Help using InfraValidator locally on OS X
See original GitHub issueWe are trying to use InfraValidator
, running locally on OS X (mac machine specs, etc.) with BeamDagRunner
, like so:
infra_validator = InfraValidator(
model=trainer.outputs["model"],
examples=example_gen.outputs["examples"],
serving_spec=infra_validator_pb2.ServingSpec(
tensorflow_serving=infra_validator_pb2.TensorFlowServing(tags=["latest"]),
local_docker=infra_validator_pb2.LocalDockerConfig(),
),
request_spec=infra_validator_pb2.RequestSpec(
tensorflow_serving=infra_validator_pb2.TensorFlowServingRequestSpec()
),
)
components.append(infra_validator)
The docker container seems to start, but then stops, fails, and gives the following error log:
INFO:absl:Starting infra validation (attempt 1/5).
INFO:absl:Starting LocalDockerRunner(image: tensorflow/serving:latest).
INFO:absl:Running container with parameter {'auto_remove': True, 'detach': True, 'publish_all_ports': True, 'image': 'tensorflow/serving:latest', 'environment': {'MODEL_NAME': 'infra-validation-model', 'MODEL_BASE_PATH': '/model'}, 'mounts': [{'Target': '/model/infra-validation-model/1', 'Source': '/var/folders/l4/pwtkmm_11xd9lnrq5t0yghdh0000gn/T/beam_testt6n8xs2i/tfx_pipeline_output/autotagging-de-tfx-full-run/.temp/6/infra-validation-model/1606931336', 'Type': 'bind', 'ReadOnly': True}]}
INFO:absl:Stopping LocalDockerRunner(image: tensorflow/serving:latest).
ERROR:absl:Infra validation (attempt 1/5) failed.
Traceback (most recent call last):
File "/Users/adu27/.local/share/virtualenvs/training-vsRZzzSA/lib/python3.6/site-packages/docker/api/client.py", line 268, in _raise_for_status
response.raise_for_status()
File "/Users/adu27/.local/share/virtualenvs/training-vsRZzzSA/lib/python3.6/site-packages/requests/models.py", line 943, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: http+docker://localhost/v1.40/containers/create
We assumed that maybe the LocalDockerConfig needed more set up, so we tried to set client_base_url
, but couldn’t really figure out what this was supposed to be. We’ve tried client_base_url
as unix://var/run/docker.sock
, unix:///var/run/docker.sock
(note three /s), and http://host.docker.internal:8500
.
Any guidance on what client_base_url
should be / anything else we should be doing?
Issue Analytics
- State:
- Created 3 years ago
- Comments:5 (1 by maintainers)
Top Results From Across the Web
The InfraValidator TFX Pipeline Component - TensorFlow
Technically, a model can be infra validated in a local Docker environment and then served in a completely different environment (e.g. Kubernetes ...
Read more >I can't install TensorFlow-macos a… | Apple Developer Forums
And so, I updated my OS to Monterey Beta and tried to install TensorFlow-Metal a few days ago. However, all installing instruction commands...
Read more >Sentiment Analysis with TFX Pipelines — Local Deploy
3.1 Components. In our case, we chose not to use the InfraValidator component. However, we chose to add one more node to our...
Read more >Bootstrap a Node - Chef Software
We recommended using “validatorless bootstrapping” to authenticate new nodes with the Chef Infra Server. The legacy Chef Infra validator-based ...
Read more >TensorFlow Extended (TFX): the components and ... - Adaltas
Putting Machine Learning (ML) and Deep Learning (DL) models in production ... To help organizations implement an industrial-grade end-to-end ...
Read more >Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start FreeTop Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Top GitHub Comments
@aidandunlop
If you check #2914. Here @chongkong clarify why you are getting this message. I agree with you that the message can lead to misinterpretation.
Are you satisfied with the resolution of your issue? Yes No