[AUTOTVM] Fix a bug in generating the search space #4779
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python/tvm/autotvm/task/space.py
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| @@ -226,7 +226,13 @@ def __init__(self, axes, policy, **kwargs): | |||
| def _generate_space(self, now, tmp_stack, enforce_no_tail=False): | |||
| """Generate space by DFS""" | |||
| if now == self.num_output - 1: | |||
| prod = np.prod(tmp_stack, dtype=np.int64) | |||
| prod = 1 | |||
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It seems to me that manually implementing a classic array production is not necessary in any case. Since limited types are only enforced in numpy and Python's types are unlimited, it would be more concise to use Python builtins to calculate the product:
import functools
import operator
prod = functools.reduce(operator.mul, tmp_stack, 1)Note that the length of tmp_stack is always small (currently 4 at most, and I don't think it would be longer than 10), so this won't hurt the performance.
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It looks more pythonic. The number of lines will be similar. Here is one debate on this: :)
https://stackoverflow.com/questions/9474412/python-alternative-to-reduce
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Well, I know that some people prevent reduce and other patterns like map from being used in Python 3, although I personally think not like map and filter, reduce is hard to be replaced by other pythonic representations. I am fine with that if you do not want to introduce reduce to the code. In this case I would suggest making this logic a standalone function in autotvm/util.py.
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Utility function looks like a overkill. A reduce call is fine. Updated. Thanks!
- Do not use numpy.prod which ignores integer (64 bits) overflows. This leads to an incorrect number of points in the search space.
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Please help review this patch. |
- Do not use numpy.prod which ignores integer (64 bits) overflows. This leads to an incorrect number of points in the search space.
- Do not use numpy.prod which ignores integer (64 bits) overflows. This leads to an incorrect number of points in the search space.
- Do not use numpy.prod which ignores integer (64 bits) overflows. This leads to an incorrect number of points in the search space.
This leads to an incorrect number of points in the search space.
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