[GitHub] [incubator-tvm] comaniac commented on a change in pull request #4779: [AUTOTVM] Fix a bug in generating the search space

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comaniac commented on a change in pull request #4779: [AUTOTVM] Fix a bug in generating the search space
URL: https://github.com/apache/incubator-tvm/pull/4779#discussion_r371397521
 
 

 ##########
 File path: python/tvm/autotvm/task/space.py
 ##########
 @@ -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
 
 Review comment:
   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:
   ```python
   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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