Question

我想通过屏蔽一些我知道在计算中不需要为零的值来优化Python中的矩阵乘法（权衡回归）。它们仍然会存在，因为我不想更改矩阵的大小。矩阵是浮点数。

Python（keras / tensorflow？）是否会以不同的方式处理这些乘法并显着加快该过程，或者将花费相似的时间，从而使这种掩盖变得毫无意义？

Answer 1

不，乘以零等于乘以任何其他数字

>>> def times_zero(x):
...     return x * 0
... 
>>> import dis
>>> dis.dis(times_zero)
  2           0 LOAD_FAST                0 (x)
              3 LOAD_CONST               1 (0)
              6 BINARY_MULTIPLY     
              7 RETURN_VALUE        
>>> def times_four(x):
...     return x * 4
... 
>>> dis.dis(times_four)
  2           0 LOAD_FAST                0 (x)
              3 LOAD_CONST               1 (4)
              6 BINARY_MULTIPLY     
              7 RETURN_VALUE

Answer 2

我给他们计时：

from timeit import default_timer as timer
import itertools

my_toggle = itertools.cycle(range(2))

for x in range(20):
    current_number = my_toggle.__next__()
    start = timer()
    y = 1 * current_number
    end = timer()
    print(f"{end - start:.10f} seconds for {current_number}")

但是我不确定结果如何：

0.0000002555 seconds for 0
0.0000002555 seconds for 1
0.0000002555 seconds for 0
0.0000002555 seconds for 1
0.0000002555 seconds for 0
0.0000000000 seconds for 1
0.0000000000 seconds for 0
0.0000002555 seconds for 1
0.0000000000 seconds for 0
0.0000000000 seconds for 1
0.0000000000 seconds for 0
0.0000002555 seconds for 1
0.0000002555 seconds for 0
0.0000000000 seconds for 1
0.0000002555 seconds for 0
0.0000000000 seconds for 1
0.0000000000 seconds for 0
0.0000002555 seconds for 1
0.0000000000 seconds for 0
0.0000000000 seconds for 1

乘0比Python中的任何其他乘法快吗？

2 个答案: