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roflcoopter / viseron

Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.
MIT License
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v1.5.0: AttributeError: 'list' object has no attribute 'rel_contours' #42

Closed akohlsmith closed 4 years ago

akohlsmith commented 4 years ago

I'm seeing this pop up in the log. It doesn't cause the system to stop, but doesn't look like it should be happening either:

Exception in thread Thread-13:
Traceback (most recent call last):
  File "/usr/lib/python3.6/threading.py", line 916, in _bootstrap_inner
    self.run()
  File "/src/viseron/lib/nvr.py", line 502, in run
    self.camera.resolution,
  File "/src/viseron/lib/nvr.py", line 54, in publish_image
    self.config.motion_detection.area,
  File "/src/viseron/lib/helpers.py", line 136, in draw_contours
    for relative_contour, area in zip(contours.rel_contours, contours.contour_areas):
AttributeError: 'list' object has no attribute 'rel_contours'
roflcoopter commented 4 years ago

Yes this is an issue that came with the drawing of motion contours when publish_image: true. I fixed it in my local branch but unfortunately it conflicts with some other changes that i am not quite done with yet.

I am build a new version right now but it is taking forever to compile som new dependencies on the RPi. I will publish this to dev tomorrow. It will include some changes which are not quite finished yet so there might be some untested code, but nothing that should break existing setups.

roflcoopter commented 4 years ago

I have pushed all images dev tags so if you grab this one this error should be resolved. The configuration validators might be a bit more strict now so let me know if you bump into any problems.

I will release a beta soon where all these changes are explained

akohlsmith commented 4 years ago

Thank you, I appreciate it.

I tried pulling :dev and running it but there are just too many regressions (object_detection debugging, area no longer in percent, etc.) that I can't really test it, so I've disabled the MQTT image push for the time being. I did pull :latest and there were updates there as well, so we'll see how this one goes. This is really exciting software to work with, I'm very happy I am able to test it out!

roflcoopter commented 4 years ago

Strange, something went wrong with the push to docker-hub so you got an older version.

I probably asked you before but cant remember, which image are you using?

akohlsmith commented 4 years ago

I'm using roflcoopter/viseron-vaapi:latest; docker images shows the ID as 993e09059cd6 (not sure if that's a repo commit number or something unique to my system).

roflcoopter commented 4 years ago

Yeah i verified, all the other three images were pushed correctly except the vaapi one. It is pushed now. One thing to note tho is i have changed the default model to being YOLOv3 instead of YOLOv3 tiny if you are using Darknet. This means the CPU usage will be higher, but the detection accurace is much higher.

I will release a beta later tonight so you might want to wanna wait for that

akohlsmith commented 4 years ago

Is there a delay between when you push to docker.io and when we can pull it? I just did a docker pull roflcoopter/viseron:latest and it said I'm already there (also tried for viseron-vaapi:latest and the :dev variants of both).

akohlsmith commented 4 years ago

re: YOLOv3 vs tiny: no worries. I'm curious why OpenCL isn't using the (i5's built in) GPU. I see

/root/opencv-master/modules/dnn/src/dnn.cpp (1404) setUpNet DNN: OpenCL target is not supported with current OpenCL device (tested with GPUs only), switching to CPU.

the first time that the object detector starts up.

roflcoopter commented 4 years ago

Is there a delay between when you push to docker.io and when we can pull it? I just did a docker pull roflcoopter/viseron:latest and it said I'm already there (also tried for viseron-vaapi:latest and the :dev variants of both).

latest tag is only updated with stable releases, not when i push to dev tag. There shouldnt be any delay.

roflcoopter commented 4 years ago

re: YOLOv3 vs tiny: no worries. I'm curious why OpenCL isn't using the (i5's built in) GPU. I see

/root/opencv-master/modules/dnn/src/dnn.cpp (1404) setUpNet DNN: OpenCL target is not supported with current OpenCL device (tested with GPUs only), switching to CPU.

the first time that the object detector starts up.

