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Compile the saved model of Google Cloud AutoML Vison with Compile Tool

taka
Beginner
415 Views


Hello,

When compiling the attached IR file with Compile Tool, the following error occurs.
The attached IR file can be executed on the CPU or GPU.

Is there a way to compile this IR model with Compile Tool?
(If it is not currently supported, I hope that Compile Tool will be improved in the future.)

[Execution environment]
ubuntu 20.04.3LTS
openvino2021.4
model: Google Cloud AutoML Vision saved_model


---------------------------------------error message---------------------------------------------------

user@193f58464f81:~/workdir/$ ${INTEL_OPENVINO_DIR}/deployment_tools/tools/compile_tool/compile_tool \
> -m saved_model.xml \
> -ip U8 \
> -VPU_NUMBER_OF_SHAVES 4 \
> -VPU_NUMBER_OF_CMX_SLICES 4 \
> -o saved_model.blob \
> -d MYRIAD
Inference Engine:
IE version ......... 2021.4.0
Build ........... 2021.4.0-3839-cd81789d294-releases/2021/4

Network inputs:
mnas_v4_a_1/feature_network/stem/conv/Conv2D_Fold/placeholder_port_0 : U8 / NCHW
Network outputs:
Sigmoid : FP16 / NC
[Warning][VPU][Config] Deprecated option was used : VPU_MYRIAD_PLATFORM

[ GENERAL_ERROR ]
/home/jenkins/agent/workspace/private-ci/ie/build-linux-ubuntu20/b/repos/openvino/inference-engine/src/vpu/graph_transformer/src/frontend/frontend.cpp:439 Failed to compile layer "mnas_v4_a_1/feature_network/stem/conv/add_fold": [ GENERAL_ERROR ]
/home/jenkins/agent/workspace/private-ci/ie/build-linux-ubuntu20/b/repos/openvino/inference-engine/src/vpu/graph_transformer/src/stages/convolution.cpp:44 invalid number of inputs: 3u

------------------------------------------------------------------------------------------------------

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4 Replies
Peh_Intel
Moderator
370 Views

Hi taka,


Thanks for reaching out to us and sharing your model with us.


I noticed that your model has been quantized as there are FakeQuantize layers in the model.


For your information, the low-precision 8-bit inference is optimized for Intel CPU and GPU only. You can refer to Low-Precision 8-bit Integer Inference for more detailed supported devices.


Hence, try to compile the FP16 IR model.



Regards,

Peh


taka
Beginner
357 Views

hi, Peh

 

The attached file is FP16 IR model. 
Just because there are FakeQuantize layers doesn't mean it's an 8-bit IR model.

 

The details of the error are as follows.

The problem is occurring in the "mnas_v4_a_1 / feature_network / stem / conv / add_fold" layer.


>  /home/jenkins/agent/workspace/private-ci/ie/build-linux-ubuntu20/b/repos/openvino/inference

> -engine/src/vpu/graph_transformer/src/frontend/frontend.cpp:439

> Failed to compile layer "mnas_v4_a_1/feature_network/stem/conv/add_fold": [ GENERAL_ERROR ]

> /home/jenkins/agent/workspace/private-ci/ie/build-linux-ubuntu20/b/repos/openvino/inference

> -engine/src/vpu/graph_transformer/src/stages/convolution.cpp:44 invalid number of inputs: 3u


Regards,

Peh_Intel
Moderator
334 Views

Hi taka,


The FakeQuantize layers are one of the unsupported layer types for the compilation. The "mnas_v4_a_1 / feature_network /stem/conv/add_fold" layer is added before the FakeQuantize layers and hence the compilation failed due to the input size is not equal to 1.


For a separate note, I was able to compile an FP16 age-gender-recognition-retail-0013 model (without FakeQuantize layers). However, when I tried to compile an FP16-INT8 age-gender-recognition-retail-0013 model (with FakeQuantize layers), I obtained the similar error as you.



Regards,

Peh


Peh_Intel
Moderator
290 Views

Hi taka,


This thread will no longer be monitored since we have provided answer. If you need any additional information from Intel, please submit a new question. 



Regards,

Peh


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