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NVIDIA / DIGITS

Deep Learning GPU Training System
https://developer.nvidia.com/digits
BSD 3-Clause "New" or "Revised" License
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DIGITS 6.0 /usr/bin/python: No module named digits #1973

Open jstromsoe opened 6 years ago

jstromsoe commented 6 years ago

1. Issue or feature description

Problem while trying to download data for digits to run using the normal python scripts.

When running the command I get an error that it seems like some folks have had (see issue #1146) but that I am unable to solve because I am using the latest and greatest version of DIGITS (not an old one).

2. Steps to reproduce the issue

Commands Run: python -m digits.download_data mnist ~/mnist

/usr/bin/python: No module named digits

3. Information to attach (optional if deemed irrelevant)

==============NVSMI LOG==============

Timestamp : Thu Feb 22 11:29:03 2018 Driver Version : 390.30

Attached GPUs : 1 GPU 00000000:01:00.0 Product Name : Quadro K2000M Product Brand : Quadro Display Mode : Disabled Display Active : Disabled Persistence Mode : Disabled Accounting Mode : Disabled Accounting Mode Buffer Size : 1920 Driver Model Current : N/A Pending : N/A Serial Number : N/A GPU UUID : GPU-6d22ea38-f611-8d8d-148e-00d8d3c80bac Minor Number : 0 VBIOS Version : 80.07.52.00.18 MultiGPU Board : No Board ID : 0x100 GPU Part Number : N/A Inforom Version Image Version : N/A OEM Object : N/A ECC Object : N/A Power Management Object : N/A GPU Operation Mode Current : N/A Pending : N/A GPU Virtualization Mode Virtualization mode : None PCI Bus : 0x01 Device : 0x00 Domain : 0x0000 Device Id : 0x0FFB10DE Bus Id : 00000000:01:00.0 Sub System Id : 0x153E1028 GPU Link Info PCIe Generation Max : 2 Current : 2 Link Width Max : 16x Current : 16x Bridge Chip Type : N/A Firmware : N/A Replays since reset : 0 Tx Throughput : N/A Rx Throughput : N/A Fan Speed : N/A Performance State : P0 Clocks Throttle Reasons Idle : Not Active Applications Clocks Setting : Not Active SW Power Cap : Not Active HW Slowdown : Not Active HW Thermal Slowdown : N/A HW Power Brake Slowdown : N/A Sync Boost : Not Active SW Thermal Slowdown : Not Active Display Clock Setting : Not Active FB Memory Usage Total : 1999 MiB Used : 387 MiB Free : 1612 MiB BAR1 Memory Usage Total : 256 MiB Used : 5 MiB Free : 251 MiB Compute Mode : Default Utilization Gpu : 0 % Memory : 0 % Encoder : 0 % Decoder : 0 % Encoder Stats Active Sessions : 0 Average FPS : 0 Average Latency : 0 Ecc Mode Current : N/A Pending : N/A ECC Errors Volatile Single Bit
Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Double Bit
Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Aggregate Single Bit
Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Double Bit
Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Retired Pages Single Bit ECC : N/A Double Bit ECC : N/A Pending : N/A Temperature GPU Current Temp : 40 C GPU Shutdown Temp : 104 C GPU Slowdown Temp : 96 C GPU Max Operating Temp : 91 C Memory Current Temp : N/A Memory Max Operating Temp : N/A Power Readings Power Management : N/A Power Draw : N/A Power Limit : N/A Default Power Limit : N/A Enforced Power Limit : N/A Min Power Limit : N/A Max Power Limit : N/A Clocks Graphics : 465 MHz SM : 465 MHz Memory : 900 MHz Video : 540 MHz Applications Clocks Graphics : N/A Memory : N/A Default Applications Clocks Graphics : N/A Memory : N/A Max Clocks Graphics : 745 MHz SM : 745 MHz Memory : 900 MHz Video : 540 MHz Max Customer Boost Clocks Graphics : N/A Clock Policy Auto Boost : N/A Auto Boost Default : N/A Processes Process ID : 984 Type : G Name : /usr/lib/xorg/Xorg Used GPU Memory : 169 MiB Process ID : 1725 Type : G Name : compiz Used GPU Memory : 63 MiB Process ID : 2640 Type : G Name : /opt/google/chrome/chrome --type=gpu-process --field-trial-handle=2914169424235169759,1377988754466863182,131072 --enable-crash-reporter=4084dc82-63cd-419f-ada2-304c595720b9, --gpu-preferences=GAAAAAAAAAAAAQAAAQAAAAAAAAAAAGAA --gpu-vendor-id=0x10de --gpu-device-id=0x0ffb --gpu-driver-vendor=Nvidia --gpu-driver-version=390.30 --gpu-driver-date --gpu-secondary-vendor-ids=0x8086 --gpu-secondary-device-ids=0x0166 --gpu-active-vendor-id=0x8086 --gpu-active-device-id=0x0166 --enable-crash-reporter=4084dc82-63cd-419f-ada2-304c595720b9, --service-request-channel-token=A228BB2FA4CD2D4280264799E62E9A86 Used GPU Memory : 122 MiB Process ID : 4248 Type : C Name : python Used GPU Memory : 14 MiB

