TF 2.4.0 build from source gets InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid.

Nvidia-SMI command issued from inside the container
NVIDIA-SMI 450.57       Driver Version: 450.57       CUDA Version: ERR!     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  Off  | 00000000:01:00.0 Off |                  N/A |
|  0%   33C    P8     6W / 180W |    193MiB /  8117MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|============================================================================
I am running Ubuntu 20.04. I followed the instructions to Build from source:
After I compiled TF inside the container, I committed and saved it.
I run the following commands to load the image and execute jupyter notebook:
docker run --gpus all --ipc="host" -it -w /tensorflow -v $PWD:/mnt -p 8888:8888 -e HOST_PERMS="$(id -u):$(id -g)" tensorflow/tensorflow:from-src2 bash
export LD_LIBRARY_PATH=“/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/include/x64_64-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64”
pip install jupyter
pip install jupyter_http_over_ws
jupyter serverextension enable --py jupyter_http_over_ws
jupyter notebook --no-browser --notebook-dir=/mnt/notebooks --ip=<IP_ADDRESS>  --debug --NotebookApp.allow_origin='https://www.example.com' --NotebookApp.allow_remote_access=True --allow-root
This gets me a running notebook server.
I try to run the tensorflow-tutorials/text_classification.ipynb file
When I ran the:
raw_train_ds = tf.keras.preprocessing.text_dataset_from_directory(
'aclImdb/train',
batch_size=batch_size,
validation_split=0.2,
subset='training',
seed=seed)
In the jupyter notebook, I get:
TypeError: Could not build a TypeSpec for ['aclImdb/train/neg/4932_4.txt',
[there follows many pages of text similar to the above]...
Then I get the following
**with type list
During handling of the above exception, another exception occurred:**
InternalError                             Traceback (most recent call last)
 in
7     validation_split=0.2,
8     subset='training',
----> 9     seed=seed)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/preprocessing/text_dataset.py in text_dataset_from_directory(directory, labels, label_mode, class_names, batch_size, max_length, shuffle, seed, validation_split, subset, follow_links)
159       label_mode=label_mode,
160       num_classes=len(class_names),
--> 161       max_length=max_length)
162   if shuffle:
163     # Shuffle locally at each iteration
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/preprocessing/text_dataset.py in paths_and_labels_to_dataset(file_paths, labels, label_mode, num_classes, max_length)
175                                 max_length):
176   """Constructs a dataset of text strings and labels."""
--> 177   path_ds = dataset_ops.Dataset.from_tensor_slices(file_paths)
178   string_ds = path_ds.map(
179       lambda x: path_to_string_content(x, max_length))
/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/ops/dataset_ops.py in from_tensor_slices(tensors)
680       Dataset: A Dataset.
681     """
--> 682     return TensorSliceDataset(tensors)
683
684   class _GeneratorState(object):
/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/ops/dataset_ops.py in init(self, element)
2999   def init(self, element):
3000     """See Dataset.from_tensor_slices() for details."""
-> 3001     element = structure.normalize_element(element)
3002     batched_spec = structure.type_spec_from_value(element)
3003     self._tensors = structure.to_batched_tensor_list(batched_spec, element)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/util/structure.py in normalize_element(element)
96         # the value. As a fallback try converting the value to a tensor.
97         normalized_components.append(
---> 98             ops.convert_to_tensor(t, name="component_%d" % i))
99       else:
100         if isinstance(spec, sparse_tensor.SparseTensorSpec):
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
1524
1525     if ret is None:
-> 1526       ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1527
1528     if ret is NotImplemented:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
337                                          as_ref=False):
338   _ = as_ref
--> 339   return constant(v, dtype=dtype, name=name)
340
341
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name)
263   """
264   return _constant_impl(value, dtype, shape, name, verify_shape=False,
--> 265                         allow_broadcast=True)
266
267
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
274       with trace.Trace("tf.constant"):
275         return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
--> 276     return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
277
278   g = ops.get_default_graph()
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
299 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
300   """Implementation of eager constant."""
--> 301   t = convert_to_eager_tensor(value, ctx, dtype)
302   if shape is None:
303     return t
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
95     except AttributeError:
96       dtype = dtypes.as_dtype(dtype).as_datatype_enum
---> 97   ctx.ensure_initialized()
98   return ops.EagerTensor(value, ctx.device_name, dtype)
99
/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/context.py in ensure_initialized(self)
547         if self._use_tfrt is not None:
548           pywrap_tfe.TFE_ContextOptionsSetTfrt(opts, self._use_tfrt)
--> 549         context_handle = pywrap_tfe.TFE_NewContext(opts)
550       finally:
551         pywrap_tfe.TFE_DeleteContextOptions(opts)
InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid.
This from /tensorflow_src/.bazelrc : release_gpu_common --action_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
I believe the GeForce 1070 is sm_61 compute level.
Some software versions
gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Python 3.6.9
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
Please make sure that this is a bug. As per our
GitHub Policy,
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary):
TensorFlow version (use command below):
Python version:
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory:

You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with:

TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior
Describe the expected behavior
Standalone code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.
Other info / logs Include any logs or source code that would be helpful to
diagnose the problem. If including tracebacks, please include the full
traceback. Large logs and files should be attached.
I will attach the full .bazelrc file and a piped output of the build from source when I can figure out how to do that. I’m on an iPad now and can copy and paste but can’t seem to figure out how to copy a file to the ipad and then upload to github issue...

BazelRC.txt
I thought I had kept the build pipe around but apparently didn't so don't have that file. If you need any more information please let me know.

Sorry closed the issue when I just wanted to add my comment. I re-opened

I’m using Nvidia-MPS so this is the nvidia-smi from outside the container.
NVIDIA-SMI 450.57       Driver Version: 450.57       CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  Off  | 00000000:01:00.0 Off |                  N/A |
|  0%   32C    P8     6W / 180W |    193MiB /  8117MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 1070    Off  | 00000000:05:00.0 Off |                  N/A |
|  0%   29C    P8     5W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  GeForce GTX 1070    Off  | 00000000:06:00.0 Off |                  N/A |
|  0%   29C    P8     4W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1056      G   /usr/lib/xorg/Xorg                 36MiB |
|    0   N/A  N/A      1501      G   /usr/bin/gnome-shell               15MiB |
|    0   N/A  N/A      2205      C   /usr/bin/python3                  137MiB |
|    1   N/A  N/A      1056      G   /usr/lib/xorg/Xorg                  4MiB |
|    2   N/A  N/A      1056      G   /usr/lib/xorg/Xorg                  4MiB
I only let 1 GPU into the container.

Here’s the trace back from the 1st error (type error)
TypeError                                 Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/util/structure.py in normalize_element(element)
92       try:
---> 93         spec = type_spec_from_value(t, use_fallback=False)
94       except TypeError:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/util/structure.py in type_spec_from_value(element, use_fallback)
465   raise TypeError("Could not build a TypeSpec for %r with type %s" %
--> 466                   (element, type(element).name))
467

This from inside container:
Bazel label: 3.1.0
Ubuntu version: 18.04
c++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
numpy                  1.18.5
protobuf               3.12.2
tensorflow             2.4.0
tensorflow-estimator   2.2.0
tf.version.VERSION = 2.4.0
tf.version.GIT_VERSION = v1.12.1-37438-g6711d96f6c
tf.version.COMPILER_VERSION = 7.5.0
python version: 3.6.9
python compiler version: GCC 8.4.0
In Docker: Yes
Check for Virtual Environment: False
== cuda libs  ===================================================
/usr/local/cuda-10.1/targets/x86_64-linux/lib/libcudart.so.10.1.243
/usr/local/cuda-10.1/targets/x86_64-linux/lib/libcudart_static.a
If you need anything else out of tf_env.txt let me know.

could this be some sort of timeout. I'm running
Jupyter Notebook 6.1.0
When I tried persistence mode on the GPU it seemed to transfer more data before it generated the error. it went from 135MiB of data assigned to python3 at time of error (with persistence mode OFF) to 189MiB of data assigned to Python3 at time of error (with persistence mode ON).

Very strange, when I reran the jupyter server and tried to run the same notebook (a 2nd time) within the same container (but adding a --MappingKernelManager.cull_interval=1200 to the server command. The notebook ran just fine and much faster. I do have persistence mode on... I don’t think the cull-interval had anything to do with it.
Is it possible that the first load of the Nvidia GPU takes a long time because we are loading in some standard NVidia and Tensorflow routines and modules but once they are present in the GPU they no longer have to be loaded (as long as persistence mode is on). That could explain why the first time I ran the text classification notebook it took so long (and ultimately errored off) but the 2nd time it flew right threw that statement.

Here is some other information from the debug run of the jupyter notebook:
2020-08-04 04:45:30.731142: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2020-08-04 04:45:30.731178: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
2020-08-04 04:45:30.731193: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2020-08-04 04:45:30.731244: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2020-08-04 04:45:30.731263: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2020-08-04 04:45:30.731281: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2020-08-04 04:45:30.731295: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7
Seems to be loading some files for cuda 10.1 (libcudart) and others from cuda 10.0 (libcublas, libcufft, libcurand, libcusolver, & libcusparse)
I tried to recreate the sequence that worked last night but can’t seem to get it to work tonight.  Any time I Ctrl-c the jupyter notebook server it seems to clear GPU memory so I get a fresh start. It seems last night it left it alone and I was able to start another jupyter notebook server session and it worked ok the second time I ran it. Sigh, that’s not working at all today.