Hmm interesting. Is that new or has it always been like that for you?

akohlsmith commented 4 years ago

It's always been like that. This is a Dell OptiPlex 9020 with 16GB of RAM and an i5-4570S.

roflcoopter commented 4 years ago

What does your docker run/docker-compose look like?

akohlsmith commented 4 years ago 
docker run --rm -v /home/andrew/visdata/recordings:/recordings -v /home/andrew/visdata/config:/config -v /etc/localtime:/etc/localtime:ro --name viseron --device /dev/dri roflcoopter/viseron-vaapi:dev

The vaapi stuff is working fine with ffmpeg. Output from vainfo that (if it is helpful):

$ docker exec -it 4a94c332e821 vainfo
error: XDG_RUNTIME_DIR not set in the environment.
error: can't connect to X server!
libva info: VA-API version 1.1.0
libva info: va_getDriverName() returns 0
libva info: Trying to open /usr/lib/x86_64-linux-gnu/dri/i965_drv_video.so
libva info: Found init function __vaDriverInit_1_1
libva info: va_openDriver() returns 0
vainfo: VA-API version: 1.1 (libva 2.9.0.pre1)
vainfo: Driver version: Intel i965 driver for Intel(R) Haswell Desktop - 2.1.0
vainfo: Supported profile and entrypoints
      VAProfileMPEG2Simple            : VAEntrypointVLD
      VAProfileMPEG2Simple            : VAEntrypointEncSlice
      VAProfileMPEG2Main              : VAEntrypointVLD
      VAProfileMPEG2Main              : VAEntrypointEncSlice
      VAProfileH264ConstrainedBaseline: VAEntrypointVLD
      VAProfileH264ConstrainedBaseline: VAEntrypointEncSlice
      VAProfileH264Main               : VAEntrypointVLD
      VAProfileH264Main               : VAEntrypointEncSlice
      VAProfileH264High               : VAEntrypointVLD
      VAProfileH264High               : VAEntrypointEncSlice
      VAProfileH264MultiviewHigh      : VAEntrypointVLD
      VAProfileH264MultiviewHigh      : VAEntrypointEncSlice
      VAProfileH264StereoHigh         : VAEntrypointVLD
      VAProfileH264StereoHigh         : VAEntrypointEncSlice
      VAProfileVC1Simple              : VAEntrypointVLD
      VAProfileVC1Main                : VAEntrypointVLD
      VAProfileVC1Advanced            : VAEntrypointVLD
      VAProfileNone                   : VAEntrypointVideoProc
      VAProfileJPEGBaseline           : VAEntrypointVLD
roflcoopter commented 4 years ago

OpenCL and VA-API are two separate things. Can you show me the output of this command? docker exec -it 4a94c332e821 clinfo

akohlsmith commented 4 years ago

The output of that is curious:

$ docker exec -it 4a94c332e821 clinfo
Number of platforms                               0

If I run clinfo on the host (NOT in the container) I get all kinds of output. That must mean I'm not passing whatever OpenCL needs into the container, right?

roflcoopter commented 4 years ago

Interesting! Yes, exactly. Whats the output of ls -al /dev/dri on the host?

akohlsmith commented 4 years ago 
$ ls -al /dev/dri
total 0
drwxr-xr-x   3 root root       100 Sep 28 17:20 .
drwxr-xr-x  21 root root      4320 Sep 29 00:43 ..
drwxr-xr-x   2 root root        80 Sep 28 17:20 by-path
crw-rw-rw-+  1 root root  226,   0 Sep 28 17:20 card0
crw-rw-rw-+  1 root video 226, 128 Sep 28 17:20 renderD128

What's interesting is that ffmpeg is using /dev/dri/renderD128 for all of its stuff (encode and decode) without spitting out any errors; Is OpenCL perhaps expecting exclusive access to the device?

roflcoopter commented 4 years ago

No its not, im running ffmpeg with vaapi and OpenCV with OpenCL with no issues. Something else must be acting up.

akohlsmith commented 4 years ago

With a little luck I'll have a coral.ai PCIe board installed, it'll be interesting to see if the kernel driver automatically creates the device that OpenCL can use natively (re: #41).

What does your docker run or docker-compose look like? Are you running -vaapi? I noticed that if I run the viseron (not -vaapi) container then vainfo still gives correct output, but the clinfo isn't found at all.

