The GlobalAveragePooling2D layer in Python's Keras library is used in deep learning models to reduce the spatial dimensions of a 2D input tensor. It computes the average value of each channel across the entire input feature map. This layer is typically used to extract global features from an image or feature maps generated by convolutional layers. The resulting output tensor has a fixed size regardless of the input size, allowing for easier and more efficient computations in subsequent layers.
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