the-algorithm/twml/twml/feature_config.py
twitter-team ef4c5eb65e Twitter Recommendation Algorithm
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2023-03-31 17:36:31 -05:00

55 lines
1.4 KiB
Python

"""
Feature configuration for DeepBird jobs:
- Which features to keep
- Which features to blacklist
- Which features are labels
- Which feature is the weight
"""
from twitter.deepbird.io.legacy import feature_config
class FeatureConfig(feature_config.FeatureConfig):
def get_feature_spec(self):
"""
Generates a serialization-friendly dict representing this FeatureConfig.
"""
doc = super(FeatureConfig, self).get_feature_spec()
# Override the class in the spec.
doc["class"] = "twml.FeatureConfig"
return doc
class FeatureConfigBuilder(feature_config.FeatureConfigBuilder):
def build(self):
# Overwrite self.build() to return twml.FeatureConfig instead
"""
Builds and returns FeatureConfig object.
"""
(
features,
tensor_types,
sparse_tensor_types,
feature_map,
feature_name_to_feature_parser,
feature_in_bq_name,
) = self._build()
return FeatureConfig(
features=features,
labels=self._labels,
weight=self._weight,
filters=self._filter_features,
tensor_types=tensor_types,
sparse_tensor_types=sparse_tensor_types,
feature_types=feature_map,
decode_mode=self._decode_mode,
legacy_sparse=self._legacy_sparse,
feature_name_to_feature_parser=self._feature_name_to_feature_parser,
feature_in_bq_name=self._feature_in_bq_name,
)
_name_to_id = feature_config._name_to_id