sorry i updated the wrong incident. Here's the "lshw" command output:
ubuntu-ai
description: Desktop Computer
product: MS-7A62 (Default string)
vendor: MSI
version: 1.0
serial: Default string
width: 64 bits
capabilities: smbios-3.0.0 dmi-3.0.0 smp vsyscall32
configuration: boot=normal chassis=desktop family=Default string sku=Default string uuid=00000000-0000-0000-0000-4CCC6AF7447F
*-core
description: Motherboard
product: Z270 GAMING M3 (MS-7A62)
vendor: MSI
physical id: 0
version: 1.0
serial: H316061861
slot: Default string
*-firmware
description: BIOS
vendor: American Megatrends Inc.
physical id: 0
version: 1.10
date: 02/07/2017
size: 64KiB
capacity: 16MiB
capabilities: pci upgrade shadowing cdboot bootselect socketedrom edd int13floppy1200 int13floppy720 int13floppy2880 int5printscreen int9keyboard int14serial int17printer acpi usb biosbootspecification uefi
*-memory
description: System Memory
physical id: 3c
slot: System board or motherboard
size: 8GiB
*-bank:0
description: [empty]
physical id: 0
slot: ChannelA-DIMM0
*-bank:1
description: DIMM DDR4 Synchronous 2400 MHz (0.4 ns)
product: BLS4G4D240FSB.8FBD2
vendor: 859B
physical id: 1
serial: A624BDFD
slot: ChannelA-DIMM1
size: 4GiB
width: 64 bits
clock: 2400MHz (0.4ns)
*-bank:2
description: [empty]
physical id: 2
slot: ChannelB-DIMM0
*-bank:3
description: DIMM DDR4 Synchronous 2400 MHz (0.4 ns)
product: BLS4G4D240FSB.8FBD2
vendor: 859B
physical id: 3
serial: A624BDFC
slot: ChannelB-DIMM1
size: 4GiB
width: 64 bits
clock: 2400MHz (0.4ns)
*-cache:0
description: L1 cache
physical id: 42
slot: L1 Cache
size: 128KiB
capacity: 128KiB
capabilities: synchronous internal write-back unified
configuration: level=1
*-cache:1
description: L2 cache
physical id: 43
slot: L2 Cache
size: 512KiB
capacity: 512KiB
capabilities: synchronous internal write-back unified
configuration: level=2
*-cache:2
description: L3 cache
physical id: 44
slot: L3 Cache
size: 3MiB
capacity: 3MiB
capabilities: synchronous internal write-back unified
configuration: level=3
*-cpu
description: CPU
product: Intel(R) Pentium(R) CPU G4400 @ 3.30GHz
vendor: Intel Corp.
physical id: 45
bus info: cpu@0
version: Intel(R) Pentium(R) CPU G4400 @ 3.30GHz
serial: To Be Filled By O.E.M.
slot: U3E1
size: 3206MHz
capacity: 4005MHz
width: 64 bits
clock: 100MHz
capabilities: lm fpu fpu_exception wp vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp x86-64 constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave rdrand lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust erms invpcid rdseed smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm arat pln pts hwp hwp_notify hwp_act_window hwp_epp md_clear flush_l1d cpufreq
configuration: cores=2 enabledcores=2 threads=2
*-pci
description: Host bridge
product: Xeon E3-1200 v5/E3-1500 v5/6th Gen Core Processor Host Bridge/DRAM Registers
vendor: Intel Corporation
physical id: 100
bus info: pci@0000:00:00.0
version: 07
width: 32 bits
clock: 33MHz
configuration: driver=skl_uncore
resources: irq:0
*-pci:0
description: PCI bridge
product: Xeon E3-1200 v5/E3-1500 v5/6th Gen Core Processor PCIe Controller (x16)
vendor: Intel Corporation
physical id: 1
bus info: pci@0000:00:01.0
version: 07
width: 32 bits
clock: 33MHz
capabilities: pci pm msi pciexpress normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:120 ioport:e000(size=4096) memory:de000000-df0fffff ioport:c0000000(size=301989888)
*-display
description: VGA compatible controller
product: GP104 [GeForce GTX 1070 Ti]
vendor: NVIDIA Corporation
physical id: 0
bus info: pci@0000:01:00.0
version: a1
width: 64 bits
clock: 33MHz
capabilities: pm msi pciexpress vga_controller bus_master cap_list rom
configuration: driver=nvidia latency=0
resources: irq:137 memory:de000000-deffffff memory:c0000000-cfffffff memory:d0000000-d1ffffff ioport:e000(size=128) memory:c0000-dffff
*-multimedia
description: Audio device
product: GP104 High Definition Audio Controller
vendor: NVIDIA Corporation
physical id: 0.1
bus info: pci@0000:01:00.1
version: a1
width: 32 bits
clock: 33MHz
capabilities: pm msi pciexpress bus_master cap_list
configuration: driver=snd_hda_intel latency=0
resources: irq:17 memory:df080000-df083fff
*-generic:0 UNCLAIMED
description: System peripheral
product: Xeon E3-1200 v5/v6 / E3-1500 v5 / 6th/7th/8th Gen Core Processor Gaussian Mixture Model
vendor: Intel Corporation
physical id: 8
bus info: pci@0000:00:08.0
version: 00
width: 64 bits
clock: 33MHz
capabilities: msi pm cap_list
configuration: latency=0
resources: memory:dd12f000-dd12ffff
*-usb
description: USB controller
product: 200 Series/Z370 Chipset Family USB 3.0 xHCI Controller
vendor: Intel Corporation
physical id: 14
bus info: pci@0000:00:14.0
version: 00
width: 64 bits
clock: 33MHz
capabilities: pm msi xhci bus_master cap_list
configuration: driver=xhci_hcd latency=0
resources: irq:127 memory:dd110000-dd11ffff
*-usbhost:0
product: xHCI Host Controller
vendor: Linux 5.4.0-42-generic xhci-hcd
physical id: 0
bus info: usb@1
logical name: usb1
version: 5.04
capabilities: usb-2.00
configuration: driver=hub slots=16 speed=480Mbit/s
*-usb:0
description: Mouse
product: USB Optical Mouse
vendor: Logitech
physical id: 7
bus info: usb@1:7
version: 72.00
capabilities: usb-2.00
configuration: driver=usbhid maxpower=100mA speed=2Mbit/s
*-usb:1
description: Keyboard
product: USB Keyboard
vendor: Logitech
physical id: 8
bus info: usb@1:8
version: 64.00
capabilities: usb-1.10
configuration: driver=usbhid maxpower=90mA speed=2Mbit/s
*-usbhost:1
product: xHCI Host Controller
vendor: Linux 5.4.0-42-generic xhci-hcd
physical id: 1
bus info: usb@2
logical name: usb2
version: 5.04
capabilities: usb-3.00
configuration: driver=hub slots=10 speed=5000Mbit/s
*-generic:1 UNCLAIMED
description: Signal processing controller
product: 200 Series PCH Thermal Subsystem
vendor: Intel Corporation
physical id: 14.2
bus info: pci@0000:00:14.2
version: 00
width: 64 bits
clock: 33MHz
capabilities: pm msi cap_list
configuration: latency=0
resources: memory:dd12e000-dd12efff
*-communication
description: Communication controller
product: 200 Series PCH CSME HECI #1
vendor: Intel Corporation
physical id: 16
bus info: pci@0000:00:16.0
version: 00
width: 64 bits
clock: 33MHz
capabilities: pm msi bus_master cap_list
configuration: driver=mei_me latency=0
resources: irq:132 memory:dd12d000-dd12dfff
*-sata
description: SATA controller
product: 200 Series PCH SATA controller [AHCI mode]
vendor: Intel Corporation
physical id: 17
bus info: pci@0000:00:17.0
logical name: scsi0
version: 00
width: 32 bits
clock: 66MHz
capabilities: sata msi pm ahci_1.0 bus_master cap_list emulated
configuration: driver=ahci latency=0
resources: irq:131 memory:dd128000-dd129fff memory:dd12c000-dd12c0ff ioport:f050(size=8) ioport:f040(size=4) ioport:f020(size=32) memory:dd12b000-dd12b7ff
*-disk
description: ATA Disk
product: SanDisk SDSSDA12
physical id: 0.0.0
bus info: scsi@0:0.0.0
logical name: /dev/sda
version: 80RL
serial:<PHONE_NUMBER>15
size: 111GiB (120GB)
capabilities: gpt-1.00 partitioned partitioned:gpt
configuration: ansiversion=5 guid=725cc7ba-faa9-4fe5-9e62-6b7b8a0b7aa7 logicalsectorsize=512 sectorsize=512
*-volume:0
description: Windows FAT volume
vendor: mkfs.fat
physical id: 1
bus info: scsi@0:0.0.0,1
logical name: /dev/sda1
logical name: /boot/efi
version: FAT32
serial: 1773-3e94
size: 510MiB
capacity: 511MiB
capabilities: boot fat initialized
configuration: FATs=2 filesystem=fat mount.fstype=vfat mount.options=rw,relatime,fmask=0022,dmask=0022,codepage=437,iocharset=iso8859-1,shortname=mixed,errors=remount-ro state=mounted
*-volume:1
description: EXT4 volume
vendor: Linux
physical id: 2
bus info: scsi@0:0.0.0,2
logical name: /dev/sda2
logical name: /boot
version: 1.0
serial: af28e231-0e6d-41f6-a632-b96cc017ffba
size: 1GiB
capabilities: journaled extended_attributes large_files huge_files dir_nlink recover 64bit extents ext4 ext2 initialized
configuration: created=2020-07-22 19:01:51 filesystem=ext4 lastmountpoint=/boot modified=2020-08-03 17:23:18 mount.fstype=ext4 mount.options=rw,relatime mounted=2020-08-03 17:23:18 state=mounted
*-volume:2
description: EFI partition
physical id: 3
bus info: scsi@0:0.0.0,3
logical name: /dev/sda3
serial: PYSAzy-ypr8-pyaN-oJcD-y4NN-YdMJ-hPwFpv
size: 110GiB
capabilities: lvm2
*-pci:1
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #17
vendor: Intel Corporation
physical id: 1b
bus info: pci@0000:00:1b.0
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:121
*-pci:2
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #19
vendor: Intel Corporation
physical id: 1b.2
bus info: pci@0000:00:1b.2
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:122 memory:df300000-df3fffff
*-usb
description: USB controller
product: ASM2142 USB 3.1 Host Controller
vendor: ASMedia Technology Inc.
physical id: 0
bus info: pci@0000:03:00.0
version: 00
width: 64 bits
clock: 33MHz
capabilities: msi msix pm pciexpress xhci bus_master cap_list
configuration: driver=xhci_hcd latency=0
resources: irq:18 memory:df300000-df307fff
*-usbhost:0
product: xHCI Host Controller
vendor: Linux 5.4.0-42-generic xhci-hcd
physical id: 0
bus info: usb@3
logical name: usb3
version: 5.04
capabilities: usb-2.00
configuration: driver=hub slots=2 speed=480Mbit/s
*-usbhost:1
product: xHCI Host Controller
vendor: Linux 5.4.0-42-generic xhci-hcd
physical id: 1
bus info: usb@4
logical name: usb4
version: 5.04
capabilities: usb-3.10
configuration: driver=hub slots=2 speed=10000Mbit/s
*-pci:3
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #1
vendor: Intel Corporation
physical id: 1c
bus info: pci@0000:00:1c.0
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:123
*-pci:4
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #6
vendor: Intel Corporation
physical id: 1c.5
bus info: pci@0000:00:1c.5
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:124 ioport:d000(size=4096) memory:dc000000-dd0fffff ioport:a0000000(size=301989888)
*-display
description: VGA compatible controller
product: GP104 [GeForce GTX 1070]
vendor: NVIDIA Corporation
physical id: 0
bus info: pci@0000:05:00.0
version: a1
width: 64 bits
clock: 33MHz
capabilities: pm msi pciexpress vga_controller bus_master cap_list rom
configuration: driver=nvidia latency=0
resources: irq:138 memory:dc000000-dcffffff memory:a0000000-afffffff memory:b0000000-b1ffffff ioport:d000(size=128) memory:dd000000-dd07ffff
*-multimedia
description: Audio device
product: GP104 High Definition Audio Controller
vendor: NVIDIA Corporation
physical id: 0.1
bus info: pci@0000:05:00.1
version: a1
width: 32 bits
clock: 33MHz
capabilities: pm msi pciexpress bus_master cap_list
configuration: driver=snd_hda_intel latency=0
resources: irq:18 memory:dd080000-dd083fff
*-pci:5
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #7
vendor: Intel Corporation
physical id: 1c.6
bus info: pci@0000:00:1c.6
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:125 ioport:c000(size=4096) memory:da000000-db0fffff ioport:80000000(size=301989888)
*-display
description: VGA compatible controller
product: GP104 [GeForce GTX 1070]
vendor: NVIDIA Corporation
physical id: 0
bus info: pci@0000:06:00.0
version: a1
width: 64 bits
clock: 33MHz
capabilities: pm msi pciexpress vga_controller bus_master cap_list rom
configuration: driver=nvidia latency=0
resources: irq:139 memory:da000000-daffffff memory:80000000-8fffffff memory:90000000-91ffffff ioport:c000(size=128) memory:db000000-db07ffff
*-multimedia
description: Audio device
product: GP104 High Definition Audio Controller
vendor: NVIDIA Corporation
physical id: 0.1
bus info: pci@0000:06:00.1
version: a1
width: 32 bits
clock: 33MHz
capabilities: pm msi pciexpress bus_master cap_list
configuration: driver=snd_hda_intel latency=0
resources: irq:19 memory:db080000-db083fff
*-pci:6
description: PCI bridge
product: 200 Series PCH PCI Express Root Port #8
vendor: Intel Corporation
physical id: 1c.7
bus info: pci@0000:00:1c.7
version: f0
width: 32 bits
clock: 33MHz
capabilities: pci pciexpress msi pm normal_decode bus_master cap_list
configuration: driver=pcieport
resources: irq:126 ioport:b000(size=4096) memory:df200000-df2fffff
*-network
description: Ethernet interface
product: Killer E2500 Gigabit Ethernet Controller
vendor: Qualcomm Atheros
physical id: 0
bus info: pci@0000:07:00.0
logical name: enp7s0
version: 10
serial: 4c:cc:6a:f7:44:7f
size: 1Gbit/s
capacity: 1Gbit/s
width: 64 bits
clock: 33MHz
capabilities: pm pciexpress msi msix bus_master cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd 1000bt-fd autonegotiation
configuration: autonegotiation=on broadcast=yes driver=alx duplex=full ip=<IP_ADDRESS> latency=0 link=yes multicast=yes port=twisted pair speed=1Gbit/s
resources: irq:19 memory:df200000-df23ffff ioport:b000(size=128)
*-isa
description: ISA bridge
product: 200 Series PCH LPC Controller (Z270)
vendor: Intel Corporation
physical id: 1f
bus info: pci@0000:00:1f.0
version: 00
width: 32 bits
clock: 33MHz
capabilities: isa bus_master
configuration: latency=0
*-memory UNCLAIMED
description: Memory controller
product: 200 Series/Z370 Chipset Family Power Management Controller
vendor: Intel Corporation
physical id: 1f.2
bus info: pci@0000:00:1f.2
version: 00
width: 32 bits
clock: 33MHz (30.3ns)
configuration: latency=0
resources: memory:dd124000-dd127fff
*-multimedia
description: Audio device
product: 200 Series PCH HD Audio
vendor: Intel Corporation
physical id: 1f.3
bus info: pci@0000:00:1f.3
version: 00
width: 64 bits
clock: 33MHz
capabilities: pm msi bus_master cap_list
configuration: driver=snd_hda_intel latency=32
resources: irq:133 memory:dd120000-dd123fff memory:dd100000-dd10ffff
*-serial
description: SMBus
product: 200 Series/Z370 Chipset Family SMBus Controller
vendor: Intel Corporation
physical id: 1f.4
bus info: pci@0000:00:1f.4
version: 00
width: 64 bits
clock: 33MHz
configuration: driver=i801_smbus latency=0
resources: irq:16 memory:dd12a000-dd12a0ff ioport:f000(size=32)
*-pnp00:00
product: PnP device PNP0c02
physical id: 1
capabilities: pnp
configuration: driver=system
*-pnp00:01
product: PnP device PNP0303
physical id: 2
capabilities: pnp
configuration: driver=i8042 kbd
*-pnp00:02
product: PnP device PNP0f03
physical id: 3
capabilities: pnp
configuration: driver=i8042 aux
*-pnp00:03
product: PnP device PNP0501
physical id: 4
capabilities: pnp
configuration: driver=serial
*-pnp00:04
product: PnP device PNP0c02
physical id: 5
capabilities: pnp
configuration: driver=system
*-pnp00:05
product: PnP device PNP0c02
physical id: 6
capabilities: pnp
configuration: driver=system
*-pnp00:06
product: PnP device PNP0b00
physical id: 7
capabilities: pnp
configuration: driver=rtc_cmos
*-pnp00:07
product: PnP device INT3f0d
physical id: 8
capabilities: pnp
configuration: driver=system
*-pnp00:08
product: PnP device PNP0c02
physical id: 9
capabilities: pnp
configuration: driver=system
*-pnp00:09
product: PnP device PNP0c02
physical id: a
capabilities: pnp
configuration: driver=system
*-pnp00:0a
product: PnP device PNP0c02
physical id: b
capabilities: pnp
configuration: driver=system
*-pnp00:0b
product: PnP device PNP0c02
physical id: c
capabilities: pnp
configuration: driver=system
*-power UNCLAIMED
description: To Be Filled By O.E.M.
product: To Be Filled By O.E.M.
vendor: To Be Filled By O.E.M.
physical id: 1
version: To Be Filled By O.E.M.
serial: To Be Filled By O.E.M.
capacity: 32768mWh
*-network:0
description: Ethernet interface
physical id: 2
logical name: vetha11e727
serial: 7e:40:7f:0a:04:8c
size: 10Gbit/s
capabilities: ethernet physical
configuration: autonegotiation=off broadcast=yes driver=veth driverversion=1.0 duplex=full link=yes multicast=yes port=twisted pair speed=10Gbit/s
*-network:1
description: Ethernet interface
physical id: 3
logical name: docker0
serial: 02:42:69:a5:23:2a
capabilities: ethernet physical
configuration: broadcast=yes driver=bridge driverversion=2.3 firmware=N/A ip=<IP_ADDRESS> link=yes multicast=yes

