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Couldn't create nuclio functions #2067
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BTW, I see a similar error message for this function (in error state) in the nuclio dashboard
|
@jinzishuai , are you able to deploy any other serverless functions? Please run |
@nmanovic I think you are on the right direction
My nucli version is 1.4.17
But my dashboard is running on version 1.4.8. Do you think that is a problem? |
I did downgrade to the same I don't see anything |
Hello, I have the same problem. I have tried nucleo versions 1.5.16 and the newest one 1.6.1. Does anyone have any suggestions? |
I have the same problem did may be 10 new installs on different ubuntu version 18.04 19 20 20.10 |
@kiteklan , could you please post your error message please? Let's try to investigate the issue together. |
I had workaround the problem but seems like cvat serverless+nuclio has an issue with all kernel versions running on hyper-v , I had solved it by installing on a proxmox cpu type “host” so that the virtual machine will use all the cpu assets. |
|
nuctl deploy --project-name cvat
--path serverless/openvino/omz/public/yolo-v3-tf/nuclio
--volume pwd/serverless/common:/opt/nuclio/common
--platform local
tryinh to install the following function to nuclio with 1.5.6 and always
breaking up with the command
========= Converting yolo-v3-tf to IR (FP32)
Conversion command: /usr/bin/python3 --
/opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf
--data_type=FP32
--output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32
--model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1
'--scale_values=input_1[255]' --reverse_input_channels
--transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json
--input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb
FAILED:
yolo-v3-tf
.......
Error - exit status 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Call stack:
stdout:
Sending build context to Docker daemon 44.69MB
Step 1/16 : FROM openvino/ubuntu18_dev:2020.2
---> bf7a4dff2d97
Step 2/16 : ARG NUCLIO_LABEL
---> Using cache
---> c9a10c5b4f05
Step 3/16 : ARG NUCLIO_ARCH
---> Using cache
---> 8ed29e90bf42
Step 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR
---> Using cache
---> fc2cdf7bdff6
Step 5/16 : USER root
---> Using cache
---> 44197e8724ab
Step 6/16 : WORKDIR /opt/nuclio
---> Using cache
---> 4b2adc3eb6f5
Step 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip
---> Using cache
---> 11dc453d1c27
Step 8/16 : RUN
/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py
--name yolo-v3-tf -o /opt/nuclio/open_model_zoo
---> Using cache
---> f6ec46de8b52
Step 9/16 : RUN
/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py
--name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o
/opt/nuclio/open_model_zoo
---> Running in 762f8276d957
�[91m+
/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py
--name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o
/opt/nuclio/open_model_zoo
�[0m========= Converting yolo-v3-tf to IR (FP32)
Conversion command: /usr/bin/python3 --
/opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf
--data_type=FP32
--output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32
--model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1
'--scale_values=input_1[255]' --reverse_input_channels
--transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json
--input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb
FAILED:
yolo-v3-tf
Removing intermediate container 762f8276d957
stderr:
The command '/bin/bash -xo pipefail -c
/opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py
--name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o
/opt/nuclio/open_model_zoo' returned a non-zero code: 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Failed to build
/nuclio/pkg/dockerclient/shell.go:118
Failed to build docker image
.../pkg/containerimagebuilderpusher/docker.go:53
Failed to build processor image
/nuclio/pkg/processor/build/builder.go:250
…On Fri, Apr 23, 2021 at 12:23 PM Nikita Manovich ***@***.***> wrote:
@kiteklan <https://github.com/kiteklan> , could you please post your
error message please? Let's try to investigate the issue together.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
<#2067 (comment)>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/ASI2NWZKRXOFVJ5TWO4MZM3TKE37ZANCNFSM4QI4JQ5Q>
.
|
Pls let me know what else I can send to help. I really like the cvat .I still keep the problematic hyper-v version with all stages’ snapshots of you need share the ssh. Deploy_cpu script can install some functions , some not but I really needed yolov3. Others give similar errors |
here is the full log.
On Fri, Apr 23, 2021 at 12:23 PM Nikita Manovich ***@***.***> wrote:
@kiteklan <https://github.com/kiteklan> , could you please post your
error message please? Let's try to investigate the issue together.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
<#2067 (comment)>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/ASI2NWZKRXOFVJ5TWO4MZM3TKE37ZANCNFSM4QI4JQ5Q>
.