I also found this on https://github.com/pkienzle/opencl_docker:

The official Intel drivers do not recognize the Intel GPU from within the container. The open source beignet driver on Ubuntu is able to see it if the /dev/dri device is forwarded to the docker container. It is not included in this container because it interferes with the other drivers on the system.

Which GPU do you use?

roflcoopter commented 4 years ago

No i am running the cuda image, but that one also installs the OpenCL packages.

And when i run the vaapi image OpenCL works for me aswell, so im not sure i trust the statement from the repository you linked. This is hard for me to assist with since it seems hardware related.

Just a s a test, if you try the beignet image linked in that repository, does clinfo work?

akohlsmith commented 4 years ago

It works with chihchun/opencl-beignet:

$ docker run --rm --device /dev/dri chihchun/opencl-beignet clinfo
Number of platforms                               1
  Platform Name                                   Intel Gen OCL Driver
  Platform Vendor                                 Intel
  Platform Version                                OpenCL 1.2 beignet 1.1.2
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_spir cl_khr_icd
  Platform Extensions function suffix             Intel

  Platform Name                                   Intel Gen OCL Driver
Number of devices                                 1
  Device Name                                     Intel(R) HD Graphics Haswell GT2 Desktop
  Device Vendor                                   Intel
  Device Vendor ID                                0x8086
  Device Version                                  OpenCL 1.2 beignet 1.1.2
  Driver Version                                  1.1.2
  Device OpenCL C Version                         OpenCL C 1.2 beignet 1.1.2
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               20
  Max clock frequency                             1000MHz
  Device Partition                                (core)
    Max number of sub-devices                     1
    Supported partition types                     None, None, None
  Max work item dimensions                        3
  Max work item sizes                             512x512x512
  Max work group size                             512
  Preferred work group size multiple              16
  Preferred / native vector sizes
    char                                                16 / 8
    short                                                8 / 8
    int                                                  4 / 4
    long                                                 2 / 2
    half                                                 0 / 8        (n/a)
    float                                                4 / 4
    double                                               0 / 2        (n/a)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 No
    Round to infinity                             No
    IEEE754-2008 fused multiply-add               No
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Double-precision Floating-point support         (n/a)
  Address bits                                    32, Little-Endian
  Global memory size                              2147483648 (2GiB)
  Error Correction support                        No
  Max memory allocation                           1073741824 (1024MiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        8192
  Global Memory cache line                        64 bytes
  Image support                                   Yes
    Max number of samplers per kernel             16
    Max size for 1D images from buffer            65536 pixels
    Max 1D or 2D image array size                 2048 images
    Max 2D image size                             8192x8192 pixels
    Max 3D image size                             8192x8192x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Global
  Local memory size                               65536 (64KiB)
  Max constant buffer size                        134217728 (128MiB)
  Max number of constant args                     8
  Max size of kernel argument                     1024
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Prefer user sync for interop                    Yes
  Profiling timer resolution                      80ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            Yes
    SPIR versions                                 1.2
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels                                __cl_copy_region_align4;__cl_copy_region_align16;__cl_cpy_region_unalign_same_offset;__cl_copy_region_unalign_dst_offset;__cl_copy_region_unalign_src_offset;__cl_copy_buffer_rect;__cl_copy_image_1d_to_1d;__cl_copy_image_2d_to_2d;__cl_copy_image_3d_to_2d;__cl_copy_image_2d_to_3d;__cl_copy_image_3d_to_3d;__cl_copy_image_2d_to_buffer;__cl_copy_image_3d_to_buffer;__cl_copy_buffer_to_image_2d;__cl_copy_buffer_to_image_3d;__cl_fill_region_unalign;__cl_fill_region_align2;__cl_fill_region_align4;__cl_fill_region_align8_2;__cl_fill_region_align8_4;__cl_fill_region_align8_8;__cl_fill_region_align8_16;__cl_fill_region_align128;__cl_fill_image_1d;__cl_fill_image_1d_array;__cl_fill_image_2d;__cl_fill_image_2d_array;__cl_fill_image_3d;
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Device Extensions                               cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_spir cl_khr_icd

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Intel Gen OCL Driver
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [Intel]
  clCreateContext(NULL, ...) [default]            Success [Intel]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (1)
    Platform Name                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics Haswell GT2 Desktop
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (1)
    Platform Name                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics Haswell GT2 Desktop

ICD loader properties
  ICD loader Name                                 OpenCL ICD Loader
  ICD loader Vendor                               OCL Icd free software
  ICD loader Version                              2.2.9
  ICD loader Profile                              OpenCL 2.1

This works whether Viseron is running or not.

roflcoopter commented 4 years ago

I wonder if this is because the docker image is built on my machine, thus the installed OpenCL is not supported on your machine.

