Ошибка Pytorch при запуске изображения Pytorch на Kubernetes

Ошибка Pytorch при запуске изображения Pytorch на Kubernetes ⇐ Python

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Anonymous

Ошибка Pytorch при запуске изображения Pytorch на Kubernetes

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Сообщение Anonymous » 05 май 2025, 06:43

I have a Docker image that uses PyTorch to perform object detection.
The container runs fine on local and on Google Colab, however when running on Kubernetes (through Airflow) it raises the following error:

Код: Выделить всё

[2021-06-23 07:13:17,592] {pod_launcher.py:148} INFO - Traceback (most recent call last):
[2021-06-23 07:13:17,592] {pod_launcher.py:148} INFO -   File "/content/main.py", line 5, in 
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     app()
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/typer/main.py", line 214, in __call__
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     return get_command(self)(*args, **kwargs)
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 829, in __call__
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     return self.main(*args, **kwargs)
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 782, in main
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     rv = self.invoke(ctx)
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 1259, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return _process_result(sub_ctx.command.invoke(sub_ctx))
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 1066, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return ctx.invoke(self.callback, **ctx.params)
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 610, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return callback(*args, **kwargs)
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/typer/main.py", line 497, in wrapper
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -     return callback(**use_params)  # type:  ignore
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -   File "/content/app/__init__.py", line 52, in detect_from_file
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     coco_path=coco_path,
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/app/__init__.py", line 126, in _detect_from_file
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     tables = infer_page(page_filename, model)
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/app/utils.py", line 9, in infer_page
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     result = inference_detector(model, str(img))
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/apis/inference.py", line 86, in inference_detector
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     result = model(return_loss=False, rescale=True, **data)
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 532, in __call__
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     result = self.forward(*input, **kwargs)
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/core/fp16/decorators.py", line 49, in new_func
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     return old_func(*args, **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/base.py", line 149, in forward
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -     return self.forward_test(img, img_metas, **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/base.py", line 130, in forward_test
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -     return self.simple_test(imgs[0], img_metas[0], **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/cascade_rcnn.py", line 324, in simple_test
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     self.test_cfg.rpn) if proposals is None else proposals
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/test_mixins.py", line 34, in simple_test_rpn
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     proposal_list = self.rpn_head.get_bboxes(*proposal_inputs)
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/core/fp16/decorators.py", line 127, in new_func
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     return old_func(*args, **kwargs)
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/anchor_heads/anchor_head.py", line 276, in get_bboxes
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     scale_factor, cfg, rescale)
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/anchor_heads/rpn_head.py", line 92, in get_bboxes_single
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -     proposals, _ = nms(proposals, cfg.nms_thr)
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/ops/nms/nms_wrapper.py", line 54, in nms
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -     inds = nms_cuda.nms(dets_th, iou_thr)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - RuntimeError: CUDA error: no kernel image is available for execution on the device (launch_kernel at /pytorch/aten/src/ATen/native/cuda/Loops.cuh:103)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #0: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x33 (0x7faf44434193 in /usr/local/lib/python3.6/dist-packages/torch/lib/libc10.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #1: void at::native::gpu_index_kernel(at::TensorIterator&, c10::ArrayRef, c10::ArrayRef, __nv_dl_wrapper_t  const&) + 0x7bb (0x7faefc45e87b in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #2:  + 0x580fc32 (0x7faefc458c32 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #3:  + 0x580ff88 (0x7faefc458f88 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #4:  + 0x1a7493b (0x7faef86bd93b in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #5: at::native::index(at::Tensor const&, c10::ArrayRef) + 0x47e (0x7faef86b96fe in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #6:  + 0x1fe06aa (0x7faef8c296aa in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #7:  + 0x1fe5173 (0x7faef8c2e173 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #8:  + 0x3bffe6a (0x7faefa848e6a in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #9:  + 0x1fe5173 (0x7faef8c2e173 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #10: at::Tensor c10::KernelFunction::callUnboxedOnly(at::Tensor const&, c10::ArrayRef) const + 0xa3 (0x7faef3b7ec73 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #11: c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const::{lambda(ska::flat_hash_map const&)#1}::operator()(ska::flat_hash_map const&) const + 0xc9 (0x7faef3b7c331 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #12: std::result_of::type c10::LeftRight::read(c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const::{lambda(ska::flat_hash_map const&)#1}&&) const + 0x128 (0x7faef3b7eed2 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #13: at::Tensor c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const + 0x6a (0x7faef3b7c3ba in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #14: c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}::operator()(c10::DispatchTable const&) const + 0x80 (0x7faef3b7936a in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #15: std::result_of::type c10::LeftRight::read(c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}&&) const + 0x128 (0x7faef3b7f056 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #16: c10::guts::infer_function_traits::type::return_type c10::impl::OperatorEntry::readDispatchTable(c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}&&) const + 0x4a (0x7faef3b7c42c in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #17: at::Tensor c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const + 0x7c (0x7faef3b7941a in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #18: at::Tensor::index(c10::ArrayRef) const + 0x16f (0x7faef3b74dad in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #19: nms_cuda(at::Tensor, float) + 0x84f (0x7faef3b71a0c in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #20: nms(at::Tensor const&, float) + 0xee (0x7faef3b6087e in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #21:  + 0x335ab (0x7faef3b6f5ab in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #22:  + 0x302b0 (0x7faef3b6c2b0 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)