here's the "lspci" command output:
lspci
00:00.0 Host bridge: Intel Corporation Xeon E3-1200 v5/E3-1500 v5/6th Gen Core Processor Host Bridge/DRAM Registers (rev 07)
00:01.0 PCI bridge: Intel Corporation Xeon E3-1200 v5/E3-1500 v5/6th Gen Core Processor PCIe Controller (x16) (rev 07)
00:08.0 System peripheral: Intel Corporation Xeon E3-1200 v5/v6 / E3-1500 v5 / 6th/7th/8th Gen Core Processor Gaussian Mixture Model
00:14.0 USB controller: Intel Corporation 200 Series/Z370 Chipset Family USB 3.0 xHCI Controller
00:14.2 Signal processing controller: Intel Corporation 200 Series PCH Thermal Subsystem
00:16.0 Communication controller: Intel Corporation 200 Series PCH CSME HECI #1
00:17.0 SATA controller: Intel Corporation 200 Series PCH SATA controller [AHCI mode]
00:1b.0 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #17 (rev f0)
00:1b.2 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #19 (rev f0)
00:1c.0 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #1 (rev f0)
00:1c.5 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #6 (rev f0)
00:1c.6 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #7 (rev f0)
00:1c.7 PCI bridge: Intel Corporation 200 Series PCH PCI Express Root Port #8 (rev f0)
00:1f.0 ISA bridge: Intel Corporation 200 Series PCH LPC Controller (Z270)
00:1f.2 Memory controller: Intel Corporation 200 Series/Z370 Chipset Family Power Management Controller
00:1f.3 Audio device: Intel Corporation 200 Series PCH HD Audio
00:1f.4 SMBus: Intel Corporation 200 Series/Z370 Chipset Family SMBus Controller
01:00.0 VGA compatible controller: NVIDIA Corporation GP104 [GeForce GTX 1070 Ti] (rev a1)
01:00.1 Audio device: NVIDIA Corporation GP104 High Definition Audio Controller (rev a1)
03:00.0 USB controller: ASMedia Technology Inc. ASM2142 USB 3.1 Host Controller
05:00.0 VGA compatible controller: NVIDIA Corporation GP104 [GeForce GTX 1070] (rev a1)
05:00.1 Audio device: NVIDIA Corporation GP104 High Definition Audio Controller (rev a1)
06:00.0 VGA compatible controller: NVIDIA Corporation GP104 [GeForce GTX 1070] (rev a1)
06:00.1 Audio device: NVIDIA Corporation GP104 High Definition Audio Controller (rev a1)
07:00.0 Ethernet controller: Qualcomm Atheros Killer E2500 Gigabit Ethernet Controller (rev 10)

If you need anything else let me know. I’m only passing one gpu into Tensorflow and thats the 1070Ti

The exact steps I took to generate the problem:
First I built from source for GPU following the instructions at the bottom of https://www.tensorflow.org/install/source
sudo nvidia-smi -pm 1
docker run --gpus 1 --ipc="host" -it -w /tensorflow -v $PWD:/mnt -p 8888:8888 -e HOST_PERMS="$(id -u):$(id -g)" tensorflow/tensorflow:from-src2 bash
export LD_LIBRARY_PATH=“/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/include/x64_64-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64”
pip install jupyter
pip install jupyter_http_over_ws
jupyter serverextension enable --py jupyter_http_over_ws
jupyter notebook --no-browser --notebook-dir=/mnt/notebooks --ip=<IP_ADDRESS> --MappingKernelManager.cull_interval=1200 --debug --NotebookApp.allow_origin='https://www.example.com' --NotebookApp.allow_remote_access=True --allow-root

@RayLucchesi TF 2.4 version is a nightly version which is unstable. Perhaps you may want to try with latest stable TF 2.3 version for building with source?

