Inference in Dinov2 Network Produces Unexpected Results with Nan Values

Required prerequisites

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What commit version of aidge do you use

aidge_core: 1c21952e
aidge_backend_cpu: 69c994fe16379138badcd19a6a1c0e75798b99b8
aidge_onnx: 9cad6572d76d36229c1de15847f0252f96fd06ce
Problem description

I am currently working with the Dinov2 network and I am encountering an issue during the inference process. The problem is that the network does not give the expected results, instead, it returns an array filled with nan values.
Steps to reproduce:
Download/Load the Dinov2 network here(https://filesender.renater.fr/?s=download&token=969d2aff-3789-4a1f-bfab-6e16d3ff9e97)
Download the python script here(https://filesender.renater.fr/?s=download&token=22c65479-7ec0-49da-8980-75e6c152e58e)
Perform inference on a given script, please change two paths (model and input image)
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: unable to forwardDims() because output dims are data dependent on input#1
[[[nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan
   nan nan nan nan nan nan nan nan nan nan]]]
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: unable to forwardDims() because output dims are data dependent on input#1
Unable to forward dimensions (circular dependency and/or wrong dimensions and/or data dependent dimension?). 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Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: unable to forwardDims() because output dims are data dependent on input#1
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: unable to forwardDims() because output dims are data dependent on input#1
Unable to forward dimensions (circular dependency and/or wrong dimensions and/or data dependent dimension?). 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"encoder_layer_10_attention_attention_Reshape_output_0 (Reshape)", "encoder_layer_10_attention_attention_value_Add_output_0 (Add)", "encoder_layer_10_attention_attention_Reshape_1_output_0 (Reshape)", "encoder_layer_10_attention_attention_Reshape_2_output_0 (Reshape)", "encoder_layer_10_attention_attention_Div_output_0 (Div)", "encoder_layer_10_attention_attention_Reshape_3_output_0 (Reshape)", "encoder_layer_10_attention_output_dense_MatMul_output_0 (MatMul)", "encoder_layer_10_attention_output_dense_Add_output_0 (Add)", "encoder_layer_10_layer_scale1_Mul_output_0 (Mul)", "encoder_layer_10_norm2_Pow_output_0 (Pow)", "encoder_layer_10_norm2_Add_output_0 (Add)", "encoder_layer_10_norm2_Mul_output_0 (Mul)", "encoder_layer_10_norm2_Add_1_output_0 (Add)", "encoder_layer_10_mlp_fc1_MatMul_output_0 (MatMul)", "encoder_layer_10_mlp_fc1_Add_output_0 (Add)", "encoder_layer_10_mlp_activation_Div_output_0 (Div)", "encoder_layer_10_mlp_activation_Add_output_0 (Add)", "encoder_layer_10_mlp_activation_Mul_1_output_0 (Mul)", "encoder_layer_11_norm1_Add_output_0 (Add)", "encoder_layer_11_norm1_Mul_output_0 (Mul)", "encoder_layer_11_norm1_Add_1_output_0 (Add)", "v_1417 (MatMul)", "v_1418 (Split)", "encoder_layer_11_attention_attention_query_Add_output_0 (Add)", "encoder_layer_11_attention_attention_key_Add_output_0 (Add)", "encoder_layer_11_attention_attention_Reshape_output_0 (Reshape)", "encoder_layer_11_attention_attention_value_Add_output_0 (Add)", "encoder_layer_11_attention_attention_Reshape_1_output_0 (Reshape)", "encoder_layer_11_attention_attention_Reshape_2_output_0 (Reshape)", "encoder_layer_11_attention_attention_Div_output_0 (Div)", "encoder_layer_11_attention_attention_Reshape_3_output_0 (Reshape)", "encoder_layer_11_attention_output_dense_MatMul_output_0 (MatMul)", "encoder_layer_11_attention_output_dense_Add_output_0 (Add)", "encoder_layer_11_layer_scale1_Mul_output_0 (Mul)", "encoder_layer_11_norm2_Pow_output_0 (Pow)", "encoder_layer_11_norm2_Add_output_0 (Add)", "encoder_layer_11_norm2_Mul_output_0 (Mul)", "encoder_layer_11_norm2_Add_1_output_0 (Add)", "encoder_layer_11_mlp_fc1_MatMul_output_0 (MatMul)", "encoder_layer_11_mlp_fc1_Add_output_0 (Add)", "encoder_layer_11_mlp_activation_Div_output_0 (Div)", "encoder_layer_11_mlp_activation_Add_output_0 (Add)", "encoder_layer_11_mlp_activation_Mul_1_output_0 (Mul)", "encoder_layer_11_mlp_fc2_MatMul_output_0 (MatMul)", "encoder_layer_11_mlp_fc2_Add_output_0 (Add)", "encoder_layer_11_layer_scale2_Mul_output_0 (Mul)", "layernorm_Pow_output_0 (Pow)", "layernorm_Add_output_0 (Add)", "layernorm_Mul_output_0 (Mul)", "output (Add)", "data_1593 (Gather)"].
No producer node attached to input#0 for node embeddings_patch_embeddings_projection_Conv_output_0 (Conv)
No producer node attached to input#0 for node embeddings_patch_embeddings_projection_Conv_output_0 (Conv)
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Split_Op: ignoring non-empty Split attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
Reshape_Op: ignoring non-empty Shape attribute because input#1 takes precedence
I have checked the input data and it seems to be in the correct format. I suspect there might be an issue with the network configuration or the inference process itself.
Could you please help me troubleshoot this issue? Any help would be greatly appreciated.
Thank you!
Edited Jul 23, 2024 by Michal Szczepanski