Is this an older CPU? From what i could gather, Intels OpenCL (which is included in the image) is not supported by Haswell based GPUs. Beignet OpenCL however is an open-source alternative which is a bit slower than Intels variant

akohlsmith commented 4 years ago

That's a very good question - I'm no stranger to building software, but am an utter newbie when it comes to docker. The system is an ultra-small form factor Dell Optiplex 9020 with 16GB of RAM and a 2.9GHz i5-4570S, so it's Haswell, but opencl outside of the container detects it fine. The version of opencl-icd inside and outside the container appears to be the same as well.

$ apt show ocl-icd-libopencl1
Package: ocl-icd-libopencl1
Version: 2.2.11-1ubuntu1

$ apt show clinfo
Package: clinfo
Version: 2.2.18.03.26-1

$ clinfo -v
clinfo version 2.2.18.03.26

$ docker exec -it 8e2818866320 apt show ocl-icd-libopencl1
Package: ocl-icd-libopencl1
Version: 2.2.11-1ubuntu1

$ docker exec -it 8e2818866320 apt show clinfo
Package: clinfo
Version: 2.2.18.03.26-1

$ docker exec -it 8e2818866320 clinfo -v
clinfo version 2.2.18.03.26
roflcoopter commented 4 years ago

Thats really only the version of clinfo, which is not tied to the OpenCL version

OpenCL is compiled from source in the image and propably overrides the one from apt. This answer on stackoverflow sums the different versions up quite well.

I wonder what happens if you try to build it yourself. Can you exec into the container and run the following to reinstall OpenCL from source and see what happens?

mkdir /opencl &&\
        cd /opencl && \
        wget https://github.com/intel/compute-runtime/releases/download/19.31.13700/intel-gmmlib_19.2.3_amd64.deb --progress=bar:force:noscroll && \
        wget https://github.com/intel/compute-runtime/releases/download/19.31.13700/intel-igc-core_1.0.10-2364_amd64.deb --progress=bar:force:noscroll && \
        wget https://github.com/intel/compute-runtime/releases/download/19.31.13700/intel-igc-opencl_1.0.10-2364_amd64.deb --progress=bar:force:noscroll && \
        wget https://github.com/intel/compute-runtime/releases/download/19.31.13700/intel-opencl_19.31.13700_amd64.deb --progress=bar:force:noscroll && \
        wget https://github.com/intel/compute-runtime/releases/download/19.31.13700/intel-ocloc_19.31.13700_amd64.deb --progress=bar:force:noscroll && \
        dpkg -i *.deb && \
        rm -R /opencl
roflcoopter commented 4 years ago

And maybe, just as a test, can you run the official Intel OpenCL image and see if this works? docker run -it --device /dev/dri:/dev/dri --rm docker.io/intelopencl/intel-opencl:ubuntu-18.04-ppa clinfo

If not I have to create a separate container for older CPUs like yours.

akohlsmith commented 4 years ago

I think you're on to something:

$ docker run -it --device /dev/dri:/dev/dri --rm docker.io/intelopencl/intel-opencl:ubuntu-18.04-ppa clinfo
Number of platforms                               0
akohlsmith commented 4 years ago

I had to install the latest .debs a little differently since the container does not have wget, and I couldn't install it via apt for some reason. I just downloaded them in the host and ran the container with -v /path/to/clinfo:/clinfo and then dpkg -i'd it in the container. Same result: 0 platforms.