@ymodak I was just following instructions on the website I indicated above. I'd like to try to rebuild from source from TF2.2 as TF 2.3 seems to have a similar problem.
How would one build with a different level than what's current?   I guess use "git fetch" with either "git merge v2.2" or "git merge v2.3" instead of "git pull" as per the instructions in https://www.tensorflow.org/install/source?

maybe use "git fetch" with "git merge v2.2.0-rc4"?
or can I just do "git pull refs/tag-/v2.2.0-rc4"?

@RayLucchesi "git checkout v2.3.0", for example - see https://www.tensorflow.org/install/source#download_the_tensorflow_source_code.

Did the git checkout “git checkout v2.3.0” in the tensorflow_src directory and it came back with “ error: pathspec 'v2.3.0' did not match any file(s) known to git.”
It seems I had to do a git fetch first

Can you try building for 2.2?
$ git checkout v2.2.0

i tried to build from source using  v2.3.0 and the build failed but I think it ran out of space.
I cleaned up some files and tried to build from source using git checkout v2.2.0 and the ./configure command failed with
./configure
Traceback (most recent call last):
File "./configure.py", line 1551, in
main()
File "./configure.py", line 1368, in main
_TF_MAX_BAZEL_VERSION)
File "./configure.py", line 483, in check_bazel_version
['bazel', '--batch', '--bazelrc=/dev/null', 'version'])
File "./configure.py", line 159, in run_shell
output = subprocess.check_output(cmd, stderr=stderr)
File "/usr/lib/python3.6/subprocess.py", line 356, in check_output
**kwargs).stdout
File "/usr/lib/python3.6/subprocess.py", line 438, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['bazel', '--batch', '--bazelrc=/dev/null', 'version']' returned non-zero exit status 1.
So I'm going to retry build from source using v2.3.0 again...
Realize that every time I build from source it's a 11+ hour operation.
Also not sure what to make of "stu1130 added a commit to awslabs/djl that referenced this issue 5 hours ago" comment above is this a fix to the problem in v2.3?

So after another evening of building from source this time with V2.3.0. I get through that ok (after clearing out some used and unused container images) and then I do the build whl and that works and then I pip uninstall tensorflow and then pip install tensorflow-2.3.0-cp36-cp36m-linux_x86_64.whl and that seems to work.
Following the instructions in the build from source website I try a simple python program to print out the #GPUs.
python -c "import tensorflow as tf; print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))"
which fails as follows:
python -c "import tensorflow as tf; print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))"
Traceback (most recent call last):
File "", line 1, in
File "/tensorflow_src/tensorflow/init.py", line 24, in
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
File "/tensorflow_src/tensorflow/python/init.py", line 40, in
from tensorflow.python.eager import context
File "/tensorflow_src/tensorflow/python/eager/context.py", line 32, in
from tensorflow.core.framework import function_pb2
ImportError: cannot import name 'function_pb2'
I have copies of the terminal output from the bazel build, the build wheel, the pip uninstall and pip install if you want them.

when I cd $HOME and try the same program
cd $HOME
root@17638e5f9f58:~# python -c "import tensorflow as tf; print(' Num GPUs Available: ', len(tf.config.experimental.list_physical_devices('GPU')))"
2020-08-08 20:19:24.128138: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2020-08-08 20:19:25.347871: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1
2020-08-08 20:19:25.347901: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: UNKNOWN ERROR (-1)
2020-08-08 20:19:25.347918: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: 17638e5f9f58
2020-08-08 20:19:25.348048: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: 17638e5f9f58
2020-08-08 20:19:25.348182: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: Not found: was unable to find libcuda.so DSO loaded into this program
2020-08-08 20:19:25.348559: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 450.57.0
Num GPUs Available:  0
I get my favorite CUINIT unknown error (-1)

Of course that’s because the stubs folder is in $LD_LIBRARY_PATH. When I delete that with
export LD_LIBRARY_PATH=“/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/include/x64_64-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64”
It now comes up ok
But now after i commit the container and startup a jupyter notebook server in the container it seems to work. thanks for your help.
Mind if I ask what the revert update to tf2_3 did?

It’s taken me a bit but it appears as if tf is built for GPUs, the docker container has GPUS ALL and I can see the GPUS in the container using NVIDIA-SMI but for some reason TF is not using any gpus.
print(device_lib.list_local_devices())
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation:<PHONE_NUMBER>536459057
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit:<PHONE_NUMBER>4
locality {
}
tf.test.is_built_with_gpu_support()

Out[5]:
True
tf.test.is_gpu_available(
cuda_only=False, min_cuda_compute_capability=None
)
WARNING:tensorflow:From :2: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.config.list_physical_devices('GPU') instead.
Out[3]:
False
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

Num GPUs Available:  0
docker container exec b48df43026b0 nvidia-smi
Mon Aug 24 06:08:41 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.57       Driver Version: 450.57       CUDA Version: ERR!     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  On   | 00000000:01:00.0 Off |                  N/A |
|  0%   32C    P8     6W / 180W |     54MiB /  8116MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 1070    On   | 00000000:05:00.0 Off |                  N/A |
|  0%   28C    P8     4W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  GeForce GTX 1070    On   | 00000000:06:00.0 Off |                  N/A |
|  0%   27C    P8     4W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
So the docker container has GPUs (3 of them). TF was built with GPU support but for some reason TF is not discovering the GPUs nor using them.
I’ve tried this by just using one GPU “GPUS 1” on docker command and it doesn’t seem to make a difference except in the Nvidia-SMi command.
I used to have debug on for the jupyter notebook server and I saw that it accessed CUDA libraries...

Oh and I tried this:
tf.config.list_physical_devices('GPU')

Out[4]:
[]
Which also shows no GPUs...

Sorry my mistake forgot to extract "/usr/local/cuda/lib64/stubs" from $LD_LIBRARY_PATH. When I did that GPUs were available again.

After all that I'm back to my favorite CUDA intialization failed error:
CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid.
After the failure here is what NVIDIA-SMI command shows in the container:
Mon Aug 24 22:41:54 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.57       Driver Version: 450.57       CUDA Version: ERR!     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  On   | 00000000:01:00.0 Off |                  N/A |
|  0%   40C    P8     7W / 180W |    165MiB /  8116MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+
and this is what the NVIDIA-SMI command shows at the ubuntu system (outside the container)
nvidia-smi
Mon Aug 24 16:42:45 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.57       Driver Version: 450.57       CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  On   | 00000000:01:00.0 Off |                  N/A |
|  0%   39C    P8     7W / 180W |    165MiB /  8116MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 1070    On   | 00000000:05:00.0 Off |                  N/A |
|  0%   30C    P8     5W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  GeForce GTX 1070    On   | 00000000:06:00.0 Off |                  N/A |
|  0%   28C    P8     4W / 166W |      7MiB /  8119MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1010      G   /usr/lib/xorg/Xorg                 36MiB |
|    0   N/A  N/A      1684      G   /usr/bin/gnome-shell               15MiB |
|    0   N/A  N/A      5623      C   /usr/bin/python3                  109MiB |
|    1   N/A  N/A      1010      G   /usr/lib/xorg/Xorg                  4MiB |
|    2   N/A  N/A      1010      G   /usr/lib/xorg/Xorg                  4MiB |
+-----------------------------------------------------------------------------+
It seems I can use TF services to see the GPU but I can't seem to get tf.keras to build a model that uses them. Here's the model I was attempting to define at the time of the error:
model = tf.keras.Sequential()
model.add(layers.Conv2D(32,(3,3), activation='relu', input_shape=(150,150,3)))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(64,(3,3), activation='relu'))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(128,(3,3), activation='relu'))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(128,(3,3), activation='relu'))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Flatten())
model.add(layers.Dense(512, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))
model.summary()
The error seems to have been generated on the 1st statement above.  I uploaded the traceback for the error.
cuda_init_error_traceback.log
anything else you need please let me know. At this point we are back to ground 0, getting the cuda initialization error.
It seems every time I thought it was working we were not working with GPUs.

Turns out I need to rebuild from source with compute capability 6.1 to support the GeForce 1070/1070 Titan GPUs... doing that now. I'll let you know tomorrow after the build finishes whether it works or not.

After rebuild from source  (TF 2.4) and using the correct CUDA GPU compute capability, 6.1, it now seems to work once I delete stubs from LD_LIBRARY_PATH. So as far as I’m concerned you can close this issue.
However, the CUINIT error message is somewhat cryptic, I would suggest rewording it to say something about TF build doesn’t support the GPU that’s available and that it needs to be rebuilt from source with the correct CUDA GPU compute capability.
Thanks for all your help in this.


Integrated some of AS5047P as a new encoder mode and got it to compile.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.dgonz seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.

Please let us know on discord if you need any assistance or feedback. We'd love to have support for the AS5047P.


stattically linked binaries build error fix

[!] The 'Pods-App' target has transitive dependencies that include statically linked binaries:

Hi @bdhwanm,
Thank you for opening the PR. We are already aware of this issue and will add this fix to the upcoming release.


Add tests and API for getListOfGCS

A new function (getListOfGCS) was created in imodel-native.
This PR contains tests for this function, and an API to make it available publicly in itwinjs-core.
imodel-native: https://github.com/iTwin/imodel-native/pull/756

This integration test has failed twice. Seems unrelated to your changes at a glance.
1) RealityDataAccess (#integration)
     should get RealityDataSource for reality data attachment in iModel:
   AssertionError: expected undefined not to be undefined
    at Context.<anonymous> (home/vsts/work/1/s/full-stack-tests/core/src/frontend/standalone/RealityDataAccess.test.ts:252:27)


fix the build rocksdb problem

rocksdb upgrade to 6.3.6
optimize the build scripts
fix build errors
fixes https://github.com/cubefs/cubefs/issues/1925
Release note:
need to upgrade to go1.17

Codecov Report

Merging #1999 (a301775) into master (434fb5b) will increase coverage by 0.00%.
The diff coverage is n/a.

