📘
Padding for Same Convolution
EasyDeep Learning
Problem Statement
Determine the padding P required to keep the output size equal to the input size (assuming stride S=1).
Background
To maintain spatial dimensions (O=I) with stride 1, we solve:
I=I−F+2P+1
This gives us: P=2F−1
This is called "same" padding because the output has the same spatial dimensions as the input.
Your Task
Write a function calculate_same_padding(filter_size) returning the integer padding amount. Assume the filter size is always odd.
Output Format
Return an integer representing the padding needed for "same" convolution.
Example:
Input:
filter_size=5
Output:
2
Reasoning:
2P = F - 1 → 2P = 4 → P = 2
Constraints:
- filter_size is always an odd number
- 1 <= filter_size <= 15
Editor
Python 3.13.1
Test Results
0/0Run code to see test results.