Feeding Tensorflow from GPU
← Older revision
Revision as of 00:30, 15 January 2020
Line 1:
Line 1:
==About== ==About==
+Reference guides:
+* [https://viralfsharp.com/2019/03/25/supercharging-object-detection-in-video-from-glacial-to-lightning-speed/ Supercharging Object Detection in Video: from Glacial to Lightning Speed]
+* [https://viralfsharp.com/2019/03/25/supercharging-object-detection-in-videos-setup/ Setup]
+* [https://viralfsharp.com/2019/03/25/supercharging-object-detection-in-video-first-app/ First App]
+* [https://viralfsharp.com/2019/03/25/supercharging-object-detection-in-video-optimizing-decoding-and-graph-feeding/ Optimizing Decoding and Graph Feeding]
+
==Setup== ==Setup==
Oleg
Feeding Tensorflow from GPU
Created page with "==About== ==Setup=="
New page
==About====Setup== Oleg
01/10/20 [imagej-elphel][lwir] by AndreyFilippov: Implemented 2d maximum modelled as Gaussian in addition to parabola
AndreyFilippov committed changes to the Elphel git project :
Implemented 2d maximum modelled as Gaussian in addition to parabola
Implemented 2d maximum modelled as Gaussian in addition to parabola
01/09/20 [imagej-elphel][lwir] by AndreyFilippov: implemented common offsets for the tile cluster s
AndreyFilippov committed changes to the Elphel git project :
implemented common offsets for the tile cluster s
implemented common offsets for the tile cluster s
Tensorflow with gpu
Tensorflow and OpenCV building notes
← Older revision Revision as of 00:49, 8 January 2020 Line 249: Line 249: ==Tensorflow and OpenCV building notes== ==Tensorflow and OpenCV building notes== −===Targets 1===+===Build 1=== # TF 1.15.0 # TF 1.15.0 # CUDA 10.0 and Toolkit and stuff # CUDA 10.0 and Toolkit and stuff Line 261: Line 261: 3. ./configure 3. ./configure 4. 4. + +===Build 2=== +# TF 1.13.1 +# CUDA 10.0 and Toolkit and stuff +# OpenCV 3.4.9 + +====TF 1.13.1==== +* Will build with Bazel 0.21.0 (installed from [https://github.com/bazelbuild/bazel/releases/tag/0.21.0 deb archive]) OlegFile:333 hd setup.jpg
Andrey.filippov changed visibility of 6 revisions on page File:333 hd setup.jpg: content hidden, edit summary hidden and username hidden vandalism
Andrey.filippovTensorflow with gpu
Notes
← Older revision Revision as of 23:12, 7 January 2020 (One intermediate revision by the same user not shown)Line 1: Line 1: −==Requirements==+==OS== * Kubuntu 16.04 LTS * Kubuntu 16.04 LTS + ==Setup (guide)== ==Setup (guide)== Just follow: Just follow: Line 246: Line 247: # Then open a browser: # Then open a browser: '''http://localhost:6006'''</font> '''http://localhost:6006'''</font> + +==Tensorflow and OpenCV building notes== +===Targets 1=== +# TF 1.15.0 +# CUDA 10.0 and Toolkit and stuff +# OpenCV 3.4.9 + +====TF 1.15.0==== +* Will build with Bazel 0.25.2 (installed from [https://github.com/bazelbuild/bazel/releases/tag/0.25.2 deb archive]) +* TF - downloaded as [https://github.com/tensorflow/tensorflow/releases/tag/v1.15.0 tensorflow-1.15.0.tar.gz] + 1. Unpack + 2. cd tensorflow-1.15.0 + 3. ./configure + 4. OlegTensorflow with gpu
Requirements
← Older revision Revision as of 20:16, 7 January 2020 Line 1: Line 1: −==Requirements==+==OS== * Kubuntu 16.04 LTS * Kubuntu 16.04 LTS + ==Setup (guide)== ==Setup (guide)== Just follow: Just follow: Oleg01/04/20 [imagej-elphel][lwir] by AndreyFilippov: Testing/debugging
AndreyFilippov committed changes to the Elphel git project :
Testing/debugging
Testing/debugging
01/02/20 [imagej-elphel][lwir] by AndreyFilippov: Debugging Jacobian with delta
AndreyFilippov committed changes to the Elphel git project :
Debugging Jacobian with delta
Debugging Jacobian with delta
01/01/20 [imagej-elphel][lwir] by AndreyFilippov: just a comment
AndreyFilippov committed changes to the Elphel git project :
just a comment
just a comment
01/01/20 [imagej-elphel][lwir] by AndreyFilippov: more editing LMA debug
AndreyFilippov committed changes to the Elphel git project :
more editing LMA debug
more editing LMA debug
01/01/20 [imagej-elphel][lwir] by AndreyFilippov: Changed disp_dist format to [quad][4], implemented and connected new LMA
AndreyFilippov committed changes to the Elphel git project :
Changed disp_dist format to [quad][4], implemented and connected new LMA
Changed disp_dist format to [quad][4], implemented and connected new LMA
12/31/19 [imagej-elphel][lwir] by AndreyFilippov: finished first pass of new LMA creation
AndreyFilippov committed changes to the Elphel git project :