dpkg -l 'nvidia' Desired=Unknown/Install/Remove/Purge/Hold | Status=Not/Inst/Conf-files/Unpacked/halF-conf/Half-inst/trig-aWait/Trig-pend |/ Err?=(none)/Reinst-required (Status,Err: uppercase=bad) ||/ Name Version Architecture Description +++-==============-============-============-================================= ii libnvidia-cont 1.0.0~alpha. amd64 NVIDIA container runtime library ii libnvidia-cont 1.0.0~alpha. amd64 NVIDIA container runtime library un nvidia-common (no description available) ii nvidia-contain 1.1.1+docker amd64 NVIDIA container runtime un nvidia-cuda-de (no description available) un nvidia-docker (no description available) ii nvidia-docker2 2.0.2+docker all nvidia-docker CLI wrapper un nvidia-libopen (no description available) ii nvidia-modprob 384.103-0ubu amd64 Load the NVIDIA kernel driver and ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime

version: 1.0.0 build date: 2018-01-11T00:16+00:00 build revision: 4a618459e8ba522d834bb2b4c665847fae8ce0ad build compiler: gcc-5 5.4.0 20160609 build flags: -D_GNU_SOURCE -D_FORTIFY_SOURCE=2 -DNDEBUG -std=gnu11 -O2 -g -fdata-sections -ffunction-sections -fstack-protector -fno-strict-aliasing -fvisibility=hidden -Wall -Wextra -Wcast-align -Wpointer-arith -Wmissing-prototypes -Wnonnull -Wwrite-strings -Wlogical-op -Wformat=2 -Wmissing-format-attribute -Winit-self -Wshadow -Wstrict-prototypes -Wunreachable-code -Wconversion -Wsign-conversion -Wno-unknown-warning-option -Wno-format-extra-args -Wno-gnu-alignof-expression -Wl,-zrelro -Wl,-znow -Wl,-zdefs -Wl,--gc-sections

ADDITIONAL INFO: Hey all, pretty new to DIGITS but with at little help from @flx42 I got it installed and running in a docker container. That being said I wanted to go through the walkthrough example much like others have done , using DIGITS 6.0 but when I run the first bit of python code I get the same error message as in this thread.

python -m digits.download_data mnist ~/mnist

/usr/bin/python: No module named digits

I realize the reason that I get this error is because indeed I do not have the python tools in the DIGITS repo because I installed everything in docker. NOW before I just go and clone the whole thing which is what I imagine folks did if they built it from source somewhere in git just so I can use the Python tools my question is:

Is there a way that folks who went the Docker route are supposed to take advantage of the tools in the repo ? Specifically this one for the walkthrough?

Confession: I could be really confused and perhaps somewhere in Docker there is an obvious way for me to use the Python tools in this repo, just not experienced enough with this to know.

AlexanderPatuk commented 6 years ago

Just add Digits to your PATH DIGITS_ROOT=~/digits

sanja7s commented 6 years ago

How is that the DIGITS_ROOT ? I have the same problem. But there is no folder ~/digits after the successful installation in my case...

jstromsoe commented 6 years ago

Did you install via Docker? If so the entire installation is essentially jailed in the docket container so the tools are in the docket container. There are several ways to deal with this, I simply cloned the entire repo into a different folder to be able to use the python tools on my host machine, leaving everything in the container alone. You would also in that case have to map a folder to the docket container from your host machine to dump the training data in. If you need real access to the container data structure itself, there are ways to ssh etc... into it, Google should help there.

Jeremy

On Fri, Mar 9, 2018 at 01:10 Sanja S notifications@github.com wrote:

How is that the DIGITS_ROOT ? I have the same problem. But there is no folder ~/digits after the successful installation in my case...

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/NVIDIA/DIGITS/issues/1973#issuecomment-371755900, or mute the thread https://github.com/notifications/unsubscribe-auth/AXnnDh8LAFKmjeqnF_-SqxHF0ukxUsqcks5tckcagaJpZM4SP3K7 .

--

Sincerely,

Jeremy Home Email: jstromsoe@gmail.com

sanja7s commented 6 years ago

Thanks a lot, Jeremy. That was helpful. For now, I am using ssh onto the docker container, as suggested here: http://docs.nvidia.com/deeplearning/digits/digits-user-guide/index.html

docker exec -it digits-17.04 bash

after that, python commands will work from inside the container.

piaoling199 commented 6 years ago

sudo gedit ~/.bashrc add /home/nvidia/digits(your digits home) into PYTHONPATH like this export PYTHONPATH=/home/nvidia/caffe/python:$PYTHONPATH change to export PYTHONPATH=/home/nvidia/caffe/python:/home/nvidia/digits:$PYTHONPATH