Welcome to Ubuntu 18.04.4 LTS (GNU/Linux 4.15.0-142-generic x86_64)
* Documentation: https://help.ubuntu.com
* Management: https://landscape.canonical.com
* Support: https://ubuntu.com/advantage
System information as of Fri Apr 23 11:53:22 UTC 2021
System load: 0.81 Processes: 199
Usage of /: 32.2% of 124.50GB Users logged in: 1
Memory usage: 18% IP address for eth0: xxxxxxxxxx
Swap usage: 0% IP address for docker0: 172.17.0.1
* Canonical Livepatch is available for installation.
- Reduce system reboots and improve kernel security. Activate at:
https://ubuntu.com/livepatch
8 packages can be updated.
0 of these updates are security updates.
To see these additional updates run: apt list --upgradable
New release '20.04.2 LTS' available.
Run 'do-release-upgrade' to upgrade to it.
Last login: Fri Apr 23 11:48:47 2021
.
.
.
***@***.***:~$ ls
cvat
***@***.***:~/cvat# cd serverless
***@***.***:~/cvat/serverless# ls
common deploy_cpu.sh deploy_gpu.sh openvino pytorch tensorflow
***@***.***:~/cvat/serverless# ./deploy_cpu.sh
Deploying /root/cvat/serverless/openvino/dextr function...
21.04.23 12:20:46.925 nuctl (I) Deploying function {"name": ""}
21.04.23 12:20:46.925 nuctl (I) Building {"versionInfo": "Label: 1.5.16, Git commit: ae43a6a560c2bec42d7ccfdf6e8e11a1e3cc3774, OS: linux, Arch: amd64, Go version: go1.14.3", "name": ""}
21.04.23 12:20:47.285 nuctl (I) Cleaning up before deployment {"functionName": "openvino-dextr"}
21.04.23 12:20:47.398 nuctl (I) Function already exists, deleting function containers {"functionName": "openvino-dextr"}
21.04.23 12:20:47.843 nuctl (I) Staging files and preparing base images
21.04.23 12:20:47.844 nuctl (I) Building processor image {"imageName": "cvat/openvino.dextr:latest"}
21.04.23 12:20:47.844 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.5.16-amd64"}
21.04.23 12:20:57.969 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
21.04.23 12:21:09.235 nuctl.platform (I) Building docker image {"image": "cvat/openvino.dextr:latest"}
21.04.23 12:21:09.875 nuctl.platform (I) Pushing docker image into registry {"image": "cvat/openvino.dextr:latest", "registry": ""}
21.04.23 12:21:09.875 nuctl.platform (I) Docker image was successfully built and pushed into docker registry {"image": "cvat/openvino.dextr:latest"}
21.04.23 12:21:09.875 nuctl (I) Build complete {"result": {"Image":"cvat/openvino.dextr:latest","UpdatedFunctionConfig":{"metadata":{"name":"openvino-dextr","namespace":"nuclio","labels":{"nuclio.io/project-name":"cvat"},"annotations":{"framework":"openvino","min_pos_points":"4","name":"DEXTR","spec":"","type":"interactor"}},"spec":{"description":"Deep Extreme Cut","handler":"main:handler","runtime":"python:3.6","env":[{"name":"NUCLIO_PYTHON_EXE_PATH","value":"/opt/nuclio/common/openvino/python3"}],"resources":{},"image":"cvat/openvino.dextr:latest","targetCPU":75,"triggers":{"myHttpTrigger":{"class":"","kind":"http","name":"myHttpTrigger","maxWorkers":2,"workerAvailabilityTimeoutMilliseconds":10000,"attributes":{"maxRequestBodySize":33554432}}},"volumes":[{"volume":{"name":"volume-1","hostPath":{"path":"/root/cvat/serverless/common"}},"volumeMount":{"name":"volume-1","mountPath":"/opt/nuclio/common"}}],"build":{"image":"cvat/openvino.dextr","baseImage":"openvino/ubuntu18_runtime:2020.2","directives":{"postCopy":[{"kind":"RUN","value":"curl -O https://download.01.org/openvinotoolkit/models_contrib/cvat/dextr_model_v1.zip"},{"kind":"RUN","value":"unzip dextr_model_v1.zip"},{"kind":"RUN","value":"pip3 install Pillow"}],"preCopy":[{"kind":"USER","value":"root"},{"kind":"WORKDIR","value":"/opt/nuclio"},{"kind":"RUN","value":"ln -s /usr/bin/pip3 /usr/bin/pip"}]},"codeEntryType":"image"},"platform":{"attributes":{"mountMode":"volume","restartPolicy":{"maximumRetryCount":3,"name":"always"}}},"readinessTimeoutSeconds":60,"securityContext":{},"eventTimeout":"30s"}}}}
21.04.23 12:21:14.833 nuctl.platform.docker (W) Failed to run container {"err": "stdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n", "errVerbose": "\nError - exit status 125\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nstdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n", "errCauses": [{"error": "exit status 125"}], "stdout": "a7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n", "stderr": ""}
