Quad stereo tensorflow eclipse

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ImageJ plugin

NOTE: if project is updated/pulled outside Eclipse - might need a manual refresh

  • TF version is pulled from pom.xml
  • Trained TF model for EO sensors is auto-downloaded - trained_model_v1.0.zip
  • Get some image samples, provide paths
  • Before running the plugin (Eyesis_Correction), copy imagej options to /home/user/.imagejs/Eyesis_Correction.xml:

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">
<properties>
    <comment>last updated Thu Sep 08 14:09:47 MDT 2042</comment>
    <entry key="ADVANCED_MODE">True</entry>
    <entry key="DCT_MODE">True</entry>
    <entry key="MODE_3D">False</entry>
    <entry key="GPU_MODE">True</entry>
    <entry key="LWIR_MODE">True</entry>
</properties>

  • Updated pom.xml to TF 1.15 - package exists
  • Install cuDNN all 3 packages - runtime, dev and docs. Used docs to verify installation - built mnistCUDNN:
https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html
  • I think TF 1.15 maven package was built for CUDA 10.0 driver, and so it whines when 10.2 is installed.
2019-12-27 13:05:15.754656: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.754756: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.754860: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.754970: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.755075: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.755178: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory
2019-12-27 13:05:15.762197: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-27 13:05:15.762227: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1641] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
  • TF 1.15 and CUDA 10.0 require GPU compute capability = 6.0, GeForce GTX 750Ti is 5.0:
2019-12-27 14:22:17.475717: I tensorflow/cc/saved_model/reader.cc:31] Reading SavedModel from: /home/oleg/GIT/imagej-elphel/target/classes/trained_model
2019-12-27 14:22:17.477009: I tensorflow/cc/saved_model/reader.cc:54] Reading meta graph with tags { serve }
2019-12-27 14:22:17.503393: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3392030000 Hz
2019-12-27 14:22:17.504196: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f610dba1a20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-27 14:22:17.504235: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2019-12-27 14:22:17.505378: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-27 14:22:17.517647: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-27 14:22:17.518168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: GeForce GTX 750 Ti major: 5 minor: 0 memoryClockRate(GHz): 1.1105
pciBusID: 0000:01:00.0
2019-12-27 14:22:17.518385: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-12-27 14:22:17.519624: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2019-12-27 14:22:17.675574: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2019-12-27 14:22:17.716621: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2019-12-27 14:22:18.160070: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2019-12-27 14:22:18.439862: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2019-12-27 14:22:18.443378: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-27 14:22:18.443483: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-27 14:22:18.444034: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-27 14:22:18.444510: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1700] Ignoring visible gpu device (device: 0, name: GeForce GTX 750 Ti, pci bus id: 0000:01:00.0, compute capability: 5.0) with 
Cuda compute capability 5.0. The minimum required Cuda capability is 6.0.
2019-12-27 14:22:18.498425: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-27 14:22:18.498455: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 
2019-12-27 14:22:18.498463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N 
2019-12-27 14:22:18.504855: I tensorflow/cc/saved_model/loader.cc:202] Restoring SavedModel bundle.
2019-12-27 14:22:18.528948: I tensorflow/cc/saved_model/loader.cc:151] Running initialization op on SavedModel bundle at path: /home/oleg/GIT/imagej-elphel/target/classes/trained_model
2019-12-27 14:22:18.581034: I tensorflow/cc/saved_model/loader.cc:311] SavedModel load for tags { serve }; Status: success. Took 1105321 microseconds.

  • So, TF1.15 + CUDA 10.0 might work with GeForce GTX 1080 Ti (compute capability 6.1)

TF Test button in Eyesis_Correction plugin worked with CUDA 10.0 (even with nvidia-smi showing CUDA 10.1 - it's probably not relevant to the libs used)

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