Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
File size: 1,231 Bytes
b13b124
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
def make_divisible(value, divisor, min_value=None, min_ratio=0.9):
    """Make divisible function.

    This function rounds the channel number to the nearest value that can be
    divisible by the divisor. It is taken from the original tf repo. It ensures
    that all layers have a channel number that is divisible by divisor. It can
    be seen here: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/mobilenet.py  # noqa

    Args:
        value (int): The original channel number.
        divisor (int): The divisor to fully divide the channel number.
        min_value (int): The minimum value of the output channel.
            Default: None, means that the minimum value equal to the divisor.
        min_ratio (float): The minimum ratio of the rounded channel number to
            the original channel number. Default: 0.9.

    Returns:
        int: The modified output channel number.
    """

    if min_value is None:
        min_value = divisor
    new_value = max(min_value, int(value + divisor / 2) // divisor * divisor)
    # Make sure that round down does not go down by more than (1-min_ratio).
    if new_value < min_ratio * value:
        new_value += divisor
    return new_value