Github user MechCoder commented on a diff in the pull request: https://github.com/apache/spark/pull/7854#discussion_r37826703 --- Diff: python/pyspark/mllib/linalg/__init__.py --- @@ -461,32 +461,41 @@ def __init__(self, size, *args): self.size = int(size) """ Size of the vector. """ assert 1 <= len(args) <= 2, "must pass either 2 or 3 arguments" - if len(args) == 1: - pairs = args[0] - if type(pairs) == dict: - pairs = pairs.items() - pairs = sorted(pairs) - self.indices = np.array([p[0] for p in pairs], dtype=np.int32) - """ A list of indices corresponding to active entries. """ - self.values = np.array([p[1] for p in pairs], dtype=np.float64) - """ A list of values corresponding to active entries. """ + if isinstance(args[0], bytes): + assert isinstance(args[1], bytes), "values should be string too" + if args[0]: + self.indices = np.frombuffer(args[0], np.int32) + self.values = np.frombuffer(args[1], np.float64) + else: + # np.frombuffer() doesn't work well with empty string in older version + self.indices = np.array([], dtype=np.int32) + self.values = np.array([], dtype=np.float64) else: - if isinstance(args[0], bytes): - assert isinstance(args[1], bytes), "values should be string too" - if args[0]: - self.indices = np.frombuffer(args[0], np.int32) - self.values = np.frombuffer(args[1], np.float64) - else: - # np.frombuffer() doesn't work well with empty string in older version - self.indices = np.array([], dtype=np.int32) - self.values = np.array([], dtype=np.float64) + if len(args) == 1: + args = args[0] + if isinstance(args, dict): --- End diff -- The idea is to change a dict into a tuple and then unpack it below on L485
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