21.04.23 12:21:14.833 nuctl (W) Failed to create a function; setting the function status {"err": "Failed to run a Docker container", "errVerbose": "\nError - exit status 125\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to run a Docker container\n /nuclio/pkg/platform/local/platform.go:653\nFailed to run a Docker container", "errCauses": [{"error": "stdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n", "errorVerbose": "\nError - exit status 125\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nstdout:\na7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35\ndocker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.\n\nstderr:\n", "errorCauses": [{"error": "exit status 125"}]}]}
Error - exit status 125
/nuclio/pkg/cmdrunner/shellrunner.go:96
Call stack:
stdout:
a7e7f135a629ad788e0fc14259f8ade1f0898a4fb8f73c18fdd3669e07ff8b35
docker: Error response from daemon: driver failed programming external connectivity on endpoint nuclio-nuclio-openvino-dextr (57cff45a36550095dd802059ec3b0a38ea20f189b941054af837962b9ccdeba7): Bind for 0.0.0.0:49154 failed: port is already allocated.
stderr:
/nuclio/pkg/cmdrunner/shellrunner.go:96
Failed to run a Docker container
/nuclio/pkg/platform/local/platform.go:653
Failed to deploy function
...//nuclio/pkg/platform/abstract/platform.go:182
Deploying /root/cvat/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco function...
21.04.23 12:21:15.740 nuctl (I) Deploying function {"name": ""}
21.04.23 12:21:15.740 nuctl (I) Building {"versionInfo": "Label: 1.5.16, Git commit: ae43a6a560c2bec42d7ccfdf6e8e11a1e3cc3774, OS: linux, Arch: amd64, Go version: go1.14.3", "name": ""}
21.04.23 12:21:16.093 nuctl (I) Cleaning up before deployment {"functionName": "openvino-mask-rcnn-inception-resnet-v2-atrous-coco"}
21.04.23 12:21:16.158 nuctl (I) Staging files and preparing base images
21.04.23 12:21:16.159 nuctl (I) Building processor image {"imageName": "cvat/openvino.omz.public.mask_rcnn_inception_resnet_v2_atrous_coco:latest"}
21.04.23 12:21:16.159 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.5.16-amd64"}
21.04.23 12:21:24.066 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
21.04.23 12:21:35.221 nuctl.platform (I) Building docker image {"image": "cvat/openvino.omz.public.mask_rcnn_inception_resnet_v2_atrous_coco:latest"}
21.04.23 12:21:45.009 nuctl.platform.docker (W) Docker command outputted to stderr - this may result in errors {"workingDir": "/tmp/nuclio-build-518354243/staging", "cmd": "docker build --network host --force-rm -t cvat/openvino.omz.public.mask_rcnn_inception_resnet_v2_atrous_coco:latest -f /tmp/nuclio-build-518354243/staging/Dockerfile.processor --build-arg NUCLIO_LABEL=1.5.16 --build-arg NUCLIO_ARCH=amd64 --build-arg NUCLIO_BUILD_LOCAL_HANDLER_DIR=handler .", "stderr": "The command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n"}
21.04.23 12:21:45.016 nuctl (W) Failed to create a function; setting the function status {"err": "Failed to build processor image", "errVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build processor image\n /nuclio/pkg/processor/build/builder.go:250\nFailed to build processor image", "errCauses": [{"error": "Failed to build docker image", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build docker image", "errorCauses": [{"error": "Failed to build", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build", "errorCauses": [{"error": "stdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/18 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/18 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/18 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/18 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/18 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 608d937df434\nStep 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in 763a740471f6\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nmask_rcnn_inception_resnet_v2_atrous_coco\nRemoving intermediate container 763a740471f6\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n", "errorCauses": [{"error": "exit status 1"}]}]}]}]}
Error - exit status 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Call stack:
stdout:
Sending build context to Docker daemon 44.69MB
Step 1/18 : FROM openvino/ubuntu18_dev:2020.2
---> bf7a4dff2d97
Step 2/18 : ARG NUCLIO_LABEL
---> Using cache
---> c9a10c5b4f05
Step 3/18 : ARG NUCLIO_ARCH
---> Using cache
---> 8ed29e90bf42
Step 4/18 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR
---> Using cache
---> fc2cdf7bdff6
Step 5/18 : USER root
---> Using cache