Ниже приведен вывод команды nvidia-smi и еще одного UTIL MMDetection , выполняемой как на Kubernetes, так и на Google Colab (где код работает просто хорошо)
Вывод, работающий на kubernetes

Код: Выделить всё

nvidia-smi

Код: Выделить всё

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    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  Tesla P100-PCIE...  Off  | 00000001:00:00.0 Off |                    0 |
| N/A   23C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
< /code>
[list]
[*]python3 /content/mmdetection/mmdet/utils/collect_env.py

[/list]

Код: Выделить всё

sys.platform: linux
Python: 3.6.9 (default, Jan 26 2021, 15:33:00) [GCC 8.4.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 10.0, V10.0.130
GPU 0: Tesla P100-PCIE-16GB
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.4.0+cu100
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a.  OpenMP 4.5)
- NNPACK is enabled
- CUDA Runtime 10.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.1
- Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Wno-stringop-overflow, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.5.0+cu100
OpenCV: 4.5.2
MMCV: 0.4.3
MMDetection: 1.2.0+unknown
MMDetection Compiler: GCC 7.5
MMDetection CUDA Compiler: 10.0
< /code>
  Вывод, запускающий код в Google colab < /strong> < /h2>
[list]
[*]nvidia-smi

[/list]

Код: Выделить всё

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.27       Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| 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  Tesla V100-SXM2...  Off  | 00000000:00:04.0 Off |                    0 |
| N/A   37C    P0    25W / 300W |      0MiB / 16160MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
< /code>
[list]
[*]python3 /content/mmdetection/mmdet/utils/collect_env.py

[/list]

Код: Выделить всё

sys.platform: linux
Python: 3.7.10 (default, May  3 2021, 02:48:31) [GCC 7.5.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.0_bu.TC445_37.28845127_0
GPU 0: Tesla V100-SXM2-16GB
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.4.0+cu100
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a.  OpenMP 4.5)
- NNPACK is enabled
- CUDA Runtime 10.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.1
- Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Wno-stringop-overflow, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.5.0+cu100
OpenCV: 4.5.2
MMCV: 0.4.3
MMDetection: 1.2.0+0f33c08
MMDetection Compiler: GCC 7.5
MMDetection CUDA Compiler: 11.0

Примечание: [/b] вывод, размещенный здесь для Google Colab, работал на графическом процессоре Tesla v100, однако иногда я выделяю Tesla P100 (который является одним и тем же графическим процессором, используемым на Kubernetes), а код работает плавно по обоим случаям (на Google Colab), однако, что это ошибочно, когда на kubernet -netes). ценится

