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I tried to compile two very basic models that I created in Keras and then saved as a TensorFlow model (I followed this guide).
First I had a model which used the LeakyReLU from Keras. Trying to compile this model using mvNCCompile
I got the following error log:
mvNCCompile v02.00, Copyright @ Intel Corporation 2017
****** Info: No Weights provided. inferred path: tf_model.data-00000-of-00001******
tf_model.meta
2019-03-18 16:44:01.272627: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
No Bias
[Error 5] Toolkit Error: Stage Details Not Supported: leaky_re_lu_1/LeakyRelu/mul
So I did a quick search on which activations are supported by NCSDK and found _tanh_ should be supported due to these release notes.
I trained a new model, now using _tanh_ as activation. But this time I got the following error log:
mvNCCompile v02.00, Copyright @ Intel Corporation 2017
****** Info: No Weights provided. inferred path: tf_model.data-00000-of-00001******
tf_model.meta
2019-03-27 09:19:38.161469: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
No Bias
[Error 4] Toolkit Error: Stage Type Not Supported: Tanh
Please help me with that, as I don't know how to work around that error.
- Tags:
- Keras
- Tensorflow
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Hi @martin-online
Which version of the NCSDK are you using?
The top and bottom blobs have different names right? Can you attach your model here so I can take a look at it please?
Best Regards,
Sahira
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Hi @Sahira_at_Intel ,
thanks for your reply!
I'm using the NCSDK version 2.10.01.01.
That's the model.summary()
of the simple model with tanh activation in the "activation_1" and softmax in "activation_2".
Layer (type) Output Shape Param #
=================================================================
dense_1 (Dense) (None, 8) 328
activation_1 (Activation) (None, 8) 0
output (Dense) (None, 3) 27
activation_2 (Activation) (None, 3) 0
=================================================================
Total params: 355
Trainable params: 355
Non-trainable params: 0
Input: []
Output: []
Here's visualisation as an image: https://imgur.com/Lx7ttfU
Looking forward to your answer. =)
Best regards,
Martin
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