123874 - rpi4b aidge – dAIEdge-VLab Status

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rpi4b

0000019c716353c48a919c2708c2e96740c0117e3b39e93019ec189e217f7302

aidge

123874 - rpi4b aidge

✅

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

Model Details

model name : udnie-8.onnx
model url : Download here

Logs Details

user.log

[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_63[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 4, 4, 0, 0, 4, 4]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_67[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_71[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_75[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_79[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_83[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_87[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_91[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_95[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_99[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_103[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_107[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_111[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_115[0m] of type [[1m[3mUpsample[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'nearest'
[[94mNOTICE[0m]   	* scales : [1.0, 1.0, 2.0, 2.0]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for oMODEL : udnie8.onnx

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

Number of input = 63 is not supported (max 1)
input1 [1, 3, 224, 224]

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

  Node(name='data_79', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_100', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res4_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_74', optype='ReLU', parents: [1], children: [[1, 1]])
  Node(name='res1_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_77', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res5_in2_bias', optype='Producer', children: [[1]])
  Node(name='res1_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_101', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res3_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res4_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_102', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_73', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_86', optype='ReLU', parents: [1], children: [[1]])
  Node(name='res2_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res3_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_67', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_71', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_90', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='data_103', optype='Pad', parents: [1], children: [[1]])
  Node(name='in4_bias', optype='Producer', children: [[1]])
  Node(name='res3_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_85', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res2_in2_weight', optype='Producer', children: [[1]])
  Node(name='data_84', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res2_in2_bias', optype='Producer', children: [[1]])
  Node(name='data_96', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res4_in1_weight', optype='Producer', children: [[1]])
  Node(name='res2_in1_bias', optype='Producer', children: [[1]])
  Node(name='data_63', optype='Pad', parents: [0], children: [[1]])
  Node(name='res1_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res3_in1_bias', optype='Producer', children: [[1]])
  Node(name='data_83', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_97', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res1_in1_weight', optype='Producer', children: [[1]])
  Node(name='in4_weight', optype='Producer', children: [[1]])
  Node(name='res3_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_65', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_98', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='res4_in2_bias', optype='Producer', children: [[1]])
  Node(name='data_76', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res2_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_70', optype='ReLU', parents: [1], children: [[1]])
  Node(name='res3_in2_bias', optype='Producer', children: [[1]])
  Node(name='res5_in1_weight', optype='Producer', children: [[1]])
  Node(name='res2_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_99', optype='Pad', parents: [1], children: [[1]])
  Node(name='res3_in2_weight', optype='Producer', children: [[1]])
  Node(name='data_92', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_68', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res5_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res4_in2_weight', optype='Producer', children: [[1]])
  Node(name='data_80', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_93', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res5_in2_weight', optype='Producer', children: [[1]])
  Node(name='data_81', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res5_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_82', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='res4_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_94', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_69', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res4_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res2_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res3_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='deconv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_66', optype='ReLU', parents: [1], children: [[1]])
  Node(name='conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_95', optype='Pad', parents: [1], children: [[1]])
  Node(name='conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='output1', optype='Conv2D', parents: [1, 1, 1], children: [[]])
  Node(name='res4_in1_bias', optype='Producer', children: [[1]])
  Node(name='data_122', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_123', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='in5_weight', optype='Producer', children: [[1]])
  Node(name='data_124', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_121', optype='Pad', parents: [1], children: [[1]])
  Node(name='res1_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_75', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_88', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='conv3_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='in1_weight', optype='Producer', children: [[1]])
  Node(name='res1_in2_bias', optype='Producer', children: [[1]])
  Node(name='in1_bias', optype='Producer', children: [[1]])
  Node(name='res1_in1_bias', optype='Producer', children: [[1]])
  Node(name='deconv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res2_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='deconv3_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='deconv3_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in2_weight', optype='Producer', children: [[1]])
  Node(name='data_91', optype='Pad', parents: [1], children: [[1]])
  Node(name='in2_bias', optype='Producer', children: [[1]])
  Node(name='deconv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='deconv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res5_in1_bias', optype='Producer', children: [[1]])
  Node(name='in3_weight', optype='Producer', children: [[1]])
  Node(name='in3_bias', optype='Producer', children: [[1]])
  Node(name='conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='conv3_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_78', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_87', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_120', optype='Upsample', parents: [1], children: [[1]])
  Node(name='res1_in2_weight', optype='Producer', children: [[1]])
  Node(name='data_117', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_118', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_119', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_116', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_115', optype='Upsample', parents: [1], children: [[1]])
  Node(name='data_89', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_112', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='res5_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_113', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_114', optype='Add', parents: [1, 1], children: [[1]])
  Node(name='in5_bias', optype='Producer', children: [[1]])
  Node(name='res5_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_125', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_108', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_72', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_109', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_110', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_111', optype='Pad', parents: [1], children: [[1]])
  Node(name='data_104', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_64', optype='Conv2D', parents: [1, 1, 1], children: [[1]])
  Node(name='data_105', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_106', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='data_107', optype='Pad', parents: [1], children: [[1]])

