Ax
08/01/2024, 10:50 AM- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:tenure_predictor_flow
parameters: {"kwargs": {"bucket_name": "dna-mlops-sagemaker-staging"}}
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules: []
pull: *pull_staging
Marvin
08/01/2024, 10:51 AMSignatureMismatchError
, suggests that there's a mismatch between the parameters expected by your flow function and the parameters provided in your deployment YAML.
Here’s a summary of the findings and a suggestion to resolve this:
### Key Points:
1. Mismatch Issue: The error indicates that your flow function expects specific parameters (bucket_name
, ltp_scorer_backfill
), but only kwargs
was provided in the deployment configuration.
2. Prefect Documentation: Parameters should be explicitly passed to flows rather than encapsulated inside kwargs
for deployment configurations.
3. GitHub Issues: Similar issues have been reported here and here.
### Resolution Steps:
To resolve this, you should directly specify the parameters in your deployment YAML config. Here's a corrected version:
yaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:tenure_predictor_flow
parameters: {"bucket_name": "dna-mlops-sagemaker-staging", "ltp_scorer_backfill": "value_for_backfill"}
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules: []
pull: *pull_staging
### Points of Interest:
- Parameters Section: Replace "kwargs": { "bucket_name": "dna-mlops-sagemaker-staging"}
with each parameter explicitly listed.
- Flow Definition: Ensure your flow function signature matches the parameters provided in the deployment YAML.
### References:
- GitHub Issue discussing kwargs
pitfalls: GitHub Issue #6039
- More on flow parameter validation: GitHub Issue#14663
By specifying parameters directly in the deployment YAML, you align the configuration with the flow’s signature, resolving the SignatureMismatchError
.Ax
08/01/2024, 10:58 AMMarvin
08/01/2024, 10:58 AMyaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:tenure_predictor_flow
parameters: {"bucket_name": "dna-mlops-sagemaker-staging", "ltp_scorer_backfill": "value_for_backfill"}
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules:
- cron: "0 12 * * *"
timezone: "America/New_York"
active: true
pull: *pull_staging
### Explanation
- Cron Schedule: This cron schedule will trigger the deployment at noon every day ("0 12 * * *"
).
- Timezone: The timezone is set to "America/New_York"
. Adjust the timezone as needed.
- Active: Setting active: true
ensures the schedule is active.
### References
- You can find more details on scheduling in Prefect's documentation here.
Is there anything else you need help with?Ax
08/01/2024, 12:23 PMMarvin
08/01/2024, 12:23 PMSignatureMismatchError
indicates that your flow function expects args
and kwargs
, but specific parameters were provided in your deployment configuration. This happens when your flow is built to accept **kwargs
, and you need to pass the parameters accordingly.
### Resolution Steps
1. Flow Function: Ensure that the flow function is designed to accept **kwargs
.
2. Deployment Configuration: You must pass a JSON object under the kwargs
key in your deployment YAML.
### Adjusted Flow and Deployment Configuration
Flow Function Example:
python
from prefect import flow, get_run_logger
@flow
def tenure_predictor_flow(**kwargs):
logger = get_run_logger()
bucket_name = kwargs.get("bucket_name")
ltp_scorer_backfill = kwargs.get("ltp_scorer_backfill")
<http://logger.info|logger.info>(f"Bucket Name: {bucket_name}")
<http://logger.info|logger.info>(f"LTP Scorer Backfill: {ltp_scorer_backfill}")
Updated Deployment Configuration:
yaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:tenure_predictor_flow
parameters: {"kwargs": {"bucket_name": "dna-mlops-sagemaker-staging", "ltp_scorer_backfill": "value_for_backfill"}}
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules:
- cron: "0 12 * * *"
timezone: "America/New_York"
active: true
pull: *pull_staging
### Points of Interest:
- Flow Function: tenure_predictor_flow
function is set to accept **kwargs
, retrieving specific parameters using kwargs.get()
.
- Deployment YAML: Parameters are provided inside kwargs
to match the method signature.
### References:
- GitHub Issue with Workaround: GitHub Issue #6039
- Prefect Documentation on Parameters: Prefect Docs
This should resolve the SignatureMismatchError
and enable your flow to work correctly with the specified parameters.Ax
08/01/2024, 12:27 PMMarvin
08/01/2024, 12:28 PM**kwargs
. Therefore, you should adjust your deployment YAML to match the parameter names exactly as defined in your flow.
Here’s the correctly updated deployment YAML:
yaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:my_flow
parameters:
bucket_name: "dna-mlops-sagemaker-staging"
ltp_scorer_backfill: false
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules:
- cron: "0 12 * * *"
timezone: "America/New_York"
active: true
pull: *pull_staging
### Explanation:
- Parameters: Directly list the flow parameters (bucket_name
, ltp_scorer_backfill
) in the parameters
section of the deployment YAML.
- Cron Schedule: A cron schedule is provided to run the flow daily at noon New York time.
### Conclusion:
By aligning the deployment YAML parameters with your flow function signature, the SignatureMismatchError
should be resolved.
If you need more assistance, feel free to ask!Ax
08/01/2024, 12:28 PMMarvin
08/01/2024, 12:28 PMSignatureMismatchError
indicates that there might still be a mismatch between the parameters expected by the flow and those provided in the deployment. It's also possible that the flow's signature is being misinterpreted.
### Checklist:
1. Check Flow Signature: Ensure the flow definition matches precisely.
2. Verify Deployment YAML: Ensure the parameters in the YAML match the function signature exactly.
3. Inspect Flow Loading: Ensure the entrypoint is correctly leading to the proper flow function.
### Flow Function:
Here's your flow function for reference:
python
from prefect import flow
@flow(name="my flow")
def my_flow(bucket_name="dna-mlops-sagemaker-development", ltp_scorer_backfill=False):
# Your flow logic here
pass
### Corrected Deployment YAML:
yaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:my_flow
parameters:
bucket_name: "dna-mlops-sagemaker-staging"
ltp_scorer_backfill: false
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules:
- cron: "0 12 * * *"
timezone: "America/New_York"
active: true
pull: *pull_staging
### Debugging Steps:
1. Flow Definition:
python
from prefect import flow, get_run_logger
@flow(name="my flow")
def my_flow(bucket_name="dna-mlops-sagemaker-development", ltp_scorer_backfill=False):
logger = get_run_logger()
<http://logger.info|logger.info>(f"Bucket Name: {bucket_name}")
<http://logger.info|logger.info>(f"LTP Scorer Backfill: {ltp_scorer_backfill}")
# Additional flow logic
2. Full YAML Inspection:
Ensure the YAML isn't splitting parameters improperly.
yaml
- name: staging
version:
tags: []
description:
entrypoint: dna/orchestration/prefect/flows/tenure_predictor.py:my_flow
parameters:
bucket_name: "dna-mlops-sagemaker-staging"
ltp_scorer_backfill: false
work_pool:
name: dna-ecs-workpool
work_queue_name:
job_variables:
env:
INFISICAL_ENVIRONMENT: staging
schedules:
- cron: "0 12 * * *"
timezone: "America/New_York"
active: true
pull: *pull_staging
### Common Pitfalls:
- Parameter Names: Ensure no typos in parameter names in both flow function and deployment YAML.
- YAML Syntax: Ensure correct indentation and structure.
### Reference Links:
- Prefect Docs on Parameters: Prefect Docs
- Related GitHub Issues: GitHub Issue #14663
This should help resolve the mismatch if everything is correctly aligned. Please check and let me know if you encounter further issues.