fix(KDP): fixing imports

kdp/features.py

@@ -2,9 +2,10 @@
 from typing import Any
 
 import tensorflow as tf
-from layers_factory import PreprocessorLayerFactory
 from loguru import logger
 
+from kdp.layers_factory import PreprocessorLayerFactory
+
 
 class TextVectorizerOutputOptions(Enum):
     TF_IDF = auto()

kdp/layers_factory.py

@@ -1,7 +1,8 @@
 import inspect
 
 import tensorflow as tf
-from custom_layers import TextPreprocessingLayer
+
+from kdp.custom_layers import TextPreprocessingLayer
 
 
 class PreprocessorLayerFactory:

kdp/processor.py

@@ -4,9 +4,9 @@
 from typing import Any
 
 import tensorflow as tf
-from features import CategoricalFeature, CategoryEncodingOptions, FeatureType, NumericalFeature, TextFeature
 from loguru import logger
 
+from kdp.features import CategoricalFeature, CategoryEncodingOptions, FeatureType, NumericalFeature, TextFeature
 from kdp.layers_factory import PreprocessorLayerFactory
 from kdp.pipeline import FeaturePreprocessor
 from kdp.stats import DatasetStatistics

kdp/stats.py

@@ -4,9 +4,10 @@
 
 import numpy as np
 import tensorflow as tf
-from features import CategoricalFeature, FeatureType, NumericalFeature
 from loguru import logger
 
+from kdp.features import CategoricalFeature, FeatureType, NumericalFeature
+
 
 class WelfordAccumulator:
     """Accumulator for computing the mean and variance of a sequence of numbers

test/test_pipeline.py

@@ -84,3 +84,7 @@ def test_chain_processing_steps(self):
         output_layer = preprocessor.chain(input_layer)
         print("type layer", type(output_layer))
         self.assertTrue(tf.keras.utils.is_keras_tensor(output_layer))
+
+
+if __name__ == "__main__":
+    unittest.main()