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
@@           Coverage Diff           @@
##           master    #1999   +/-   ##
=======================================
  Coverage   44.96%   44.97%
=======================================
  Files         446      446
  Lines       71793    71793
=======================================
+ Hits        32283    32288    +5
+ Misses      37272    37264    -8
- Partials     2238     2241    +3

see 98 files with indirect coverage changes
:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more

NB

Good

#2016


ModuleNotFoundError while include-module is used

C:\WINDOWS\system32>nuitka --onefile --windows-onefile-tempdir --enable-plugin=multiprocessing --follow-imports --include-module=gevent._gevent_c_hub_local --enable-plugin=gevent C:\Users\K\Downloads\dddd\BottyThotty.py
Output
...
...
Nuitka-Plugins:INFO: gevent: Greenlet tree tracking switched off
Nuitka:INFO: Completed Python level compilation and optimization.
Nuitka:INFO: Generating source code for C backend compiler.
Nuitka:WARNING: Did not follow import to unused 'gevent._gevent_c_hub_local', consider include options.
Nuitka:INFO: Running data composer tool for optimal constant value handling.
Nuitka:INFO: Running C level backend compilation via Scons.
Nuitka-Scons:INFO: Backend C compiler: cl (cl).
Nuitka-Scons:INFO: Compiled 145 C files using clcache with 0 cache hits and 145 cache misses.
Nuitka-Postprocessing:INFO: Creating single file from dist folder, this may take a while.
Nuitka:INFO: Running bootstrap binary compilation via Scons.
Nuitka-Scons:INFO: Backend C compiler: cl (cl).
Nuitka-Scons:INFO: Compiled 1 C files using clcache with 0 cache hits and 1 cache misses.
Nuitka:INFO: Keeping onefile build directory 'BottyThotty.onefile-build'.
Nuitka:INFO: Keeping dist folder 'BottyThotty.dist' for inspection, no need to use it.
Nuitka:INFO: Keeping build directory 'BottyThotty.build'.
Nuitka:INFO: Successfully created 'BottyThotty.exe'.
When running:
File "C:\Users\K\BOTTYT~1.DIS\BottyThotty.py", line 9, in
File "C:\Users\K\BOTTYT~1.DIS\gevent_init_.py", line 86, in
File "C:\Users\K\BOTTYT~1.DIS\gevent_hub_local.py", line 101, in
File "C:\Users\K\BOTTYT~1.DIS\gevent_util.py", line 148, in import_c_accel
File "importlib.py", line 127, in import_module
ModuleNotFoundError: No module named 'gevent._gevent_c_hub_local'
Include-module=gevent does not solve it either
Any and all ideas on how this might be resolved are appreciated!
Thanks in advance.

You didn't fill out the issue template at all, and your outputs seem to not match the input, or rather strange bugs exist. I don't really appreciate guessing information.


Add react three fiber

The experimental beginnings of using react three fiber as an alternative way to express webgl scene graphs in a react-style declarative syntax.
Likely better in every way to our current framework, except perhaps performance (TBD). More exploration needed.
Next step is to try porting vision and then revaluate.

Replaced by #1115


Remove extra actionlint

Description of proposed changes
Noticed the extra actionlint when I was catching up on the addition of pre-commit to this repo.
Remove extra actionlint and sort pre-commit config by repo name to avoid duplicates in the future.
Checklist

[ ] Checks pass

Changes order in which the hooks are run in pre-commit CI, but order shouldn't really matter here. All hooks are run with the default False value for the fail_fast option, so all hooks are run regardless of failure status of other hooks.


Fixed neon task issue

Use neon binary from node_modules directory instead of the system one.

this causes weird build problems on windows.


Also apply version update into url

Apply update from https://github.com/starkandwayne/cf-deployment/commit/5b420c274916a5fceb004fed7678dcef57bd7ffe

cc @bodymindarts

If we drop the url + sha1 files, the latest genesis version will detect if the release is on the director already, and if not, grab details from the genesis index. Then we won't have to worry about updating the url/sha every time we get a new version.

I agree would be good to drop the url + sha1 genesis fills them in dynamically at deploy time anyway.


build tdlib problem

hi sir
I encountered a problem while building tdlib
LINK : fatal error LNK1181: 无法打开输入文件“ZLIB_LIBRARY-NOTFOUND.lib” [F:\td\build\td\generate\generate_json.vcxproj]
无法打开输入文件=Unable to open input file

Did you follow https://tdlib.github.io/td/build.html?

yes  im follow https://tdlib.github.io/td/build.html  other->windows->PowerShell ->32

Then, zlib should have been installed by the command /vcpkg.exe install gperf:x86-windows openssl:x86-windows zlib:x86-windows. You need to check output of the command and whether it succeeded. You can rerun the command if appropriate.


[DS-2670] Restrospectively create DOIs for all items in archive

This curation task will create any identifiers which are configured on but not present in a given Item.
Briefly tested a version for DSpace 5.6.  Please inspect, test, critique.
Fixes #6030

Just did a rough code inspection. I love it.
We need to test it with:

HandleIdentifierProvider
VersionedHandleIdentifierProvider
VersionedHandleIdentifierProviderWithCannonicalHandles
DOIIdentifierProvider and
VersionedDOIIdentifierProvider

Close/open to get Travis to run.

Close/reopen to kick stuck tests.

@kshepherd Can you please give this a test run and merge it then?

This is a great simple script. I've tested it with handles and DOIs in different conditions to understand the results, and the code being 'tested' is really the identifier service / provider register() behaviour, but it's good to know before running it over a large set of items in prod. As noted below, I did find some issues with the versioned handle provider with canonical handles (where the handle is rewritten to point to the newest version, and the old ones get the x.1 and x.2 handles etc) that means things get a bit messed up when the task is run over old versions of items that have handles.
Handle testing
Worked well for HandleIdentifierProvider and VersionedHandleIdentifierProvider - if already present, metadata deleted and re-added which is nice for prefix updates too?
Deleted handle from metadata but not DB, and was added again.
Using the standard VersionedHandleIdentifierProvider, the versioned handle for the newest item was correctly recreated after deletion, but not for older item versions...
Running the script over these items in typical circumstances where they already had handles / versioned handles didn't result in any problems or duplicate identifiers.
VersionedHandleIdentifierProviderWithCanonicalHandles did show some problems. I made a new version of an item and ran the script without any other changes. When it hit the 23.1 handle (the oldest version, since canonical for new version was updated 23 at the time of versioning), it acted almost as though I'd made a new version, assigning a new 23.2 handle to the newest item and updating 23 to the oldest, which now has 23.1 and 23 pointing to it:
28 | 123456789/23.2 | 2 | | 942c31dd-6b6d-4b86-a987-1ef98d12397a
29 | 123456789/23.1 | 2 | | c16970f3-d28a-40d6-bacd-f23f3eb884a2
27 | 123456789/23   | 2 | | c16970f3-d28a-40d6-bacd-f23f3eb884a2

I don't know if this needs to be a blocker for this script, or just a note not to run it on items with versions under the VersionedHandleIdentifierProviderWithCanonicalHandles provider. Perhaps in the task itself, the handle identifier provider service could be looked up, and if the class matches the Canonical provider, exit the curation task with a failure message?
It seems to me that the VersionedHandleIdentifierProviderWithCanonicalHandles provider needs to change some assumptions about what to do when register() is called, because it won't always be in the context of a new version. But that's probably out of scope for this PR.
DOI testing
Worked for DOIs and versioned DOIs and also respected item filter. If DOI already present, metadata deleted and re-added (again, nice if eg dx.doi.org -> doi.org)
If metadata deleted but in DB, the correct DOI URI is added back to metadata.
If DOI is missing from the DB but a DOI URI kept in metadata, a new DOI was queued for registration.
This is to be expected, and isn't really a problem, but I'm just noting it here.
(perhaps in the future the DOI providers could look in metadata and if it finds a valid DOI URI of the prefix managed by DSpace, put it in the DB with "already reg'd" status?)
In the particular case I tested, it was a versioned DOI and the newly minted DOI was ../10 rather than ending in a .2 or .3 as with other versioned identifiers, but that's not a big deal either as far as i can tell, just aesthetic.

So, is this ready to go?

So, is this ready to go?

I'm +1 as long as we really clearly explain that this will be destructive if run over repositories using VersionedHandleIdentifierProviderWithCanonicalHandles - it will reassign versioned handles incorrectly and cause some items to have multiple handles. I think ideally we'd check for that particular provider somehow and exit the script, but perhaps it can be handled in documentation? I'm not trying to be a blocker, just a bit worried about that scenario.


FYP: show placeholder tiles when fetching membership or fyp itself.

This prevents the "no membership" and "no recommendations" message from flashing during load.

Should we do the same for upcoming live streams? Raphael recent noticed it made his homepage jumpy too.


.exclude(pk__in=qs) and .difference() error

opportunities = Opportunity.objects.filter(amount__gt=0, is_won=True)

P_opportunities = opportunities.filter(opportunitylineitem__product2__pk="myid123123")
noP_opportunities = opportunities.exclude(opportunitylineitem__product2__pk="myid123123")

noP_opportunities will always raise error. For example: noP_opportunities.count() gives:
File "C:\Users\XXX\PycharmProjects\SalesForceConsole\venv\lib\site-packages\salesforce\dbapi\driver.py", line 325, in raise_errors
    raise SalesforceError([err_msg], response)
salesforce.dbapi.exceptions.SalesforceError: INVALID_FIELD

    FROM OpportunityLineItem WHERE U1.Product2Id = 'myid123123'))))
                                   ^
    ERROR at Row:1:Column:220
    Didn't understand relationship 'U1' in field path. If you are attempting to use a custom relationship, be sure to append the '__r' after the custom relationship name. Please reference your WSDL or the describe call for the appropriate names.

So I've tried this:
opportunities = Opportunity.objects.filter(amount__gt=0, is_won=True)

P_opportunities = opportunities.filter(opportunitylineitem__product2__pk="myid123123")
noP_opportunities = opportunities.exclude(pk__in=P_opportunities.values("pk"))

But it doesn't make any sense.
opportunities.count() is 3895. P_opportunities.count() is 512. So, noP_opportunities should be 3383 but it gives 0.
Clearly, something isn't working with .exclude()
Similar problem with .difference()
opportunities = Opportunity.objects.filter(amount__gt=0, is_won=True)

P_opportunities = opportunities.filter(opportunitylineitem__product2__pk="myid123123")
noP_opportunities = opportunities.difference(P_opportunities ).count()

  File "C:\Users\XXX\PycharmProjects\SalesForceConsole\venv\lib\site-packages\salesforce\backend\utils.py", line 249, in execute_select
    is_query_all = self.query and self.query.is_query_all
AttributeError: 'AggregateQuery' object has no attribute 'is_query_all'

Short answer:
noP_opportunities = opportunities.filter(
    pk__not_in=OpportunityLineItem.objects.filter(product2_id='any_id').values("opportunity_id")
)

Salesforce really doesn't support SOQL like
... WHERE NOT (Id IN (SELECT ...))
and the query must be
... WHERE Id NOT IN (SELECT ...))
If the expression NOT (Id IN (SELECT is exacttly after WHERE then it raises exception
MALFORMED_QUERY
    ... FROM Opportunity WHERE (NOT (Opportunity.Id IN (SELECT OpportunityLineItem.OpportunityId
                                     ^
    ERROR at Row:1:Column:887
    'NOT' operator cannot be combined with semi/anti join subqueries

Docs Salesforce SOQL chapter Semi-Joins with IN and Anti-Joins with NOT IN:

You cannot use the NOT operator as a conjunction with semi-joins and anti-joins. Using it converts a semi-join to an anti-join, and the reverse. Instead of using the NOT operator, write the query in the appropriate semi-join or anti-join form.