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

Native operators: 108 (5 types)
- Add: 5
- Conv2D: 16
- InstanceNorm: 15
- Producer: 62
- ReLU: 10
Generic operators: 18 (2 types)
- Pad: 16
- Upsample: 2
Native types coverage: 71.4% (5/7)
Native operators coverage: 85.7% (108/126)
  (defaultdict(<class 'int'>, {'Conv2D': 16, 'Add': 5, 'InstanceNorm': 15, 'Producer': 62, 'ReLU': 10}), defaultdict(<class 'int'>, {'Pad': 16, 'Upsample': 2}))

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

Remove flatten
Fuse batchnorm
Expand metaop
Fuse to metaop

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

  Node(name='data_110', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_119', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_94', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_102', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_85', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_105', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_86', optype='ReLU', parents: [1], children: [[1]])
  Node(name='res5_in2_bias', optype='Producer', children: [[1]])
  Node(name='res5_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_97', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_106', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='res5_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res4_in1_bias', optype='Producer', children: [[1]])
  Node(name='res4_in2_bias', optype='Producer', children: [[1]])
  Node(name='data_89', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_90', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='res5_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res4_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res5_in1_bias', optype='Producer', children: [[1]])
  Node(name='res5_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res4_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res5_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res4_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res3_in2_weight', optype='Producer', children: [[1]])
  Node(name='res3_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_81', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res3_in1_bias', optype='Producer', children: [[1]])
  Node(name='res3_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res3_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res3_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res2_in2_weight', optype='Producer', children: [[1]])
  Node(name='res2_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_82', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='res2_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res2_in1_bias', optype='Producer', children: [[1]])
  Node(name='res4_in1_weight', optype='Producer', children: [[1]])
  Node(name='data_77', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res2_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='data_73', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res4_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res1_in2_weight', optype='Producer', children: [[1]])
  Node(name='res1_in2_bias', optype='Producer', children: [[1]])
  Node(name='data_74', optype='ReLU', parents: [1], children: [[1, 1]])
  Node(name='res1_in1_weight', optype='Producer', children: [[1]])
  Node(name='res2_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res1_in1_bias', optype='Producer', children: [[1]])
  Node(name='res1_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_78', optype='ReLU', parents: [1], children: [[1]])
  Node(name='res1_conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res2_conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_98', optype='Add', parents: [1, 1], children: [[1, 1]])
  Node(name='data_69', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_93', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='res1_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='res1_conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_118', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_113', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='data_115', optype='Upsample', parents: [1], children: [[1]])
  Node(name='data_120', optype='Upsample', parents: [1], children: [[1]])
  Node(name='res3_in2_bias', optype='Producer', children: [[1]])
  Node(name='deconv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in5_weight', optype='Producer', children: [[1]])
  Node(name='data_66', optype='ReLU', parents: [1], children: [[1]])
  Node(name='conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in4_weight', optype='Producer', children: [[1]])
  Node(name='conv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='data_70', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_124', optype='ReLU', parents: [1], children: [[1]])
  Node(name='data_123', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='conv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in5_bias', optype='Producer', children: [[1]])
  Node(name='conv3_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='res3_conv1_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in1_weight', optype='Producer', children: [[1]])
  Node(name='in1_bias', optype='Producer', children: [[1]])
  Node(name='deconv2_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='deconv3_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='in2_weight', optype='Producer', children: [[1]])
  Node(name='deconv3_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in2_bias', optype='Producer', children: [[1]])
  Node(name='deconv1_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='deconv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[]])
  Node(name='data_65', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  perator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_116[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_120[0m] of type [[1m[3mUpsample[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'nearest'
[[94mNOTICE[0m]   	* scales : [1.0, 1.0, 2.0, 2.0]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_121[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 1, 1, 0, 0, 1, 1]
[[33mWARNING[0m] - Warning: Attribute dict_keys(['pads']) is not supported for operator Pad.
[[94mNOTICE[0m] - Loaded node [[1m[3mdata_125[0m] of type [[1m[3mPad[0m] as a GenericOperator.
[[94mNOTICE[0m]   	* mode : b'reflect'
[[94mNOTICE[0m]   	* pads : [0, 0, 4, 4, 0, 0, 4, 4]
[[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!
[[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!
[[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!
[[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!
[[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: 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 fNode(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='res4_in2_weight', optype='Producer', children: [[1]])
  Node(name='in3_weight', optype='Producer', children: [[1]])
  Node(name='in3_bias', optype='Producer', children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='res2_in2_bias', optype='Producer', children: [[1]])
  Node(name='data_109', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='data_101', optype='InstanceNorm', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [1, 1, 1], children: [[1]])
  Node(name='data_114', optype='Add', parents: [1, 1], children: [[1]])
  Node(name='', optype='PadConv', parents: [0, 1, 1], children: [[1]])
  Node(name='res5_in2_weight', optype='Producer', children: [[1]])
  Node(name='conv2_conv2d_weight', optype='Producer', children: [[1]])
  Node(name='conv3_conv2d_bias', optype='Producer', children: [[1]])
  Node(name='in4_bias', optype='Producer', children: [[1]])