---> 44197e8724ab
Step 6/18 : WORKDIR /opt/nuclio
---> Using cache
---> 4b2adc3eb6f5
Step 7/18 : RUN ln -s /usr/bin/pip3 /usr/bin/pip
---> Using cache
---> 11dc453d1c27
Step 8/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name mask_rcnn_inception_resnet_v2_atrous_coco -o /opt/nuclio/open_model_zoo
---> Using cache
---> 608d937df434
Step 9/18 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo
---> Running in 763a740471f6
+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo
========= Converting mask_rcnn_inception_resnet_v2_atrous_coco to IR (FP32)
Conversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32 --model_name=mask_rcnn_inception_resnet_v2_atrous_coco --reverse_input_channels '--input_shape=[1,800,1365,3]' --input=image_tensor --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28/frozen_inference_graph.pb
FAILED:
mask_rcnn_inception_resnet_v2_atrous_coco
Removing intermediate container 763a740471f6
stderr:
The command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name mask_rcnn_inception_resnet_v2_atrous_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Failed to build
/nuclio/pkg/dockerclient/shell.go:118
Failed to build docker image
.../pkg/containerimagebuilderpusher/docker.go:53
Failed to build processor image
/nuclio/pkg/processor/build/builder.go:250
Failed to deploy function
...//nuclio/pkg/platform/abstract/platform.go:182
Deploying /root/cvat/serverless/openvino/omz/public/faster_rcnn_inception_v2_coco function...
21.04.23 12:21:45.862 nuctl (I) Deploying function {"name": ""}
21.04.23 12:21:45.862 nuctl (I) Building {"versionInfo": "Label: 1.5.16, Git commit: ae43a6a560c2bec42d7ccfdf6e8e11a1e3cc3774, OS: linux, Arch: amd64, Go version: go1.14.3", "name": ""}
21.04.23 12:21:46.262 nuctl (I) Cleaning up before deployment {"functionName": "openvino-omz-public-faster_rcnn_inception_v2_coco"}
21.04.23 12:21:46.309 nuctl (I) Staging files and preparing base images
21.04.23 12:21:46.310 nuctl (I) Building processor image {"imageName": "cvat/openvino.omz.public.faster_rcnn_inception_v2_coco:latest"}
21.04.23 12:21:46.310 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.5.16-amd64"}
21.04.23 12:21:54.597 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
21.04.23 12:22:05.063 nuctl.platform (I) Building docker image {"image": "cvat/openvino.omz.public.faster_rcnn_inception_v2_coco:latest"}
21.04.23 12:22:11.545 nuctl.platform.docker (W) Docker command outputted to stderr - this may result in errors {"workingDir": "/tmp/nuclio-build-008327586/staging", "cmd": "docker build --network host --force-rm -t cvat/openvino.omz.public.faster_rcnn_inception_v2_coco:latest -f /tmp/nuclio-build-008327586/staging/Dockerfile.processor --build-arg NUCLIO_LABEL=1.5.16 --build-arg NUCLIO_ARCH=amd64 --build-arg NUCLIO_BUILD_LOCAL_HANDLER_DIR=handler .", "stderr": "The command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n"}
21.04.23 12:22:11.552 nuctl (W) Failed to create a function; setting the function status {"err": "Failed to build processor image", "errVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build processor image\n /nuclio/pkg/processor/build/builder.go:250\nFailed to build processor image", "errCauses": [{"error": "Failed to build docker image", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build docker image", "errorCauses": [{"error": "Failed to build", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build", "errorCauses": [{"error": "stdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> 21d848ab1b94\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in df783794e387\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting faster_rcnn_inception_v2_coco to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb\n\nFAILED:\nfaster_rcnn_inception_v2_coco\nRemoving intermediate container df783794e387\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n", "errorCauses": [{"error": "exit status 1"}]}]}]}]}
Error - exit status 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Call stack:
stdout:
Sending build context to Docker daemon 44.69MB
Step 1/16 : FROM openvino/ubuntu18_dev:2020.2
---> bf7a4dff2d97
Step 2/16 : ARG NUCLIO_LABEL
---> Using cache
---> c9a10c5b4f05
Step 3/16 : ARG NUCLIO_ARCH
---> Using cache
---> 8ed29e90bf42
Step 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR
---> Using cache
---> fc2cdf7bdff6
Step 5/16 : USER root
---> Using cache
---> 44197e8724ab
