diff --git a/albumentations/augmentations/functional.py b/albumentations/augmentations/functional.py
index 78b8aec72..464478a71 100644
--- a/albumentations/augmentations/functional.py
+++ b/albumentations/augmentations/functional.py
@@ -9,7 +9,6 @@
 import numpy as np
 from albucore import (
     MAX_VALUES_BY_DTYPE,
-    add,
     add_array,
     add_constant,
     add_weighted,
@@ -117,10 +116,10 @@ def shift_hsv(img: np.ndarray, hue_shift: float, sat_shift: float, val_shift: fl
         hue = sz_lut(hue, lut_hue, inplace=False)
 
     if sat_shift != 0:
-        sat = add_constant(sat, sat_shift)
+        sat = add_constant(sat, sat_shift, inplace=True)
 
     if val_shift != 0:
-        val = add_constant(val, val_shift)
+        val = add_constant(val, val_shift, inplace=True)
 
     img = cv2.merge((hue, sat, val))
     img = cv2.cvtColor(img, cv2.COLOR_HSV2RGB)
@@ -1589,7 +1588,7 @@ def unsharp_mask(
 
     soft_mask = blur_fn(mask)
 
-    return add(multiply(sharp, soft_mask), multiply(image, 1 - soft_mask))
+    return add_array(multiply(sharp, soft_mask), multiply(image, 1 - soft_mask), inplace=True)
 
 
 @preserve_channel_dim
@@ -1880,7 +1879,7 @@ def generate_approx_gaussian_noise(
 
 @clipped
 def add_noise(img: np.ndarray, noise: np.ndarray) -> np.ndarray:
-    return add_array(img, noise)
+    return add_array(img, noise, inplace=False)
 
 
 def swap_tiles_on_keypoints(
diff --git a/albumentations/augmentations/geometric/functional.py b/albumentations/augmentations/geometric/functional.py
index 5298ad7d8..cd006cd1c 100644
--- a/albumentations/augmentations/geometric/functional.py
+++ b/albumentations/augmentations/geometric/functional.py
@@ -6,7 +6,7 @@
 
 import cv2
 import numpy as np
-from albucore import get_num_channels, hflip, maybe_process_in_chunks, preserve_channel_dim, vflip
+from albucore import get_num_channels, hflip, maybe_process_in_chunks, multiply_by_constant, preserve_channel_dim, vflip
 
 from albumentations.augmentations.utils import angle_2pi_range, handle_empty_array
 from albumentations.core.bbox_utils import bboxes_from_masks, denormalize_bboxes, masks_from_bboxes, normalize_bboxes
@@ -1512,7 +1512,7 @@ def generate_noise_field() -> np.ndarray:
         elif noise_distribution == "uniform":
             field = random_generator.uniform(low=-1, high=1, size=image_shape[:2]).astype(np.float32)
             cv2.GaussianBlur(field, kernel_size, sigma, dst=field)
-        return field * alpha
+        return multiply_by_constant(field, alpha, inplace=True)
 
     # Generate first displacement field
     dx = generate_noise_field()