Подробнее здесь: https://stackoverflow.com/questions/680 ... kubernetes

1746416634

Anonymous

I have a Docker image that uses PyTorch to perform object detection.
The container runs fine on [b]local[/b] and on [b]Google Colab[/b], however when running on [b]Kubernetes[/b] (through [b]Airflow[/b]) it raises the following error:
[code][2021-06-23 07:13:17,592] {pod_launcher.py:148} INFO - Traceback (most recent call last):
[2021-06-23 07:13:17,592] {pod_launcher.py:148} INFO -   File "/content/main.py", line 5, in 
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     app()
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/typer/main.py", line 214, in __call__
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     return get_command(self)(*args, **kwargs)
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 829, in __call__
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -     return self.main(*args, **kwargs)
[2021-06-23 07:13:17,594] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 782, in main
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     rv = self.invoke(ctx)
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 1259, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return _process_result(sub_ctx.command.invoke(sub_ctx))
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 1066, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return ctx.invoke(self.callback, **ctx.params)
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/click/core.py", line 610, in invoke
[2021-06-23 07:13:17,595] {pod_launcher.py:148} INFO -     return callback(*args, **kwargs)
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/typer/main.py", line 497, in wrapper
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -     return callback(**use_params)  # type:  ignore
[2021-06-23 07:13:17,596] {pod_launcher.py:148} INFO -   File "/content/app/__init__.py", line 52, in detect_from_file
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     coco_path=coco_path,
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/app/__init__.py", line 126, in _detect_from_file
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     tables = infer_page(page_filename, model)
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/app/utils.py", line 9, in infer_page
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -     result = inference_detector(model, str(img))
[2021-06-23 07:13:17,597] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/apis/inference.py", line 86, in inference_detector
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     result = model(return_loss=False, rescale=True, **data)
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -   File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 532, in __call__
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     result = self.forward(*input, **kwargs)
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/core/fp16/decorators.py", line 49, in new_func
[2021-06-23 07:13:17,598] {pod_launcher.py:148} INFO -     return old_func(*args, **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/base.py", line 149, in forward
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -     return self.forward_test(img, img_metas, **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/base.py", line 130, in forward_test
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -     return self.simple_test(imgs[0], img_metas[0], **kwargs)
[2021-06-23 07:13:17,599] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/cascade_rcnn.py", line 324, in simple_test
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     self.test_cfg.rpn) if proposals is None else proposals
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/detectors/test_mixins.py", line 34, in simple_test_rpn
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     proposal_list = self.rpn_head.get_bboxes(*proposal_inputs)
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/core/fp16/decorators.py", line 127, in new_func
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     return old_func(*args, **kwargs)
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/anchor_heads/anchor_head.py", line 276, in get_bboxes
[2021-06-23 07:13:17,600] {pod_launcher.py:148} INFO -     scale_factor, cfg, rescale)
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/models/anchor_heads/rpn_head.py", line 92, in get_bboxes_single