Therefore the expression .exclude(pk__in=queryset) is not supported and the operator not_in exists in django-salesforce to fix it: .filter(pk__not_in=queryset)
Another restriction:

The selected column in a subquery must be a foreign key field, and cannot traverse relationships. This limit means that you cannot use dot notation in a selected field of a subquery.

Example
MALFORMED_QUERY
    Opportunity.Id NOT IN (SELECT OpportunityLineItem.Opportunity.Id
                                  ^
    ERROR at Row:1:Column:970

Therefore I can not use
pk__not_in=Opportunity....values('id')
and must use
pk__not_in=OpportunityLineItem....values('opportunity_id')
Finally you are also restricted by this rule:

You cannot query on the same object in a subquery as in the main query. You can write such self semi-join queries without using semi-joins or anti-joins.

.difference()
I'm adding this paragraph to README

Unsupported methods: Queryset methods .union(), .difference(), .intersection() and .distinct() are not supported because SOQL doesn't support corresponding operators: UNION, EXCEPT, INTERSECT and DISTINCT.

Thanks a lot both for your work and your support!

I will also raise an error preventive where SF returns invalid results, because an invalid result is worse than an exception.
@Saturnix The heart emoticon is very similar to "Sponsor" icon above in the repository.
A non frequent support for issues is useful also for development, but it is finally time consuming and most of work on the project is not related to any my employment.
Thing about becoming a sponsor you or your employer.


Readme  Improvement in virtual makeover

https://github.com/akshitagupta15june/Face-X/tree/master/Virtual_makeover/Virtual-Makeup

I want to work on this. I request you to assign me this. I am a GSSoC'21 PARTICIPANT

assigning


[Timestamp FIle Names] Capture all non-extension text

This alters the regex used for the capture to one with a dynamic quantifier.
If there is no dot in the filename, the curly bracket quantifier's value is equal to the filename's length.
If there is a dot in the filename, the curly bracket quantifier's value is equal to its last index. This will not include the dot in the capture (because the index starts at 0).

Hi there,
I'm happy to see that you're using my plugin :D
When writing it I wasn't aware that user's might use dot separators in their filenames.
The reason I decided against matching until lastIndexOf(".") was that some files might have multiple extensions like myfile.tar.gz.
I just pushed a commit (https://github.com/ioj4/shelter-plugins/commit/f290f7c8e19bdc50aef976be22824ee954c99943) that adds an option in the settings to also match dot seperators. I hope that helps :)


Heroes of the Storm (HotS) graphics corruption after update to Mesa 19.3

This might be a Mesa issue since it's manifested itself after updating to 19.3 and when downgrading to 19.2 I don't have any issue but I figured I should check here first if there's an obvious reason this is happening + not sure how much support on gets for bugreports on Mesa when using applications through Wine/DXVK.
I'm seeing some sort of corruption, it looks a bit like it's at the edges of the tiles.
Screenshot below

GPU: RX480
Driver: RADV, Mesa 19.3.3 ACO not enabled, although I get the same corruption with ACO enabled.
Wine: Staging 5.0
DXVK: 1.5.3
dxgi and d3d11 logs below
HeroesOfTheStorm_x64_dxgi.log
HeroesOfTheStorm_x64_d3d11.log
If this is something that is caused by/should be fixed by DXVK I can add an Apitrace of course.

If this is a Mesa regression, why not report this to Mesa instead?

If this is a Mesa regression, why not report this to Mesa instead?

Well, I listed those reasons in the first paragraph of the description. They might not be valid, I don't know.
Anyway, from your response I'm assuming this doesn't ring any bells and that you think it's a Mesa issue?
I've created a bug for Mesa https://gitlab.freedesktop.org/mesa/mesa/issues/2458 so feel free to close if this is not a DXVK bug.

Well the problem is that with a screenshot alone I can't do much. In general, if an update to software B breaks software A then software B is most likely what broke it.


Unable to use django-debug-toolbar together with django-cms

Summary
When opening a cms page to edit the page fails
Expected behaviour
You should be able to open a page and be able to see a working django-debug-toolbar.
Actual behaviour
It fails with the following traceback.
web_1  | Traceback (most recent call last):
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/core/handlers/exception.py", line 41, in inner
web_1  |     response = get_response(request)
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/core/handlers/base.py", line 187, in _get_response
web_1  |     response = self.process_exception_by_middleware(e, request)
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/core/handlers/base.py", line 185, in _get_response
web_1  |     response = wrapped_callback(request, *callback_args, **callback_kwargs)
web_1  |   File "/usr/local/lib/python3.6/site-packages/newrelic/hooks/framework_django.py", line 544, in wrapper
web_1  |     return wrapped(*args, **kwargs)
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/utils/decorators.py", line 149, in _wrapped_view
web_1  |     response = view_func(request, *args, **kwargs)
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/views/decorators/cache.py", line 57, in _wrapped_view_func
web_1  |     response = view_func(request, *args, **kwargs)
web_1  |   File "/usr/local/lib/python3.6/site-packages/django/contrib/admin/sites.py", line 224, in inner
web_1  |     return view(request, *args, **kwargs)
web_1  |   File "/usr/local/lib/python3.6/site-packages/cms/views.py", line 237, in render_object_edit
web_1  |     toolbar.set_object(content_type_obj)
web_1  | AttributeError: 'EmptyToolbar' object has no attribute 'set_object'

Environment

Python version: 3.6
Django version: 1.11
django CMS version: 4.0

@jonathan-s I have a document that I can share with you regarding django-debug-toolbar setup both standalone and in the Divio cloud setup. Please reach out if that is ever required again.

Since there is such a document perhaps that should be a part of the
documentation?
Sent from my mobile
On Fri, 23 Oct 2020, 20:04 Aiky30<EMAIL_ADDRESS>wrote:

@jonathan-s https://github.com/jonathan-s I have a document that I can
share with you regarding django-debug-toolbar setup both standalone and in
the Divio cloud setup. Please reach out if that is ever required again.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/django-cms/django-cms/issues/6731#issuecomment-715493523,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AAQGYEWYVKG472U4VYOVPV3SMHASHANCNFSM4IW7ZPHA
.

@jonathan-s the information is already part of the debug toolbars docs, it needs additional settings for the cloud, it doesn't belong in the CMS as it is a third party.

@magicproductions, to rephrase your request: @Aiky30 Can you please provide that information here?
@Aiky30: Sure.
Note: This is for a Divio Cloud project with django-cms.
Django 2.2+
Modify urls.py of the project by adding:
import settings

if settings.DEBUG:
    from django.urls import path
    import debug_toolbar

    urlpatterns = [
        path('__debug__/', include(debug_toolbar.urls)),
    ] + urlpatterns

At the bottom of requirements.in
django-debug-toolbar

At the bottom of the settings.py file
########################
# Django Debug Toolbar
########################
INSTALLED_APPS.extend([
    # add your project specific apps here
    'debug_toolbar',
])
MIDDLEWARE.insert(
    MIDDLEWARE.index('django.middleware.gzip.GZipMiddleware') + 1,
    'debug_toolbar.middleware.DebugToolbarMiddleware'
)
INTERNAL_IPS = ('<IP_ADDRESS>', 'localhost', '<IP_ADDRESS>',)
def show_toolbar(request):
    return True
DEBUG_TOOLBAR_CONFIG = {
    'SHOW_TOOLBAR_CALLBACK': show_toolbar,
    'RESULTS_CACHE_SIZE': 500
}

Django 1.11
Modify urls.py of the project by adding:
import settings
if settings.DEBUG:
    from django.conf.urls import url
    import debug_toolbar
    urlpatterns = [
        url(r'^__debug__/', include(debug_toolbar.urls)),
    ] + urlpatterns

At the bottom of requirements.in
django-debug-toolbar

At the bottom of the settings.py file
########################
# Django Debug Toolbar
########################
INSTALLED_APPS.extend([
    # add your project specific apps here
    'debug_toolbar',
])
MIDDLEWARE_CLASSES.insert(
    MIDDLEWARE_CLASSES.index('django.middleware.gzip.GZipMiddleware') + 1,
    'debug_toolbar.middleware.DebugToolbarMiddleware'
)
INTERNAL_IPS = ('<IP_ADDRESS>', 'localhost', '<IP_ADDRESS>',)
def show_toolbar(request):
    return True
DEBUG_TOOLBAR_CONFIG = {
    'SHOW_TOOLBAR_CALLBACK': show_toolbar,
    'RESULTS_CACHE_SIZE': 500
}


OCM-9191 | fix: typo in logger info message for output of command

Fix typo in info logger message in runner

/ok-to-test

/retest

/lgtm


update README

Pointer to a gist with an approach for publishing to Redis from Elixir for MessageBus to pick up the message.

awesome thanks !


Could not find or load main class com.wgzhao.datax.core.Engine

C:\ETL\DataX_ETL\target\datax\datax-3.2.3>python bin/datax.py job/job.json
Error: Could not find or load main class com.wgzhao.datax.core.Engine

@mosynaq thanks for your feedback. Currently, datax is not good enough for windows compatibility, I am improving this, hopefully in the next version can be better compatible with windows system

you can download the datax.py.zip  and uncompress your DATAX_HOME\bin folder, replace the current datax.py, It should work.


