asfgit closed pull request #23484: [SPARK-26559][ML][PySpark] ML image can't
work with numpy versions prior to 1.9
URL: https://github.com/apache/spark/pull/23484
This is a PR merged from a forked repository.
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diff --git a/python/pyspark/ml/image.py b/python/pyspark/ml/image.py
index edb90a3578546..a1aacea88e42e 100644
--- a/python/pyspark/ml/image.py
+++ b/python/pyspark/ml/image.py
@@ -28,6 +28,7 @@
import warnings
import numpy as np
+from distutils.version import LooseVersion
from pyspark import SparkContext
from pyspark.sql.types import Row, _create_row, _parse_datatype_json_string
@@ -190,7 +191,11 @@ def toImage(self, array, origin=""):
# Running `bytearray(numpy.array([1]))` fails in specific Python
versions
# with a specific Numpy version, for example in Python 3.6.0 and NumPy
1.13.3.
# Here, it avoids it by converting it to bytes.
- data = bytearray(array.astype(dtype=np.uint8).ravel().tobytes())
+ if LooseVersion(np.__version__) >= LooseVersion('1.9'):
+ data = bytearray(array.astype(dtype=np.uint8).ravel().tobytes())
+ else:
+ # Numpy prior to 1.9 don't have `tobytes` method.
+ data = bytearray(array.astype(dtype=np.uint8).ravel())
# Creating new Row with _create_row(), because Row(name = value, ... )
# orders fields by name, which conflicts with expected schema order
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