel_shape : [5, 5]
[[94mNOTICE[0m]   	* strides : [1, 1]
[[33mWARNING[0m] - Aidge currently only supports layerwise scaling and not channelwise for
[[33mWARNING[0m]   QLinearConv[Weight DequantizeLinear] node. This node will be filled by a
[[33mWARNING[0m]   GenericOperator.
[[94mNOTICE[0m] - Loaded node [[1m[3mConvolution110_quant[0m] of type [[1m[3mQLinearConv[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* auto_pad : b'SAME_UPPER'
[[94mNOTICE[0m]   	* dilations : [1, 1]
[[94mNOTICE[0m]   	* group : 1
[[94mNOTICE[0m]   	* kernel_shape : [5, 5]
[[94mNOTICE[0m]   	* strides : [1, 1]
[[33mWARNING[0m] - Aidge currently only supports layerwise scaling and not channelwise for
[[33mWARNING[0m]   QLinearMatMul[Weight DequantizeLinear] node. This node will be filled by a
[[33mWARNING[0m]   GenericOperator.
[[94mNOTICE[0m] - Loaded node [[1m[3mgemm_MatMul_quant[0m] of type [[1m[3mQLinearMatMul[0m] as a GenericOperator.
[[94mNOTICE[0m] - Loaded node [[1m[3mgemm_Add_quant[0m] of type [[1m[3mQLinearAdd[0m] as a GenericOperator.
[[94mNOTICE[0m] - Node name "ZeroPoint" is a duplicate, renaming it to ZeroPoint_1.
[[94mNOTICE[0m] - Node name "ScalingFactor" is a duplicate, renaming it to ScalingFactor_1.
[[94mNOTICE[0m] - Node name "ZeroPoint" is a duplicate, renaming it to ZeroPoint_2.
[[94mNOTICE[0m] - Node name "ScalingFactor" is a duplicate, renaming it to ScalingFactor_2.
[[33mWARNING[0m] - GenericOperator::setBackend(): cannot set backend for a generic operator, as no
[[33mWARNING[0m]   implementation has been provided!
[[33mWARNING[0m] - GenericOperator::setBackend(): cannot set backend for a generic operator, as no
[[33mWARNING[0m]   implementation has been provided!
[[33mWARNING[0m] - GenericOperator::setBackend(): cannot set backend for a generic operator, as no
[[33mWARNING[0m]   implementation has been provided!
[[33mWARNING[0m] - GenericOperator::setBackend(): cannot set backend for a generic operator, as no
[[33mWARNING[0m]   implementation has been provided!
[[31mERROR[0m] - Unable to forward data type for node Convolution28_quant (of type QLinearConv)
[[31mERROR[0m] - Unable to forward data type for node Convolution28_quant (of type QLinearConv)
[[31mERROR[0m] - Unable to forward data type for node Convolution28_quant (of type QLinearConv)
[[33mWARNING[0m] - Unable to forward data type (circular dependency and/or wrong dimensions and/or data
[[33mWARNING[0m]   dependent dimension?). Unable to compute output data type for nodes
[[33mWARNING[0m]   ["Convolution110_quant (QLinearConv)", "Convolution28_quant (QLinearConv)",
[[33mWARNING[0m]   "Convolution110_DequantizeLinear_0_MulDeQuant (Mul)",
[[33mWARNING[0m]   "Convolution110_DequantizeLinear_0_SubDeQuant (Sub)", "Times212_reshape0 (Reshape)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_MulQuant (Mul)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_AddQuant (Add)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuant (Clip)",
[[33mWARNING[0m]   "gemm_MatMul_quant (QLinearMatMul)", "gemm_Add_quant (QLinearAdd)",
[[33mWARNING[0m]   "Plus214_Output_0_DequantizeLinear_0_MulDeQuant (Mul)",
[[33mWARNING[0m]   "Plus214_Output_0_DequantizeLinear_0_SubDeQuant (Sub)"].
[[33mWARNING[0m] - GenericOperator: cannot compute output dims, no ComputeDimsFunc function provided.
[[33mWARNING[0m] - GenericOperator: cannot compute output dims, no ComputeDimsFunc function provided.
[[33mWARNING[0m] - GenericOpNode(name='ScalingFactor', optype='Producer', children: [[1]])
  Node(name='Times212_reshape0', optype='Reshape', parents: [1, 1], children: [[1]])
  Node(name='ScalingFactor_2', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_MatMul_scale', optype='Producer', children: [[1, 1]])
  Node(name='Input3_Convolution28_QuantizeLinear_MulQuant', optype='Mul', parents: [1, 1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_MulQuant', optype='Mul', parents: [1, 1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_CastIn', optype='Cast', parents: [1], children: [[1]])
  Node(name='Parameter194_scale', optype='Producer', children: [[1]])
  Node(name='Convolution110_scale', optype='Producer', children: [[1]])
  Node(name='ConvAddFusion_Add_B_Parameter88_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter194_quantized', optype='Producer', children: [[1]])
  Node(name='Convolution110_zero_point', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_DequantizeLinear_0_CastIn', optype='Cast', parents: [1], children: [[1]])
  Node(name='Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_AddQuant', optype='Add', parents: [1, 1], children: [[1]])
  Node(name='Parameter5_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter87_quantized', optype='Producer', children: [[1]])
  Node(name='Parameter87_zero_point', optype='Producer', children: [[1]])
  Node(name='Parameter193_reshape1_scale', optype='Producer', children: [[1]])
  Node(name='ScalingFactor_1', optype='Producer', children: [[1]])
  Node(name='Convolution28_scale', optype='Producer', children: [[1]])
  Node(name='Parameter87_scale', optype='Producer', children: [[1]])
  Node(name='Convolution28_zero_point', optype='Producer', children: [[1]])
  Node(name='Plus214_Output_0_MatMul_zero_point', optype='Producer', children: [[1, 1]])
  Node(name='Parameter5_zero_point', optype='Producer', children: [[1]])

