change double for loop to list comprehension for upgrading speed

```python
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))
```

```python
# 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.

modeling_hyperclovax.py

@@ -465,12 +465,12 @@ class HCXVisionForCausalLM(PreTrainedModel, GenerationMixin):
         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])
+            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)
+            ]
 
             possible_resolutions = [
                 [ys * vision_config.image_size, xs * vision_config.image_size] for ys, xs in possible_resolutions