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -     proposals, _ = nms(proposals, cfg.nms_thr)
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -   File "/content/mmdetection/mmdet/ops/nms/nms_wrapper.py", line 54, in nms
[2021-06-23 07:13:17,601] {pod_launcher.py:148} INFO -     inds = nms_cuda.nms(dets_th, iou_thr)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - RuntimeError: CUDA error: no kernel image is available for execution on the device (launch_kernel at /pytorch/aten/src/ATen/native/cuda/Loops.cuh:103)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #0: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x33 (0x7faf44434193 in /usr/local/lib/python3.6/dist-packages/torch/lib/libc10.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #1: void at::native::gpu_index_kernel(at::TensorIterator&, c10::ArrayRef, c10::ArrayRef, __nv_dl_wrapper_t  const&) + 0x7bb (0x7faefc45e87b in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #2:  + 0x580fc32 (0x7faefc458c32 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #3:  + 0x580ff88 (0x7faefc458f88 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,602] {pod_launcher.py:148} INFO - frame #4:  + 0x1a7493b (0x7faef86bd93b in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #5: at::native::index(at::Tensor const&, c10::ArrayRef) + 0x47e (0x7faef86b96fe in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #6:  + 0x1fe06aa (0x7faef8c296aa in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #7:  + 0x1fe5173 (0x7faef8c2e173 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,603] {pod_launcher.py:148} INFO - frame #8:  + 0x3bffe6a (0x7faefa848e6a in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #9:  + 0x1fe5173 (0x7faef8c2e173 in /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #10: at::Tensor c10::KernelFunction::callUnboxedOnly(at::Tensor const&, c10::ArrayRef) const + 0xa3 (0x7faef3b7ec73 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #11: c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const::{lambda(ska::flat_hash_map const&)#1}::operator()(ska::flat_hash_map const&) const + 0xc9 (0x7faef3b7c331 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #12: std::result_of::type c10::LeftRight::read(c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const::{lambda(ska::flat_hash_map const&)#1}&&) const + 0x128 (0x7faef3b7eed2 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #13: at::Tensor c10::Dispatcher::doCallUnboxedOnly(c10::DispatchTable const&, c10::LeftRight const&, at::Tensor const&, c10::ArrayRef) const + 0x6a (0x7faef3b7c3ba in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #14: c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}::operator()(c10::DispatchTable const&) const + 0x80 (0x7faef3b7936a in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #15: std::result_of::type c10::LeftRight::read(c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}&&) const + 0x128 (0x7faef3b7f056 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #16: c10::guts::infer_function_traits::type::return_type c10::impl::OperatorEntry::readDispatchTable(c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const::{lambda(c10::DispatchTable const&)#1}&&) const + 0x4a (0x7faef3b7c42c in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,604] {pod_launcher.py:148} INFO - frame #17: at::Tensor c10::Dispatcher::callUnboxedOnly(c10::OperatorHandle const&, at::Tensor const&, c10::ArrayRef) const + 0x7c (0x7faef3b7941a in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #18: at::Tensor::index(c10::ArrayRef) const + 0x16f (0x7faef3b74dad in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #19: nms_cuda(at::Tensor, float) + 0x84f (0x7faef3b71a0c in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #20: nms(at::Tensor const&, float) + 0xee (0x7faef3b6087e in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #21:  + 0x335ab (0x7faef3b6f5ab in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[2021-06-23 07:13:17,605] {pod_launcher.py:148} INFO - frame #22:  + 0x302b0 (0x7faef3b6c2b0 in /content/mmdetection/mmdet/ops/nms/nms_cuda.cpython-36m-x86_64-linux-gnu.so)
[/code]
Ниже приведен вывод команды nvidia-smi  и еще одного UTIL MMDetection , выполняемой как на Kubernetes, так и на Google Colab (где код работает просто хорошо) 
 [b] Вывод, работающий на kubernetes  

