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Hi,
I'm testing few models with NCS at the moment. I found out the layers supported by mvNCCompile is quite limited.
Can you provide what full list of layers supported by your product in each framework (caffe/tensorflow)?
I wasn't able to find it in the dev documents.
Also, I see 'concat' layer is not supported atm, Is there any time-plan when it is going to be updated?
Thanks
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- Caffe
- Tensorflow
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Supported layers are listed in the latest release notes: https://github.com/movidius/ncsdk/releases/tag/v1.10.01.01
Currently includes (according to the release notes)
- Convolutions
- NxN Convolution with Stride S.
- The following cases have been extensively tested: 1x1s1,3x3s1,5x5s1,7x7s1, 7x7s2, 7x7s4
- Group convolution
- Depth Convolution
- Dilated convolution
- Max Pooling Radix NxM with Stride S
- Average Pooling: Radix NxM with Stride S, Global average pooling
- Local Response Normalization
- Relu, Relu-X, Prelu (see erattum #10)
- Softmax
- Sigmoid
- Tanh (see erratum #10)
- Deconvolution
- Slice
- Scale
- ElmWise unit : supported operations - sum, prod, max
- Fully Connected Layers (limited support -- see erratum #8)
- Reshape
- Flatten
- Power
- Crop
- ELU
- Batch Normalization
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@tf_movidius Thank you very much!
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Hi,
My net uses a tf.slice operator on a tensor and I get
[Error 5] Toolkit Error: Stage Details Not Supported: Slice type not supported
while running mvNCCompile on it.
Could you help me with this?
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@gokul_uf Yes. We're working to add as much support as we can for all of the different neural networks out there, so if you can provide a link to your network, we can help with debugging issues.
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@Tome_at_Intel The net is at model.py
here https://github.com/SpaceML/GalaxyGAN_python/
I had modified the net to have both image
and cond
passed in as single tensor and slice it inside to get around the only one input limitation. That's where I got the Slice issue.
I later realized that I needed only cond
so I reverted back to the original code and I get the following error.
[Error 5] Toolkit Error: Stage Details Not Supported: Unsupported Mean operation
It'd be great if you could help me with this, because I have a demo coming up :smile:
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@gokul_uf Since I cannot find the network's meta file from the link., it looks like I am required to download their data and train to obtain the network. It would save me a lot of time if you could provide me the model's meta file.
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@Tome_at_Intel Apologies, my bad! The meta files are at https://drive.google.com/drive/folders/1yoqOVZIAfm3UpVAqWq3Ps-6cmpgd_1Cr?usp=sharing
the non_bnorm one has the bnorm op removed (because we use just 1 image per training so no point having bnorm)
the non_unet one has the skip links removed in the generator method (this uses concat and I saw that concat is buggy in ncsdk)
the input node name is cond
and output is gen/gen_op
.
Thanks!
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@gokul_uf I need the checkpoint file also if you could provide it. I am getting an error saying : Failed to find any matching files for non_bnorm_model_1.ckpt
. Thanks!
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Hi, are you planning to release support for 3dconvolutions/ 3d Max pooling any time soon?
Thanks!
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@gokul_uf Can you try your network with the latest SDK (1.11) and let me know if this fixes your issue?
@JMat I can't give a specific timeline for you regarding the support for 3d convolutions, but as of now, it is something we are considering and looking into. Thanks.
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@gokul_uf I had issues too, according to /opt/movidius/NCSDK/ncsdk-x86_64/tk/Controllers/TensorFlowParser.py, line 1489:
if (len(input_shape) != 4 or len(slicingbegin) != 4 or len(slicingsize) != 4 or
slicingbegin[0] != 0 or slicingbegin[1] != 0 or slicingbegin[2] != 0 or
input_shape[0] != slicingsize[0] or input_shape[1] != slicingsize[1] or input_shape[2] != slicingsize[2]):
You can slice only on 4th dimension (image channels). Moreover, you can't use "-1" indexing you can use on base Tensorflow.
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Is GRU supported?
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@sreerag_ibtl,
I don't think GRU is supported as currently the NCSDK does not have support for RCNNs, hope this helps.
Regards,
@Luis_at_Intel
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