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

Native operators: 108 (5 types)
- Add: 5
- InstanceNorm: 15
- PadConv: 16
- Producer: 62
- ReLU: 10
Generic operators: 2 (1 types)
- Upsample: 2
Native types coverage: 83.3% (5/6)
Native operators coverage: 98.2% (108/110)
  (defaultdict(<class 'int'>, {'InstanceNorm': 15, 'Add': 5, 'ReLU': 10, 'Producer': 62, 'PadConv': 16}), defaultdict(<class 'int'>, {'Upsample': 2}))

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

Native operators: 108 (5 types)
- Add: 5
- InstanceNorm: 15
- PadConv: 16
- Producer: 62
- ReLU: 10
Generic operators: 2 (1 types)
- Upsample: 2
Native types coverage: 83.3% (5/6)
Native operators coverage: 98.2% (108/110)
  (defaultdict(<class 'int'>, {'Add': 5, 'Producer': 62, 'InstanceNorm': 15, 'ReLU': 10, 'PadConv': 16}), defaultdict(<class 'int'>, {'Upsample': 2}))

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

OK

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

OK

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

in4_bias (Producer)
in4_weight (Producer)
in5_bias (Producer)
in5_weight (Producer)
_PadConv_3_biases (Producer)
_PadConv_3_weights (Producer)
_PadConv_4_biases (Producer)
_PadConv_4_weights (Producer)
res1_in1_bias (Producer)
res1_in1_weight (Producer)
res1_in2_bias (Producer)
res1_in2_weight (Producer)
_PadConv_5_biases (Producer)
_PadConv_5_weights (Producer)
_PadConv_6_weights (Producer)
_PadConv_6_biases (Producer)
res2_in1_bias (Producer)
res2_in1_weight (Producer)
res2_in2_bias (Producer)
res2_in2_weight (Producer)
_PadConv_7_biases (Producer)
_PadConv_7_weights (Producer)
_PadConv_8_biases (Producer)
_PadConv_8_weights (Producer)
res3_in1_bias (Producer)
res3_in1_weight (Producer)
res3_in2_bias (Producer)
res3_in2_weight (Producer)
_PadConv_9_biases (Producer)
_PadConv_9_weights (Producer)
_PadConv_10_biases (Producer)
_PadConv_10_weights (Producer)
res4_in1_bias (Producer)
res4_in1_weight (Producer)
res4_in2_bias (Producer)
res4_in2_weight (Producer)
_PadConv_11_biases (Producer)
_PadConv_11_weights (Producer)
_PadConv_12_biases (Producer)
_PadConv_12_weights (Producer)
res5_in1_bias (Producer)
res5_in1_weight (Producer)
res5_in2_bias (Producer)
res5_in2_weight (Producer)
_PadConv_2_biases (Producer)
_PadConv_1_weights (Producer)
in3_bias (Producer)
in3_weight (Producer)
_PadConv_14_weights (Producer)
_PadConv_13_weights (Producer)
in2_bias (Producer)
in2_weight (Producer)
_PadConv_15_biases (Producer)
_PadConv_15_weights (Producer)
_PadConv_14_biases (Producer)
in1_bias (Producer)
in1_weight (Producer)
