Created
August 13, 2018 16:15
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How to serve an embedding trained with Estimators
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| station_embed = tf.feature_column.embedding_column( | |
| tf.feature_column.categorical_column_with_hash_bucket('start_station_id', 5000, tf.int32), 2) | |
| feature_cols = [ | |
| tf.feature_column.categorical_column_with_identity('day_of_week', num_buckets = 8), | |
| station_embed, | |
| tf.feature_column.categorical_column_with_vocabulary_list('rainy', ['false', 'true']) | |
| ] | |
| estimator = tf.estimator.LinearRegressor( | |
| model_dir = output_dir, | |
| feature_columns = feature_cols) |
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