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Removing the deprecated log_xxx_metadata calls #28

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merged 7 commits into from
Dec 2, 2024
Merged

Removing the deprecated log_xxx_metadata calls #28

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97ac292
removing the deprecated calls
bcdurak Nov 13, 2024
223516c
correcting the ref
bcdurak Nov 13, 2024
52bf387
fixing the review comments
bcdurak Nov 13, 2024
b8d4467
fixing the steps
bcdurak Nov 28, 2024
fb8cdb7
new way to fetch artifacts
bcdurak Nov 28, 2024
1124356
fixed the errors
bcdurak Nov 28, 2024
b60e441
fixed imports
bcdurak Nov 28, 2024
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2 changes: 1 addition & 1 deletion .github/workflows/ci.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -55,5 +55,5 @@ jobs:
with:
stack-name: ${{ matrix.stack-name }}
python-version: ${{ matrix.python-version }}
ref-zenml: ${{ inputs.ref-zenml || 'develop' }}
ref-zenml: ${{ inputs.ref-zenml || 'feature/followup-run-metadata' }}
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ref-template: ${{ inputs.ref-template || github.ref }}
7 changes: 4 additions & 3 deletions template/steps/data_preprocessor.py
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Expand Up @@ -7,7 +7,7 @@
from sklearn.preprocessing import MinMaxScaler
from typing_extensions import Annotated
from utils.preprocess import ColumnsDropper, DataFrameCaster, NADropper
from zenml import log_artifact_metadata, step
from zenml import log_metadata, step


@step
Expand Down Expand Up @@ -67,8 +67,9 @@ def data_preprocessor(
dataset_tst = preprocess_pipeline.transform(dataset_tst)

# Log metadata so we can load it in the inference pipeline
log_artifact_metadata(
artifact_name="preprocess_pipeline",
log_metadata(
metadata={"random_state": random_state, "target": target},
artifact_name="preprocess_pipeline",
infer_artifact=True,
)
return dataset_trn, dataset_tst, preprocess_pipeline
5 changes: 3 additions & 2 deletions template/steps/model_evaluator.py
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Expand Up @@ -4,7 +4,7 @@

import pandas as pd
from sklearn.base import ClassifierMixin
from zenml import log_artifact_metadata, step
from zenml import log_metadata, step
from zenml.logger import get_logger

logger = get_logger(__name__)
Expand Down Expand Up @@ -79,8 +79,9 @@ def model_evaluator(
for message in messages:
logger.warning(message)

log_artifact_metadata(
log_metadata(
metadata={"train_accuracy": float(trn_acc), "test_accuracy": float(tst_acc)},
artifact_name="sklearn_classifier",
infer_artifact=True,
)
return float(tst_acc)
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