Update to new event system for PermissionSystemEvent

Code updated to new bukkit event system for PermissionSystemEvent

Already done. Thank you! :)


OptionOutputAsXml adds spaces to comments when using InnerHtml

Description
I have some cases with HTML comments which I need to preserve their syntax. Some HTML examples can be modified (by changing the Comment property on a HtmlCommentNode). When I set OptionOutputAsXml to true, spaces are always added on different places.
In the fiddle I provide below I have a working example of the issue. This are my basic cases:

Original HTML
HtmlDocument.DocumentNode.InnerHtml

text

text

text <[endif]-->

text <[endif]-->

For the first row case:  A space has been added after "comment", now having two spaces.
For the second row case: Two spaces have been added on the second "


Game crashes on launch 1.20.6

With the latest version of the mod installed and enabled, the game reports a crash and generates the log attached
crash-2024-06-03_16.24.30-client.txt

Hey there, Curseforge is pending with the update/fix for 1.20.5 and 1.20.6. It should fix this issue.
Sorry about the inconvenience.

This looks to have been fixed, along with the issue about the smoker no longer accepting the recipe in 1.20.5 and 1.20.6. Sorry for the issues.


[nginx-ingress-controller] cleanup before update updating nginx controller to 0.7

fixes #930
fixes #884

LGTM, guess we'll need followups for examples and readme anyway so you can fix the nits in that


Add iterm2 support

Let me know if you want me to squash the two commits into one.

Thanks @jasonm23, but I'm curious about your use-case. iTerm2 is already supported via bin/os_x_iterm script.

It's not.  ITerm suffers from a bit of naming issues.
The ITerm app is the general release and is in V.2x
ITerm2 is the bundle name on the nightlies ...
Confused?  I am.
If you grab a nightly zip the app bundle is still called ITerm.app but it will run as Iterm2 (the bundle id)
They should really sort it out!  Anyway suffice to say the two versions are NOT AppleScript compatible.  The old terminal and terminals objects are no longer there.
If you add iterm2.app (renamed nightly) to the AppleScript Editor Library, you will get the docs for the currevt API.
I'll be happy to assist while this is all fresh in my mind.

Will the official name become iTerm2 going forward? If only the nightly build is named that, and it will be renamed before they cut a stable release (maybe it's a bug), then I don't think it should be a concern of vim-rspec to support that nightly build situation.

It is to become Iterm2

Makes sense to merge it the. Do you mind squashing into 1 commit?

Sure thing.

I'll add a note and links re:iterm2 in the commit and comments on the script itself.  To clear up any FAQ / ambiguities.

Squashed and updated, in the pipe 5 by 5

https://www.youtube.com/watch?v=8dXc2W1uWck

https://www.youtube.com/watch?v=8dXc2W1uWck

Ah, that's where Starcraft got it from!
Do you mind adding the new runner to the README (under "Custom runners")?

README update :)

Excellent work, @jasonm23! Merged as f733ab32702577ad799e3cd4095aa0bd5bcaf582.

Thank you, hth


Add github actions for PR

Create github actions corresponding to setup-cache, linting and unit-tests on gitlab-ci.

Overall seems good to me, thanks for the work! I have a few questions:

what is the extra dot at the begining of some commands ? such as in . .venv/bin/activate
we are not building the doc so maybe we don't need to install graphiz and the other doc dependencies
similar remark about coverage, maybe we could just run pytest since we don't do anything with the generated files

Or maybe you want to keep theses in case we fully switch to github in the future

Thanks @olvb for the review !

* what is the extra dot at the begining of some commands ? such as in `. .venv/bin/activate`

The dot is a POSIX command that is more portable than source but it makes the same thing. In this case, it activates the virtual environment.

* we are not building the doc so maybe we don't need to install graphiz and the other doc dependencies

Agreed. It is not relevant for the time being. However, I wanted to have as much as possible the same behavior between gitlab-ci and github-actions.
Also, I think that doc build should also be tested for contributions on documentation. It will be added later.

* similar remark about coverage, maybe we could just run pytest since we don't do anything with the generated files

Same remark = same answer ;) I will see later how to upload/display coverage report in PR.


ci: add a publish step to upload dockerhub readme

In the publish workflow, add an job to publish a readme file on docker hub. This file will be introduced in an other PR : https://github.com/okp4/okp4d/pull/130/commits/137e3c5f39e693bd000a1c49ce9f05ebb0508ad1
Maybe let's wait for https://github.com/okp4/docker-images/pull/72 to be sure the action works.

This changes will be done in this PR : https://github.com/okp4/okp4d/pull/130


InterSystems Testing Manager use a bad ^UnitTestRoot path

Hello,
I use the  "InterSystems Testing Manager" extension on a local iris instance in my vscode editor.
I have a problem when i run unit test with vscode extension : the used path is bad.
In my namespace : ^UnitTestRoot="C:\git-data\care_backend\care_core\src\cls\core\test\services"
VS code run test into : C:\git-data\care_backend\care_core\src\cls\core\test\services\daporrov
daporrov is the username the instance.
So, tests are running into a bad directory and i have one error "bad directory"
I don't know why the username is added at the end of the path.
How to fix that ?
Thank you

Based on the instructions in the extension's README your ^UnitTestRoot node in namespace XXX should end with \XXX\UnitTestRoot (see step 2) and the prefix to this should match the Application Path you chose for the /_vscode web app you were told to create (see step 1).
When you are using the client-side paradigm to create and manage your unit test class sources, the extension doesn't load and run them directly from their source folder but first copies them to the {webAppPath}\XXX\UnitTestRoot\{username} folder. It does this in order to support remote IRIS servers as well as local ones.

Thank you for these informations.
It is work well.

Thank you for these informations.
It is work well.


Visually differentiate roads speed limits

Need: Be able to see on map each segment speed to know where is missing or incorrect.
Proposal: Add a new map data layer that would render a color line or halo next to each roads segment that have the maxspeed tag, using different colors to visualize each speed range.
For example:
kmh:
10: dark red (10-19 kmh)
20:
30:
40:
45:
50:
60:
70:
80:
90:
100:
110:
130+: dark green
mph:
5: dark red
10:
15:
20:
25:
30:
35:
40:
45:
50:
55:
60:
65:
70:
75:
80:
85+: dark green

Maybe this is a job better suited for an OSM-Validator, showing segments which have big differences in speed Limit with adjacent segments.

ITO World has a map showing missing speed limits from major/minor roads: http://product.itoworld.com/map/125
They also have maps showing the speed limits in km/h, mph and both: http://product.itoworld.com/map/group/19

The just-merged KeepRight integration #5201 includes a check for missing maxspeed tag.  That's a good start for now, but I agree it would be nice to give users more of an ability to add custom styling to highlight issues with the map that they are interested in.


turn on "copy" and "paste" by right clicking in tiny mce fields

closes #633

E2E errors might be real this time?
The following error originated from your application code, not from Cypress.

  > Unexpected token '<'

When Cypress detects uncaught errors originating from your application it will automatically fail the current test.

This behavior is configurable, and you can choose to turn this off by listening to the uncaught:exception event.

https://on.cypress.io/uncaught-exception-from-application


Fast-Render re-write feature tries to re-write added messages of non existing document

Issue:
There is still a case when fast-render re-writes added messages of previously removed documents. As result meteor throws the following error:

Here is an example app where you could try this out: https://github.com/varenytskyi/fast-render-example/tree/master
or see this video
Mostly it happens when document is re-added with another cursor in complex publications

Fix:
The fix is pretty simple. Since meteor buffers ddp messages we have to be sure that there is no removed message in internal meteor queue before re-writing added message of the same document.
There is a branch with patched fast-render in the app I've mentioned above: https://github.com/varenytskyi/fast-render-example/tree/with-patched-fast-render
Here is also a video how patched version works.

Hi @arunoda,
This is a critical issue which appears even when initial loading is completed.
It would be great to see this issue patched. Thanks!

@theosp No, I didn't.
I clearly explain above what kind of issue this changes fix.
Nice to see your new PR as far as the issue you've mentioned appears as well sometimes :thumbsup:


Added the LCM calculator

Pull Request
Closes #92
Description (required)
It takes 2 numbers as input and then calculates the LCM of the 2 numbers and prints it.
Checklist (required)

[x] I have read and understand the contribution guidelines.
[x] I have tested this code.
[x] I have updated the documentation.
[x] I followed the standards described in the README.
[x] I have reviewed and addressed any comments and feedback.

Screenshots (optional)
If applicable, add screenshots that help visualize the changes you made.

Issue: #92

@RuanAragao, is this PR merged?


fix problem of setting the default file format

According to an earlier C user guide, the default format is used when no format specific flag is used when creating a new file. This PR fixes to respect the rule. A test program nc_test/tst_default_format.c added in this PR can be used to detect the error.
See commit message for detailed changes.
I also notice that API nc_set_default_format is missing from to C user guide.

Pulling into a combined PR request to set the stage for larger merges early next week.

Exploring an issue observed on 32-bit mpich systems, will post more details when I get it nailed down.

This PR is on hold due to failures observed in an mpich32 system.  Details here:

http://cdash.unidata.ucar.edu/testDetails.php?test=206110&build=5378

I'll look into this further after I get some of the PR's merged.

The test error is due to netCDF library does not support CDF-5 on 32-bit machines.
I added some preprocessor conditions to skip CDF-5 tests to the program that failed.
It should work now.

Excellent, thank you very much @wkliao!


panic: runtime error: invalid memory address or nil pointer dereference

Version Reports:
Distro  version of host:
[root@laptop k801]# cat /etc/redhat-release
Fedora release 27 (Twenty Seven)
[root@laptop k801]#
Terraform Version Report
[root@laptop k801]# terraform -v
Terraform v0.11.4-dev (4f38f4f9eb7e892aecb546e52851a85cfad5af6c)

provider.libvirt (unversioned)

[root@laptop k801]#
Libvirt version
[root@laptop k801]# virsh --version
3.7.0
[root@laptop k801]#
terraform-provider-libvirt plugin version (git-hash)
commit d4863a5da629376462a0ca431c0e84f56f1cf180
Author: Flavio Castelli<EMAIL_ADDRESS>Date:   Sun Jan 14 14:46:36 2018 +0100
Description of Issue/Question
Terraform crashes while creating a virtual machine
Setup
Latest updated Fedora 27 (updated 6th Feb 2018)
Latest Terraform built from git
Latest terraform-provider-libvirt built from git
Terraform Plan
[root@laptop k801]# cat k801.tf
provider "libvirt" {
uri = "qemu:///system"
}
// blank 32GB image for net install.
resource "libvirt_volume" "k801-qcow2" {
name = "k801-qcow2"
pool = "default"
format = "qcow2"
size =<PHONE_NUMBER>80
}
// set boot order hd, network
resource "libvirt_domain" "k801-qcow2" {
name = "k801"
memory = "2048"
vcpu = 2
network_interface {
network_name = "dc00-10"
}
boot_device {
dev = [ "hd", "network"]
}
disk {
volume_id = "${libvirt_volume.k801-qcow2.id}"
}
graphics {
type = "spice"
autoport = "yes"
address = "<IP_ADDRESS>"
listen_type = "address"
}
}
Steps to Reproduce Issue
Latest updated Fedora 27 (updated 6th Feb 2018)
Latest Terraform built from git
Latest terraform-provider-libvirt built from git