===============
Supported nodes 2
===============

Native operators: 62 (9 types)
- Add: 2
- Cast: 6
- Clip: 2
- MaxPooling2D: 2
- Mul: 4
- Producer: 41
- Reshape: 1
- Round: 2
- Sub: 2
Generic operators: 4 (3 types)
- QLinearAdd: 1
- QLinearConv: 2
- QLinearMatMul: 1
Native types coverage: 75.0% (9/12)
Native operators coverage: 93.9% (62/66)
  (defaultdict(<class 'int'>, {'Producer': 41, 'Sub': 2, 'Round': 2, 'Add': 2, 'Cast': 6, 'Mul': 4, 'Clip': 2, 'Reshape': 1, 'MaxPooling2D': 2}), defaultdict(<class 'int'>, {'QLinearMatMul': 1, 'QLinearConv': 2, 'QLinearAdd': 1}))

===============
Supported nodes
===============

Native operators: 62 (9 types)
- Add: 2
- Cast: 6
- Clip: 2
- MaxPooling2D: 2
- Mul: 4
- Producer: 41
- Reshape: 1
- Round: 2
- Sub: 2
Generic operators: 4 (3 types)
- QLinearAdd: 1
- QLinearConv: 2
- QLinearMatMul: 1
Native types coverage: 75.0% (9/12)
Native operators coverage: 93.9% (62/66)
  (defaultdict(<class 'int'>, {'Cast': 6, 'Producer': 41, 'Clip': 2, 'Add': 2, 'Sub': 2, 'Mul': 4, 'Round': 2, 'Reshape': 1, 'MaxPooling2D': 2}), defaultdict(<class 'int'>, {'QLinearAdd': 1, 'QLinearMatMul': 1, 'QLinearConv': 2}))