 
 [code]nvidia-smi[/code] 

[code]+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    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  Tesla P100-PCIE...  Off  | 00000001:00:00.0 Off |                    0 |
| N/A   23C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
< /code>
[list]
[*]python3 /content/mmdetection/mmdet/utils/collect_env.py[/code]
[/list]
[code]sys.platform: linux
Python: 3.6.9 (default, Jan 26 2021, 15:33:00) [GCC 8.4.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 10.0, V10.0.130
GPU 0: Tesla P100-PCIE-16GB
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.4.0+cu100
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a.  OpenMP 4.5)
- NNPACK is enabled
- CUDA Runtime 10.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.1
- Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Wno-stringop-overflow, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.5.0+cu100
OpenCV: 4.5.2
MMCV: 0.4.3
MMDetection: 1.2.0+unknown
MMDetection Compiler: GCC 7.5
MMDetection CUDA Compiler: 10.0
< /code>
  Вывод, запускающий код в Google colab < /strong> < /h2>
[list]
[*]nvidia-smi[/code]
[/list]
[code]+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.27       Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| 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  Tesla V100-SXM2...  Off  | 00000000:00:04.0 Off |                    0 |
| N/A   37C    P0    25W / 300W |      0MiB / 16160MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
< /code>
[list]
[*]python3 /content/mmdetection/mmdet/utils/collect_env.py[/code]
[/list]
[code]sys.platform: linux
Python: 3.7.10 (default, May  3 2021, 02:48:31) [GCC 7.5.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.0_bu.TC445_37.28845127_0
GPU 0: Tesla V100-SXM2-16GB
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.4.0+cu100
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a.  OpenMP 4.5)
- NNPACK is enabled
- CUDA Runtime 10.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.1
- Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Wno-stringop-overflow, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.5.0+cu100
OpenCV: 4.5.2
MMCV: 0.4.3
MMDetection: 1.2.0+0f33c08
MMDetection Compiler: GCC 7.5
MMDetection CUDA Compiler: 11.0
[/code]
 Примечание: [/b] вывод, размещенный здесь для Google Colab, работал на графическом процессоре Tesla v100, однако иногда я выделяю Tesla P100 (который является одним и тем же графическим процессором, используемым на Kubernetes), а код работает плавно по обоим случаям (на Google Colab), однако, что это ошибочно, когда на kubernet -netes). ценится  

Подробнее здесь: [url]https://stackoverflow.com/questions/68095962/pytorch-error-when-running-pytorch-image-on-kubernetes[/url]

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Добавлено в форуме JAVA

Anonymous » 18 окт 2024, 23:04 » в форуме JAVA

Я использую kubernetes-client/java API и хочу программно получить статус всех модулей во всех пространствах имен. Мой код основан на этом примере Java-библиотеки Kubernetes.

Вот фрагмент моего кода:

Watch watch = Watch.createWatch(
client,...

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Последнее сообщение Anonymous
18 окт 2024, 23:04
Понимание Kubernetes Watch (kubernetes-client/java api)

Последнее сообщение Anonymous « 18 окт 2024, 23:36
Добавлено в форуме JAVA

Anonymous » 18 окт 2024, 23:36 » в форуме JAVA

Я использую kubernetes-client/java API и хочу программно получить статус всех модулей во всех пространствах имен. Мой код основан на этом примере Java-библиотеки Kubernetes.

Вот фрагмент моего кода:

Watch watch = Watch.createWatch(
client,...

0 Ответы

25 Просмотры

Последнее сообщение Anonymous
18 окт 2024, 23:36
Spring-Cloud-Deployer-Kubernetes: 2.9.5 и Kubernetes-Model-Core: 7.3.1

Последнее сообщение Anonymous « 26 май 2025, 20:11
Добавлено в форуме JAVA

Anonymous » 26 май 2025, 20:11 » в форуме JAVA

Я хочу использовать вышеупомянутые версии вместе, но с ошибкой с ошибкой:
java.lang.NoSuchMethodError: 'io.fabric8.kubernetes.api.model.HTTPGetActionFluent io.fabric8.kubernetes.api.model.HTTPGetActionBuilder.withNewPort(java.lang.Integer)'

То,...

0 Ответы

1 Просмотры

Последнее сообщение Anonymous
26 май 2025, 20:11
Spring-Cloud-Deployer-Kubernetes: 2.9.5 и Kubernetes-Model-Core: 7.3.1

Последнее сообщение Anonymous « 29 май 2025, 11:45
Добавлено в форуме JAVA

Anonymous » 29 май 2025, 11:45 » в форуме JAVA

Я хочу использовать вышеупомянутые версии вместе, но с ошибкой с ошибкой:
java.lang.NoSuchMethodError: 'io.fabric8.kubernetes.api.model.HTTPGetActionFluent io.fabric8.kubernetes.api.model.HTTPGetActionBuilder.withNewPort(java.lang.Integer)'

То,...

0 Ответы

1 Просмотры

Последнее сообщение Anonymous
29 май 2025, 11:45

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