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HyperCLOVAX-SEED-Vision-Instruct-3B

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HyperCLOVA X 940

import timeit

class DummyConfig:
    def __init__(self, max_num_grids=10, use_1x1_grid=False, anyres=True):
        self.max_num_grids = max_num_grids
        self.use_1x1_grid = use_1x1_grid
        self.anyres = anyres

config = DummyConfig()

def original_version():
    possible_resolutions = []
    if config.anyres:
        assert config.max_num_grids > 0
        for i in range(1, config.max_num_grids + 1):
            for j in range(1, config.max_num_grids + 1):
                if i == 1 and j == 1 and not config.use_1x1_grid:
                    continue
                if i * j <= config.max_num_grids:
                    possible_resolutions.append([i, j])
    return possible_resolutions

def list_comprehension_version():
    possible_resolutions = []
    if config.anyres:
        assert config.max_num_grids > 0
        possible_resolutions = [
            [i, j]
            for i in range(1, config.max_num_grids + 1)
            for j in range(1, (config.max_num_grids // i) + 1)
            if not (i == 1 and j == 1 and not config.use_1x1_grid)
        ]
    return possible_resolutions

# 측정
print("original_version:", timeit.timeit(original_version, number=10000))
print("list_comprehension_version:", timeit.timeit(list_comprehension_version, number=10000))

# original_version: 0.19971796300001188                              0.10782223799999713
# list_comprehension_version: 0.15134139399999924    0.0473939370000096

timeit을 사용해 두 코드의 성능 비교를 했을때 list_comprehension쪽이 더 빠르며 이론적으로도 더 빠른것으로 알고 있습니다. grid 설정으로 적절한 해상도 목록을 반환하는데 시간을 줄일 수 있습니다.