finished first pass of new LMA creation
finished first pass of new LMA creation
12/30/19 [imagej-elphel][lwir] by AndreyFilippov: working on Jacobian
AndreyFilippov committed changes to the Elphel git project :
working on Jacobian
working on Jacobian
12/30/19 [imagej-elphel][lwir] by AndreyFilippov: Working on new LMA correlation
AndreyFilippov committed changes to the Elphel git project :
Working on new LMA correlation
Working on new LMA correlation
12/27/19 [imagej-elphel][gpu] by Oleg Dzhimiev: inserted getClassLoader() so it could locate resources
Oleg Dzhimiev committed changes to the Elphel git project :
inserted getClassLoader() so it could locate resources
inserted getClassLoader() so it could locate resources
Quad stereo tensorflow eclipse
← Older revision
Revision as of 23:19, 27 December 2019
(12 intermediate revisions by the same user not shown)Line 2:
Line 2:
* Install Eclipse * Install Eclipse
* Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel] * Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel]
−<font color='tomato'>'''Note: if the project is updated/pulled outside Eclipse - need manual refresh'''</font>+<font color='red'>'''NOTE: if project is updated/pulled outside Eclipse - might need a manual refresh'''</font>
+* TF version is pulled from pom.xml
+* Trained TF model for EO sensors is auto-downloaded - [https://community.elphel.com/files/quad-stereo/ml/trained_model_v1.0.zip 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:
+<font size='1'>
+ <?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>
+</font>
+* 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.
+ <font size=1 color=red>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...</font>
+
+* TF 1.15 and CUDA 10.0 require GPU compute capability = 6.0, GeForce GTX 750Ti is 5.0:
+ <font color=red size=1>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.
+</font>
+* So, <font color='darkgreen'>'''TF1.15 + CUDA 10.0 might work with GeForce GTX 1080 Ti (compute capability 6.1)'''</font>
+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)
Oleg
Quad stereo tensorflow eclipse
← Older revision
Revision as of 21:55, 27 December 2019
(10 intermediate revisions by the same user not shown)Line 2:
Line 2:
* Install Eclipse * Install Eclipse
* Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel] * Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel]
−<font color='tomato'>'''Note: if the project is updated/pulled outside Eclipse - need manual refresh'''</font>+<font color='red'>'''NOTE: if project is updated/pulled outside Eclipse - might need a manual refresh'''</font>
+* TF version is pulled from pom.xml
+* Trained TF model for EO sensors is auto-downloaded - [https://community.elphel.com/files/quad-stereo/ml/trained_model_v1.0.zip 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:
+<font size='1'>
+ <?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>
+</font>
+* 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.
+ <font size=1 color=red>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...</font>
+
+* TF 1.15 and CUDA 10.0 require GPU compute capability = 6.0, GeForce GTX 750Ti is 5.0:
+ <font color=red size=1>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.
+</font>
+* So, <font color='darkgreen'>'''TF1.15 + CUDA 10.0 might work with GeForce GTX 1080 Ti (compute capability 6.1)'''</font>
Oleg
Quad stereo tensorflow eclipse
← Older revision
Revision as of 20:32, 27 December 2019
(7 intermediate revisions by the same user not shown)Line 2:
Line 2:
* Install Eclipse * Install Eclipse
* Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel] * Clone and Import [https://git.elphel.com/Elphel/imagej-elphel imagej-elphel]
−<font color='tomato'>'''Note: if the project is updated/pulled outside Eclipse - need manual refresh'''</font>+<font color='red'>'''NOTE: if project is updated/pulled outside Eclipse - might need a manual refresh'''</font>
+* TF version is pulled from pom.xml
+* Trained TF model for EO sensors is auto-downloaded - [https://community.elphel.com/files/quad-stereo/ml/trained_model_v1.0.zip 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:
+<font size='1'>
+ <?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>
+</font>
+* Updaed 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.
+ <font size=1 color=red>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...</font>
Oleg
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