Step 6/16 : WORKDIR /opt/nuclio
---> Using cache
---> 4b2adc3eb6f5
Step 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip
---> Using cache
---> 11dc453d1c27
Step 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name faster_rcnn_inception_v2_coco -o /opt/nuclio/open_model_zoo
---> Using cache
---> 21d848ab1b94
Step 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo
---> Running in df783794e387
+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo
========= Converting faster_rcnn_inception_v2_coco to IR (FP32)
Conversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32 --model_name=faster_rcnn_inception_v2_coco --reverse_input_channels '--input_shape=[1,600,1024,3]' --input=image_tensor --output=detection_scores,detection_boxes,num_detections --transformations_config=/opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --input_model=/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb
FAILED:
faster_rcnn_inception_v2_coco
Removing intermediate container df783794e387
stderr:
The command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name faster_rcnn_inception_v2_coco --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1
/nuclio/pkg/cmdrunner/shellrunner.go:96
Failed to build
/nuclio/pkg/dockerclient/shell.go:118
Failed to build docker image
.../pkg/containerimagebuilderpusher/docker.go:53
Failed to build processor image
/nuclio/pkg/processor/build/builder.go:250
Failed to deploy function
...//nuclio/pkg/platform/abstract/platform.go:182
Deploying /root/cvat/serverless/openvino/omz/public/yolo-v3-tf function...
21.04.23 12:22:12.416 nuctl (I) Deploying function {"name": ""}
21.04.23 12:22:12.417 nuctl (I) Building {"versionInfo": "Label: 1.5.16, Git commit: ae43a6a560c2bec42d7ccfdf6e8e11a1e3cc3774, OS: linux, Arch: amd64, Go version: go1.14.3", "name": ""}
21.04.23 12:22:12.771 nuctl (I) Cleaning up before deployment {"functionName": "openvino-omz-public-yolo-v3-tf"}
21.04.23 12:22:12.821 nuctl (I) Staging files and preparing base images
21.04.23 12:22:12.822 nuctl (I) Building processor image {"imageName": "cvat/openvino.omz.public.yolo-v3-tf:latest"}
21.04.23 12:22:12.822 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/handler-builder-python-onbuild:1.5.16-amd64"}
21.04.23 12:22:20.813 nuctl.platform.docker (I) Pulling image {"imageName": "quay.io/nuclio/uhttpc:0.0.1-amd64"}
21.04.23 12:22:31.319 nuctl.platform (I) Building docker image {"image": "cvat/openvino.omz.public.yolo-v3-tf:latest"}
21.04.23 12:22:37.577 nuctl.platform.docker (W) Docker command outputted to stderr - this may result in errors {"workingDir": "/tmp/nuclio-build-422481459/staging", "cmd": "docker build --network host --force-rm -t cvat/openvino.omz.public.yolo-v3-tf:latest -f /tmp/nuclio-build-422481459/staging/Dockerfile.processor --build-arg NUCLIO_LABEL=1.5.16 --build-arg NUCLIO_ARCH=amd64 --build-arg NUCLIO_BUILD_LOCAL_HANDLER_DIR=handler .", "stderr": "The command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n"}
21.04.23 12:22:37.583 nuctl (W) Failed to create a function; setting the function status {"err": "Failed to build processor image", "errVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> f6ec46de8b52\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in c3ff545e7063\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting yolo-v3-tf to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32 --model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1 '--scale_values=input_1[255]' --reverse_input_channels --transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json --input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb\n\nFAILED:\nyolo-v3-tf\nRemoving intermediate container c3ff545e7063\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build processor image\n /nuclio/pkg/processor/build/builder.go:250\nFailed to build processor image", "errCauses": [{"error": "Failed to build docker image", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> f6ec46de8b52\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in c3ff545e7063\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting yolo-v3-tf to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32 --model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1 '--scale_values=input_1[255]' --reverse_input_channels --transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json --input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb\n\nFAILED:\nyolo-v3-tf\nRemoving