Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
test2 / mmseg /models /utils /make_divisible.py
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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