Forums - snpe-tensorflow-to-dlc error

4 posts / 0 new
or Register
Last post
snpe-tensorflow-to-dlc error
jack.profit
Join Date: 10 May 22
Posts: 5
Posted: Mon, 2022-05-16 19:24
Top

I am seeing an error when using the SNPE tutorial setup script that converts the the inception_v3 TF model to DLC.

I am running the latest QC and Tensorflow tools (I think): SNPE version 1.61.0, Hexagon versoin 4.5.0.3, Tensorflow 2.6.2, Nvidia Toolbox latest.

Unfortunately, I cannot include the full output because the QC forum thinks I'm posting in an unallowed language if I include the whole thing. Here is the edited output. As you can see, it reports to have completed successfully, but there is a problem on this line:

2022-05-16 19:20:20.474169: I tensorflow/core/platform/default/subprocess.cc:304] Start cannot spawn child process: No such file or directory

Here is the trimmed script output:

$ snpe-tensorflow-to-dlc --input_network /home/jprofit/qc/snpe-1.61.0.3358/models/inception_v3/tensorflow/inception_v3_2016_08_28_frozen_opt.pb --input_dim input 1,299,299,3 --out_node InceptionV3/Predictions/Reshape_1 --output_path /home/jprofit/qc/snpe-1.61.0.3358/models/inception_v3/dlc/inception_v3.dlc
2022-05-16 19:20:18.610432: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
...
2022-05-16 19:20:19.336455: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 2246 MB memory:  -> device: 0, name: NVIDIA T500, pci bus id: 0000:01:00.0, compute capability: 7.5
2022-05-16 19:20:20.134022: I tensorflow/stream_executor/cuda/cuda_dnn.cc:369] Loaded cuDNN version 8100
2022-05-16 19:20:20.474169: I tensorflow/core/platform/default/subprocess.cc:304] Start cannot spawn child process: No such file or directory
2022-05-16 19:20:22,339 - 214 - INFO - INFO_ALL_BUILDING_NETWORK: 
    ==============================================================
    Building Network
    ==============================================================
2022-05-16 19:20:22,667 - 214 - INFO - Resolving static sub-graphs in network...
2022-05-16 19:20:22,761 - 214 - INFO - Resolving static sub-graphs in network, complete.
2022-05-16 19:20:22,995 - 214 - INFO - INFO_DLC_SAVE_LOCATION: Saving model at /home/jprofit/qc/snpe-1.61.0.3358/models/inception_v3/dlc/inception_v3.dlc
2022-05-16 19:20:23,745 - 214 - INFO - INFO_CONVERSION_SUCCESS: Conversion completed successfully
 
  • Up0
  • Down0
Re: snpe-tensorflow-to-dlc error
sanjjey.a.sanjjey
Join Date: 17 May 22
Posts: 55
Posted: Tue, 2022-05-17 05:16
Top

Hi,

I am also working on that SNPE tutorial setups only, Please try changing the versions.

Ubuntu:18.04

Tensorflow==1.15.0

Python==3.6.13

SNPE==1.54.2.2899

 

  • Up0
  • Down0
Re: snpe-tensorflow-to-dlc error
jack.profit
Join Date: 10 May 22
Posts: 5
Posted: Tue, 2022-05-17 08:22
Top

Thanks for the response.

Downgrading to Tensorflow 1.X is not an option for me.  Are you saying the SNPE doesn't support Tensorflow 2? The documentation for SNPE suggests that Tensorflow 1.x is deprecated.

  • Up0
  • Down0
Re: snpe-tensorflow-to-dlc error
jack.profit
Join Date: 10 May 22
Posts: 5
Posted: Wed, 2022-05-18 08:39
Top

Any thoughts on the issue? I am just trying to run the tutorial straight from the instructions without success so I'm confused why I'm the only one having this problem.

Is there a known set of versions for OS, SNPE, Hexagon_SDK and Nvidia (using Tensorflow 2) that is known to work?

Thanks for any pointers.

  • Up0
  • Down0
or Register

Opinions expressed in the content posted here are the personal opinions of the original authors, and do not necessarily reflect those of Qualcomm Incorporated or its subsidiaries (“Qualcomm”). The content is provided for informational purposes only and is not meant to be an endorsement or representation by Qualcomm or any other party. This site may also provide links or references to non-Qualcomm sites and resources. Qualcomm makes no representations, warranties, or other commitments whatsoever about any non-Qualcomm sites or third-party resources that may be referenced, accessible from, or linked to this site.