The AI Interview - Master AI/ML Interviews

Implement a function that performs Global Average Pooling on a 3D NumPy array representing feature maps from a convolutional layer. The function should take an input of shape (height, width, channels) and return a 1D array of shape (channels,), where each element is the average of all values in the corresponding feature map.

Examples

Example 1:

Input: x = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])

Output: [5.5, 6.5, 7.5]

Explanation: For each channel, compute the average of all elements. For channel 0: (1+4+7+10)/4 = 5.5, for channel 1: (2+5+8+11)/4 = 6.5, for channel 2: (3+6+9+12)/4 = 7.5.

Starter Code

import numpy as np

def global_avg_pool(x: np.ndarray) -> np.ndarray:
	# Your code here
	pass

Implement Global Average Pooling

Examples

Starter Code