Additional Infos:
Virtual machine is still created and installs as expected.
Appears Terraform simply time out after 30seconds and then crashes due to
panic: runtime error: invalid memory address or nil pointer dereference:
Shell session:
[root@laptop k801]# terraform apply -auto-approve
Initializing provider plugins...
Terraform has been successfully initialized!
You may now begin working with Terraform. Try running "terraform plan" to see
any changes that are required for your infrastructure. All Terraform commands
should now work.
If you ever set or change modules or backend configuration for Terraform,
rerun this command to reinitialize your working directory. If you forget, other
commands will detect it and remind you to do so if necessary.
libvirt_volume.k801-qcow2: Creating...
format: "" => "qcow2"
name:   "" => "k801-qcow2"
pool:   "" => "default"
size:   "" => "343597383680"
libvirt_volume.k801-qcow2: Creation complete after 0s (ID: /var/lib/libvirt/images/k801-qcow2)
libvirt_domain.k801-qcow2: Creating...
arch:                             "" => ""
boot_device.#:                    "" => "1"
boot_device.0.dev.#:              "" => "2"
boot_device.0.dev.0:              "" => "hd"
boot_device.0.dev.1:              "" => "network"
disk.#:                           "" => "1"
disk.0.%:                         "" => "1"
disk.0.volume_id:                 "" => "/var/lib/libvirt/images/k801-qcow2"
emulator:                         "" => ""
graphics.%:                       "" => "4"
graphics.address:                 "" => "<IP_ADDRESS>"
graphics.autoport:                "" => "yes"
graphics.listen_type:             "" => "address"
graphics.type:                    "" => "spice"
machine:                          "" => ""
memory:                           "" => "2048"
name:                             "" => "k801"
network_interface.#:              "" => "1"
network_interface.0.addresses.#:  "" => ""
network_interface.0.hostname:     "" => ""
network_interface.0.mac:          "" => ""
network_interface.0.network_id:   "" => ""
network_interface.0.network_name: "" => "dc00-10"
vcpu:                             "" => "2"
libvirt_domain.k801-qcow2: Still creating... (10s elapsed)
libvirt_domain.k801-qcow2: Still creating... (20s elapsed)
libvirt_domain.k801-qcow2: Still creating... (30s elapsed)
Error: Error applying plan:
1 error(s) occurred:
panic: runtime error: invalid memory address or nil pointer dereference
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: [signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0xab6e28]
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt:
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: goroutine 31 [running]:
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/libvirt.getDomainInterfacesFromNetworks(0x0, 0x0, 0xc420477c58, 0x6, 0xc420477c88, 0x3, 0xc420477c9c, 0x4, 0xc42031a450, 0x24, ...)
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/libvirt/domain.go:215 +0x6b8
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/libvirt.domainGetIfacesInfo(0x7fd158001ea0, 0x0, 0x0, 0xc420477c58, 0x6, 0xc420477c88, 0x3, 0xc420477c9c, 0x4, 0xc42031a450, ...)
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/libvirt/domain.go:167 +0x188
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/libvirt.resourceLibvirtDomainRead(0xc4202b7180, 0xc2e9e0, 0xc42000edb8, 0x0, 0x0)
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/libvirt/resource_libvirt_domain.go:987 +0x1e4e
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/libvirt.resourceLibvirtDomainCreate(0xc4202b7180, 0xc2e9e0, 0xc42000edb8, 0x0, 0x0)
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/libvirt/resource_libvirt_domain.go:718 +0x542c
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/helper/schema.(*Resource).Apply(0xc4202eeb40, 0xc4202665f0, 0xc42025db00, 0xc2e9e0, 0xc42000edb8, 0x1, 0xc4203f0810, 0xd05c00)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/helper/schema/resource.go:193 +0x3b6
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/helper/schema.(*Provider).Apply(0xc4203821c0, 0xc4202665a0, 0xc4202665f0, 0xc42025db00, 0x7fd1760ce6c8, 0x0, 0xd40ce0)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/helper/schema/provider.go:259 +0xa4
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/plugin.(*ResourceProviderServer).Apply(0xc4202e9040, 0xc42025daa0, 0xc42044c130, 0x0, 0x0)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/vendor/github.com/hashicorp/terraform/plugin/resource_provider.go:488 +0x57
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: reflect.Value.call(0xc420067620, 0xc42000eba8, 0x13, 0xdc0788, 0x4, 0xc420046f20, 0x3, 0x3, 0xc4202fa6e8, 0xc4201af4b8, ...)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/usr/lib/golang/src/reflect/value.go:434 +0x905
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: reflect.Value.Call(0xc420067620, 0xc42000eba8, 0x13, 0xc4202fa720, 0x3, 0x3, 0xc400000003, 0x0, 0x0)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/usr/lib/golang/src/reflect/value.go:302 +0xa4
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: net/rpc.(*service).call(0xc4203986c0, 0xc42008af00, 0xc42039a120, 0xc4200b4d00, 0xc4202e9140, 0xc319e0, 0xc42025daa0, 0x16, 0xc31a20, 0xc42044c130, ...)
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/usr/lib/golang/src/net/rpc/server.go:381 +0x142
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: created by net/rpc.(*Server).ServeCodec
2018-02-06T14:37:09.900Z [DEBUG] plugin.terraform-provider-libvirt: 	/usr/lib/golang/src/net/rpc/server.go:475 +0x36b
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalWriteState
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalApplyProvisioners
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalIf
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalWriteState
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalWriteDiff
2018/02/06 14:37:09 [TRACE] root: eval: *terraform.EvalApplyPost
2018-02-06T14:37:09.901Z [DEBUG] plugin: plugin process exited: path=/root/go/bin/terraform-provider-libvirt
2018/02/06 14:37:09 [ERROR] root: eval: *terraform.EvalApplyPost, err: 1 error(s) occurred:

libvirt_domain.k801-qcow2: unexpected EOF
2018/02/06 14:37:09 [ERROR] root: eval: *terraform.EvalSequence, err: 1 error(s) occurred:

libvirt_domain.k801-qcow2: unexpected EOF
2018/02/06 14:37:09 [TRACE] [walkApply] Exiting eval tree: libvirt_domain.k801-qcow2
2018/02/06 14:37:09 [TRACE] dag/walk: upstream errored, not walking "meta.count-boundary (count boundary fixup)"
2018/02/06 14:37:09 [TRACE] dag/walk: upstream errored, not walking "provider.libvirt (close)"
2018/02/06 14:37:09 [TRACE] dag/walk: upstream errored, not walking "root"
2018/02/06 14:37:09 [TRACE] Preserving existing state lineage "7acf523d-b4b0-424e-80f5-c1220fbd85ee"
2018/02/06 14:37:09 [DEBUG] plugin: waiting for all plugin processes to complete...
2018-02-06T14:37:09.905Z [WARN ] plugin: error closing client during Kill: err="connection is shut down"

libvirt_domain.k801-qcow2: 1 error(s) occurred:

libvirt_domain.k801-qcow2: unexpected EOF

Terraform does not automatically rollback in the face of errors.
!!!!!!!!!!!!!!!!!!!!!!!!!!! TERRAFORM CRASH !!!!!!!!!!!!!!!!!!!!!!!!!!!!
Terraform crashed! This is always indicative of a bug within Terraform.
A crash log has been placed at "crash.log" relative to your current
working directory. It would be immensely helpful if you could please
report the crash with Terraform1 so that we can fix this.
When reporting bugs, please include your terraform version. That
information is available on the first line of crash.log. You can also
get it by running 'terraform --version' on the command line.
!!!!!!!!!!!!!!!!!!!!!!!!!!! TERRAFORM CRASH !!!!!!!!!!!!!!!!!!!!!!!!!!!!
Instead, your Terraform state file has been partially updated with
any resources that successfully completed. Please address the error
above and apply again to incrementally change your infrastructure.
[root@laptop k801]#
Selinux or Firewall:
Selinux disabled
iptables disabled and flushed

crash.log

2018-02-06T14:37:09.896Z [DEBUG] plugin.terraform-provider-libvirt: 2018/02/06 14:37:09 [WARN] WaitForState timeout after 30s
2018-02-06T14:37:09.896Z [DEBUG] plugin.terraform-provider-libvirt: 2018/02/06 14:37:09 [WARN] WaitForState starting 30s refresh grace period
2018-02-06T14:37:09.896Z [DEBUG] plugin.terraform-provider-libvirt: 2018/02/06 14:37:09 [DEBUG] getting domain addresses from networks
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: panic: runtime error: invalid memory address or nil pointer dereference
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: [signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0xab6e28]
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt:
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: goroutine 31 [running]:
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: github.com/dmacvicar/terraform-provider-libvirt/libvirt.getDomainInterfacesFromNetworks(0x0, 0x0, 0xc420477c58, 0x6, 0xc420477c88, 0x3, 0xc420477c9c, 0x4, 0xc42031a450, 0x24, ...)
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: 	/root/go/src/github.com/dmacvicar/terraform-provider-libvirt/libvirt/domain.go:215 +0x6b8

Perhaps my libvirt setup is incorrect. I'm using a separate dhcp service rather then the libvirt dhcp.
WIll change and re-test
2018-02-06T14:37:09.896Z [DEBUG] plugin.terraform-provider-libvirt: 2018/02/06 14:37:09 [WARN] WaitForState starting 30s refresh grace period
2018-02-06T14:37:09.896Z [DEBUG] plugin.terraform-provider-libvirt: 2018/02/06 14:37:09 [DEBUG] getting domain addresses from networks
2018-02-06T14:37:09.899Z [DEBUG] plugin.terraform-provider-libvirt: panic: runtime error: invalid memory address or nil pointer dereference

Fixed!
 Resources: 2 added, 0 changed, 0 destroyed.
[root@laptop k801]#

Closing, fixed as explained above.


waymore work stop due to empty line

Hi ,
if the input contain just one empty line we get "Each line of the input file must contain a domain only (with no schema)...." error even all other lines well formed .
I hop you will fix this issue , because as you know it's comman to have empty lines from other recon tool output .

Hi @StrglrX
You are right, sorry about that! That has been fixed now if you get the newest version 1.19. Thanks for using the tool and taking the time to raise the issue!