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a1916c966c
* feature: modularized feature engineering for ml setup (new pipeline) * chore: updating imports properly * test: updating fixtures with ua and meta * chore: migrating code ignore groups * chore: syntax cleaning and code quality * chore: fixing pipeline data compatability * Update experiments/procesing/steps/session.py Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> * chore: refactoring and dixing path joining * chore: refactoring function definition to avoid reinit --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
33 lines
965 B
Python
Executable File
33 lines
965 B
Python
Executable File
from abc import ABC, abstractmethod
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from sklearn.base import BaseEstimator, TransformerMixin
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from procesing.context import PipelineContext
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from typing import Any
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class BaseContextStep(BaseEstimator, TransformerMixin, ABC):
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"""
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Base for all pipeline steps.
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Each step is stateless, context-driven, and performs ONE transformation.
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"""
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def __init__(self, context: PipelineContext):
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self.context = context
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def fit(self, X=None, y=None):
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"""Most steps don't need training"""
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return self
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@abstractmethod
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def transform(self, X) -> Any:
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"""Transform input using context. Must be implemented by subclass."""
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pass
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def get_params(self, deep=True):
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"""sklearn compatibility"""
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return {'context': self.context}
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def set_params(self, **params):
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"""sklearn compatibility"""
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if 'context' in params:
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self.context = params['context']
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return self
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