_PadConv_2_weights (Producer)
_PadConv_1_biases (Producer)
_PadConv_0_weights (Producer)
_PadConv_0_biases (Producer)
_PadConv_13_biases (Producer)
_PadConv_0 (PadConv)
_InstanceNorm_0 (InstanceNorm)
_ReLU_0 (ReLU)
_PadConv_1 (PadConv)
_InstanceNorm_1 (InstanceNorm)
_ReLU_1 (ReLU)
_PadConv_2 (PadConv)
_InstanceNorm_2 (InstanceNorm)
_ReLU_2 (ReLU)
_PadConv_3 (PadConv)
_InstanceNorm_3 (InstanceNorm)
_ReLU_3 (ReLU)
_PadConv_4 (PadConv)
_InstanceNorm_4 (InstanceNorm)
_Add_0 (Add)
_PadConv_5 (PadConv)
_InstanceNorm_5 (InstanceNorm)
_ReLU_4 (ReLU)
_PadConv_6 (PadConv)
_InstanceNorm_6 (InstanceNorm)
_Add_1 (Add)
_PadConv_7 (PadConv)
_InstanceNorm_7 (InstanceNorm)
_ReLU_5 (ReLU)
_PadConv_8 (PadConv)
_InstanceNorm_8 (InstanceNorm)
_Add_2 (Add)
_PadConv_9 (PadConv)
_InstanceNorm_9 (InstanceNorm)
_ReLU_6 (ReLU)
_PadConv_10 (PadConv)
_InstanceNorm_10 (InstanceNorm)
_Add_3 (Add)
_PadConv_11 (PadConv)
_InstanceNorm_11 (InstanceNorm)
_ReLU_7 (ReLU)
_PadConv_12 (PadConv)
_InstanceNorm_12 (InstanceNorm)
_Add_4 (Add)
_Upsample_0 (Upsample)
_PadConv_13 (PadConv)
_InstanceNorm_13 (InstanceNorm)
_ReLU_8 (ReLU)
_Upsample_1 (Upsample)
_PadConv_14 (PadConv)
_InstanceNorm_14 (InstanceNorm)
_ReLU_9 (ReLU)
_PadConv_15 (PadConv)

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

or nodes ["data_63 (Pad)",
[[33mWARNING[0m]   "data_64 (Conv2D)"].
[[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 ["data_65
[[33mWARNING[0m]   (InstanceNorm)", "data_69 (InstanceNorm)", "data_73 (InstanceNorm)", "data_77
[[33mWARNING[0m]   (InstanceNorm)", "data_81 (InstanceNorm)", "data_89 (InstanceNorm)", "data_85
[[33mWARNING[0m]   (InstanceNorm)", "data_93 (InstanceNorm)", "data_97 (InstanceNorm)", "data_101
[[33mWARNING[0m]   (InstanceNorm)", "data_105 (InstanceNorm)", "data_109 (InstanceNorm)", "data_113
[[33mWARNING[0m]   (InstanceNorm)", "data_118 (InstanceNorm)", " (PadConv)", " (PadConv)", " (PadConv)", "
[[33mWARNING[0m]   (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", "
[[33mWARNING[0m]   (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", " (PadConv)", "
[[33mWARNING[0m]   (PadConv)", "data_123 (InstanceNorm)"].
[[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
[[95mFATAL[0m]   N5Aidge15InstanceNorm_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 N5Aidge15InstanceNorm_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 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 udnie8.onnx No targets specified and no makefile found. Stop.

Report Details

report.json

null

123873 - rpi4b aidge 123875 - rpi4b aidge