===============
Compile
===============

OK

===============
Create Scheduler
===============

OK

===============
Name nodes
===============

Pooling160_Output_0_reshape0_scale (Producer)
Plus214_Output_0_MatMul_scale (Producer)
Parameter193_reshape1_quantized (Producer)
Plus214_Output_0_scale (Producer)
Parameter194_quantized (Producer)
Parameter194_scale (Producer)
Parameter194_zero_point (Producer)
Input3_zero_point (Producer)
Input3_scale (Producer)
Parameter5_quantized (Producer)
Plus214_Output_0_zero_point (Producer)
Parameter193_reshape1_zero_point (Producer)
Plus214_Output_0_MatMul_zero_point (Producer)
Parameter193_reshape1_scale (Producer)
Pooling160_Output_0_reshape0_zero_point (Producer)
Pooling160_Output_0_reshape0_shape (Producer)
Parameter5_scale (Producer)
Parameter5_zero_point (Producer)
Convolution28_zero_point (Producer)
Convolution28_scale (Producer)
ConvAddFusion_Add_B_Parameter6_quantized (Producer)
Pooling66_Output_0_zero_point (Producer)
Pooling66_Output_0_scale (Producer)
Parameter87_scale (Producer)
Parameter87_quantized (Producer)
Parameter87_zero_point (Producer)
Convolution110_zero_point (Producer)
Convolution110_scale (Producer)
ConvAddFusion_Add_B_Parameter88_quantized (Producer)
ScalingFactor (Producer)
ZeroPoint (Producer)
Input3_Convolution28_QuantizeLinear_ClipQuantMin (Producer)
Input3_Convolution28_QuantizeLinear_ClipQuantMax (Producer)
ZeroPoint_1 (Producer)
ScalingFactor_1 (Producer)
ScalingFactor (Producer)
ZeroPoint (Producer)
Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuantMin (Producer)
Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuantMax (Producer)
ZeroPoint_2 (Producer)
ScalingFactor_2 (Producer)
_Cast_0 (Cast)
_Mul_0 (Mul)
_Round_0 (Round)
_Add_0 (Add)
_Clip_0 (Clip)
_Cast_1 (Cast)
_QLinearConv_0 (QLinearConv)
_MaxPooling2D_0 (MaxPooling2D)
_QLinearConv_1 (QLinearConv)
_Cast_2 (Cast)
_Sub_0 (Sub)
_Mul_1 (Mul)
_MaxPooling2D_1 (MaxPooling2D)
_Reshape_0 (Reshape)
_Cast_3 (Cast)
_Mul_2 (Mul)
_Round_1 (Round)
_Add_1 (Add)
_Clip_1 (Clip)
_Cast_4 (Cast)
_QLinearMatMul_0 (QLinearMatMul)
_QLinearAdd_0 (QLinearAdd)
_Cast_5 (Cast)
_Sub_1 (Sub)
_Mul_3 (Mul)

===============
Set backend
===============

erator: cannot compute output dims, no ComputeDimsFunc function provided.
[[33mWARNING[0m] - Unable to forward dimensions (circular dependency and/or wrong dimensions and/or data
[[33mWARNING[0m]   dependent dimension?). Unable to compute output dims for nodes ["Convolution110_quant
[[33mWARNING[0m]   (QLinearConv)", "Convolution28_quant (QLinearConv)",
[[33mWARNING[0m]   "Convolution110_DequantizeLinear_0_MulDeQuant (Mul)",
[[33mWARNING[0m]   "Convolution110_DequantizeLinear_0_SubDeQuant (Sub)", "Times212_reshape0 (Reshape)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_MulQuant (Mul)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_AddQuant (Add)",
[[33mWARNING[0m]   "Pooling160_Output_0_reshape0_gemm_MatMul_QuantizeLinear_ClipQuant (Clip)",
[[33mWARNING[0m]   "gemm_MatMul_quant (QLinearMatMul)", "gemm_Add_quant (QLinearAdd)",
[[33mWARNING[0m]   "Plus214_Output_0_DequantizeLinear_0_MulDeQuant (Mul)",
[[33mWARNING[0m]   "Plus214_Output_0_DequantizeLinear_0_SubDeQuant (Sub)"].
[[31mERROR[0m] - Assertion failed: exists(key) in /opt/aidge/aidge/aidge_core/include/aidge/utils/Registrar.hpp:87
[[95mFATAL[0m] - missing or invalid registrar key: "export_cpp" for registrable object N5Aidge8Round_OpE
[[95mFATAL[0m]   Did you include/import the corresponding module?
[[95mFATAL[0m]   If so, it is possible that the object is not yet supported.
[[95mFATAL[0m]   
[[95mFATAL[0m]   Available registrar keys are:
[[95mFATAL[0m]       cpu
Traceback (most recent call last):
  File "/app/AI_Project/01_generate_cpp.py", line 115, in <module>
    model_aidge.set_backend(aidge_export_cpp.ExportLibCpp._name)
RuntimeError: missing or invalid registrar key: "export_cpp" for registrable object N5Aidge8Round_OpE
Did you include/import the corresponding module?
If so, it is possible that the object is not yet supported.

Available registrar keys are:
    cpu
Error: export_model/data directory does not exist.

error.log

sed: can't read export_model/Makefile: No such file or directory
sed: can't read export_model/Makefile: No such file or directory
sed: can't read export_model/Makefile: No such file or directory
sed: can't read export_model/Makefile: No such file or directory
./AI_Project/03_build.sh: line 17: cd: export_model: No such file or directory
make: AI_Build AI_Deploy AI_Manager AI_Project AI_Support ConvNet.onnx MLP_MNIST.onnx MobileNet-v2.onnx README.md __pycache__ config.json docker examples exit_functions.sh mnist.onnx mnist12int8.onnx mnist_test_input_type2.bin model_1D_classifier.onnx model_type2.onnx print_raw_output.py type1_test.sh type2_test.sh type3_test.sh No targets specified and no makefile found. Stop.

Report Details

report.json

null

124072 - rpi5 aidge 124074 - rpi5 aidge