I think that you've correctly identified the issue in that the official Intel CL does not seem to work with older GPUs inside a container. It does, however, seem to work fine outside of the container, which is weird.

roflcoopter commented 4 years ago

Whats the clinfo output on the host?

akohlsmith commented 4 years ago

This is the output from the host:

Number of platforms                               1
  Platform Name                                   Intel(R) CPU Runtime for OpenCL(TM) Applications
  Platform Vendor                                 Intel(R) Corporation
  Platform Version                                OpenCL 2.1 LINUX
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_khr_icd cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer cl_intel_vec_len_hint
  Platform Host timer resolution                  1ns
  Platform Extensions function suffix             INTEL

  Platform Name                                   Intel(R) CPU Runtime for OpenCL(TM) Applications
Number of devices                                 1
  Device Name                                     Intel(R) Core(TM) i5-4570S CPU @ 2.90GHz
  Device Vendor                                   Intel(R) Corporation
  Device Vendor ID                                0x8086
  Device Version                                  OpenCL 2.1 (Build 0)
  Driver Version                                  18.1.0.0920
  Device OpenCL C Version                         OpenCL C 2.0
  Device Type                                     CPU
  Device Profile                                  FULL_PROFILE
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Max compute units                               4
  Max clock frequency                             2900MHz
  Device Partition                                (core)
    Max number of sub-devices                     4
    Supported partition types                     by counts, equally, by names (Intel)
  Max work item dimensions                        3
  Max work item sizes                             8192x8192x8192
  Max work group size                             8192
  Preferred work group size multiple              128
  Max sub-groups per work group                   1
  Preferred / native vector sizes
    char                                                 1 / 32
    short                                                1 / 16
    int                                                  1 / 8
    long                                                 1 / 4
    half                                                 0 / 0        (n/a)
    float                                                1 / 8
    double                                               1 / 4        (cl_khr_fp64)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 No
    Round to infinity                             No
    IEEE754-2008 fused multiply-add               No
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Double-precision Floating-point support         (cl_khr_fp64)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
  Address bits                                    64, Little-Endian
  Global memory size                              16721399808 (15.57GiB)
  Error Correction support                        No
  Max memory allocation                           4180349952 (3.893GiB)
  Unified memory for Host and Device              Yes
  Shared Virtual Memory (SVM) capabilities        (core)
    Coarse-grained buffer sharing                 Yes
    Fine-grained buffer sharing                   Yes
    Fine-grained system sharing                   Yes
    Atomics                                       Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Preferred alignment for atomics
    SVM                                           64 bytes
    Global                                        64 bytes
    Local                                         0 bytes
  Max size for global variable                    65536 (64KiB)
  Preferred total size of global vars             65536 (64KiB)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        262144 (256KiB)
  Global Memory cache line size                   64 bytes
  Image support                                   Yes
    Max number of samplers per kernel             480
    Max size for 1D images from buffer            261271872 pixels
    Max 1D or 2D image array size                 2048 images
    Base address alignment for 2D image buffers   64 bytes
    Pitch alignment for 2D image buffers          64 pixels
    Max 2D image size                             16384x16384 pixels
    Max 3D image size                             2048x2048x2048 pixels
    Max number of read image args                 480
    Max number of write image args                480
    Max number of read/write image args           480
  Max number of pipe args                         16
  Max active pipe reservations                    65535
  Max pipe packet size                            1024
  Local memory type                               Global
  Local memory size                               32768 (32KiB)
  Max number of constant args                     480
  Max constant buffer size                        131072 (128KiB)
  Max size of kernel argument                     3840 (3.75KiB)
  Queue properties (on host)
    Out-of-order execution                        Yes
    Profiling                                     Yes
    Local thread execution (Intel)                Yes
  Queue properties (on device)
    Out-of-order execution                        Yes
    Profiling                                     Yes
    Preferred size                                4294967295 (4GiB)
    Max size                                      4294967295 (4GiB)
  Max queues on device                            4294967295
  Max events on device                            4294967295
  Prefer user sync for interop                    No
  Profiling timer resolution                      1ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            Yes
    Sub-group independent forward progress        No
    IL version                                    SPIR-V_1.0
    SPIR versions                                 1.2
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels
  Device Extensions                               cl_khr_icd cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer cl_intel_vec_len_hint

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  No platform
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   No platform
  clCreateContext(NULL, ...) [default]            No platform
  clCreateContext(NULL, ...) [other]              Success [INTEL]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  No platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  No platform
roflcoopter commented 4 years ago

The error that this issue was originally about is now fixed in latest beta