intermediate container c3ff545e7063\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build docker image\n .../pkg/containerimagebuilderpusher/docker.go:53\nFailed to build docker image", "errorCauses": [{"error": "Failed to build", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> f6ec46de8b52\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in c3ff545e7063\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting yolo-v3-tf to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32 --model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1 '--scale_values=input_1[255]' --reverse_input_channels --transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json --input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb\n\nFAILED:\nyolo-v3-tf\nRemoving intermediate container c3ff545e7063\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n\n /nuclio/pkg/cmdrunner/shellrunner.go:96\nFailed to build\n /nuclio/pkg/dockerclient/shell.go:118\nFailed to build", "errorCauses": [{"error": "stdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> f6ec46de8b52\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in c3ff545e7063\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting yolo-v3-tf to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32 --model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1 '--scale_values=input_1[255]' --reverse_input_channels --transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json --input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb\n\nFAILED:\nyolo-v3-tf\nRemoving intermediate container c3ff545e7063\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo' returned a non-zero code: 1\n", "errorVerbose": "\nError - exit status 1\n /nuclio/pkg/cmdrunner/shellrunner.go:96\n\nCall stack:\nstdout:\nSending build context to Docker daemon 44.69MB\r\r\nStep 1/16 : FROM openvino/ubuntu18_dev:2020.2\n ---> bf7a4dff2d97\nStep 2/16 : ARG NUCLIO_LABEL\n ---> Using cache\n ---> c9a10c5b4f05\nStep 3/16 : ARG NUCLIO_ARCH\n ---> Using cache\n ---> 8ed29e90bf42\nStep 4/16 : ARG NUCLIO_BUILD_LOCAL_HANDLER_DIR\n ---> Using cache\n ---> fc2cdf7bdff6\nStep 5/16 : USER root\n ---> Using cache\n ---> 44197e8724ab\nStep 6/16 : WORKDIR /opt/nuclio\n ---> Using cache\n ---> 4b2adc3eb6f5\nStep 7/16 : RUN ln -s /usr/bin/pip3 /usr/bin/pip\n ---> Using cache\n ---> 11dc453d1c27\nStep 8/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name yolo-v3-tf -o /opt/nuclio/open_model_zoo\n ---> Using cache\n ---> f6ec46de8b52\nStep 9/16 : RUN /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n ---> Running in c3ff545e7063\n\u001b[91m+ /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions FP32 -d /opt/nuclio/open_model_zoo -o /opt/nuclio/open_model_zoo\n\u001b[0m========= Converting yolo-v3-tf to IR (FP32)\nConversion command: /usr/bin/python3 -- /opt/intel/openvino/deployment_tools/model_optimizer/mo.py --framework=tf --data_type=FP32 --output_dir=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32 --model_name=yolo-v3-tf '--input_shape=[1,416,416,3]' --input=input_1 '--scale_values=input_1[255]' --reverse_input_channels --transformations_config=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.json --input_model=/opt/nuclio/open_model_zoo/public/yolo-v3-tf/yolo-v3.pb\n\nFAILED:\nyolo-v3-tf\nRemoving intermediate container c3ff545e7063\n\nstderr:\nThe command '/bin/bash -xo pipefail -c /opt/intel/openvino/deployment_tools/open_model_zoo/tools/downloader/converter.py --name yolo-v3-tf --precisions
|
I have a proxmox-KVM system with a newer cpu and have no issues. |
I had the same issue. Maybe something went wrong when deploying a new function. To solve it, remove the directory that was created at |
Hi there,
I am new to cvat and am trying to follow instructions at https://github.com/opencv/cvat/blob/develop/cvat/apps/documentation/installation.md#semi-automatic-and-automatic-annotation to setup automatic annotation with nuclio.
The project in nuclio was created without any problem but I got errors creating the functions.
Here is what I see:
I assume we are missing files under the
/tmp/nuclio-build-xxx
folder but I don't see anything like that in the/tmp
folder and I made sure I do have the permission to create a new folder within/tmp
.Has anyone seen this problem before? Any advice is greatly appreciated.
Thanks a lot
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