Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/15074#discussion_r82455939
--- Diff: python/pyspark/mllib/linalg/__init__.py ---
@@ -1296,9 +1296,19 @@ def asML(self):
return newlinalg.SparseMatrix(self.numRows, self.numCols,
self.colPtrs, self.rowIndices,
self.values, self.isTransposed)
- # TODO: More efficient implementation:
def __eq__(self, other):
- return np.all(self.toArray() == other.toArray())
+ if ((type(other) is not type(self)) or
+ self.isTransposed != other.isTransposed or
--- End diff --
So what about if one matrix is represented as transposed and the other
isn't but the both represent the same actual data?
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