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new 06e103d87e8 Add ApplyBucketsWithInterpolation TFTransform (#31291)
06e103d87e8 is described below
commit 06e103d87e8ac883f606475dbadbefed4ba77c9a
Author: Jack McCluskey <[email protected]>
AuthorDate: Wed May 29 14:23:57 2024 -0400
Add ApplyBucketsWithInterpolation TFTransform (#31291)
* Add ApplyBucketsWithInterpolation TFTransform
* Update sdks/python/apache_beam/ml/transforms/tft.py
Co-authored-by: tvalentyn <[email protected]>
* add tft documentation link
* change docstring wording around bucket_boundaries
* Update sdks/python/apache_beam/ml/transforms/tft.py
Co-authored-by: tvalentyn <[email protected]>
---------
Co-authored-by: tvalentyn <[email protected]>
---
sdks/python/apache_beam/ml/transforms/tft.py | 49 ++++++++++++++++++++---
sdks/python/apache_beam/ml/transforms/tft_test.py | 30 ++++++++++++++
2 files changed, 74 insertions(+), 5 deletions(-)
diff --git a/sdks/python/apache_beam/ml/transforms/tft.py
b/sdks/python/apache_beam/ml/transforms/tft.py
index 370043bc0d9..e2f02971e7c 100644
--- a/sdks/python/apache_beam/ml/transforms/tft.py
+++ b/sdks/python/apache_beam/ml/transforms/tft.py
@@ -337,16 +337,16 @@ class ApplyBuckets(TFTOperation):
name: Optional[str] = None):
"""
This functions is used to map the element to a positive index i for
- which bucket_boundaries[i-1] <= element < bucket_boundaries[i],
- if it exists. If input < bucket_boundaries[0], then element is
- mapped to 0. If element >= bucket_boundaries[-1], then element is
+ which `bucket_boundaries[i-1] <= element < bucket_boundaries[i]`,
+ if it exists. If `input < bucket_boundaries[0]`, then element is
+ mapped to 0. If `element >= bucket_boundaries[-1]`, then element is
mapped to len(bucket_boundaries). NaNs are mapped to
len(bucket_boundaries).
Args:
columns: A list of column names to apply the transformation on.
- bucket_boundaries: A rank 2 Tensor or list representing the bucket
- boundaries sorted in ascending order.
+ bucket_boundaries: An iterable of ints or floats representing the bucket
+ boundaries. Must be sorted in ascending order.
name: (Optional) A string that specifies the name of the operation.
"""
super().__init__(columns)
@@ -363,6 +363,45 @@ class ApplyBuckets(TFTOperation):
return output
+@register_input_dtype(float)
+class ApplyBucketsWithInterpolation(TFTOperation):
+ def __init__(
+ self,
+ columns: List[str],
+ bucket_boundaries: Iterable[Union[int, float]],
+ name: Optional[str] = None):
+ """Interpolates values within the provided buckets and then normalizes to
+ [0, 1].
+
+ Input values are bucketized based on the provided boundaries such that the
+ input is mapped to a positive index i for which `bucket_boundaries[i-1] <=
+ element < bucket_boundaries[i]`, if it exists. The values are then
+ normalized to the range [0,1] within the bucket, with NaN values being
+ mapped to 0.5.
+
+ For more information, see:
+
https://www.tensorflow.org/tfx/transform/api_docs/python/tft/apply_buckets_with_interpolation
+
+ Args:
+ columns: A list of column names to apply the transformation on.
+ bucket_boundaries: An iterable of ints or floats representing the bucket
+ boundaries sorted in ascending order.
+ name: (Optional) A string that specifies the name of the operation.
+ """
+ super().__init__(columns)
+ self.bucket_boundaries = [bucket_boundaries]
+ self.name = name
+
+ def apply_transform(
+ self, data: common_types.TensorType,
+ output_column_name: str) -> Dict[str, common_types.TensorType]:
+ output = {
+ output_column_name: tft.apply_buckets_with_interpolation(
+ x=data, bucket_boundaries=self.bucket_boundaries, name=self.name)
+ }
+ return output
+
+
@register_input_dtype(float)
class Bucketize(TFTOperation):
def __init__(
diff --git a/sdks/python/apache_beam/ml/transforms/tft_test.py
b/sdks/python/apache_beam/ml/transforms/tft_test.py
index 5c42ecc012f..f5615e9d4ad 100644
--- a/sdks/python/apache_beam/ml/transforms/tft_test.py
+++ b/sdks/python/apache_beam/ml/transforms/tft_test.py
@@ -364,6 +364,36 @@ class ApplyBucketsTest(unittest.TestCase):
actual_output, equal_to(expected_output, equals_fn=np.array_equal))
+class ApplyBucketsWithInterpolationTest(unittest.TestCase):
+ def setUp(self) -> None:
+ self.artifact_location = tempfile.mkdtemp()
+
+ def tearDown(self):
+ shutil.rmtree(self.artifact_location)
+
+ @parameterized.expand([
+ ([-1, 9, 10, 11], [10], [0., 0., 1., 1.]),
+ ([15, 20, 25], [10, 20], [.5, 1, 1]),
+ ])
+ def test_apply_buckets(self, test_inputs, bucket_boundaries,
expected_values):
+ with beam.Pipeline() as p:
+ data = [{'x': [i]} for i in test_inputs]
+ result = (
+ p
+ | "Create" >> beam.Create(data)
+ | "MLTransform" >> base.MLTransform(
+ write_artifact_location=self.artifact_location).with_transform(
+ tft.ApplyBucketsWithInterpolation(
+ columns=['x'], bucket_boundaries=bucket_boundaries)))
+ expected_output = []
+ for x in expected_values:
+ expected_output.append(np.array(x))
+
+ actual_output = (result | beam.Map(lambda x: x.x))
+ assert_that(
+ actual_output, equal_to(expected_output, equals_fn=np.allclose))
+
+
class ComputeAndApplyVocabTest(unittest.TestCase):
def setUp(self) -> None:
self.artifact_location = tempfile.mkdtemp()
