Model for large scale image classification. Uses parallel architecture that expanding Batches by each Convolutional Desne Layer.
OCDNet uses parataxis CNN architecture, which the Convolution Layers are layed parallelly like as a node of Linear Layer. With the parallel architecture, batch is expanding as amount of Amount(prev layer's convolution node) X Amount(current layer's convolution node)
To maximize the expanding batch's advantage and fix the batch size, OCDNet uses 3 ways.
- Add all the Batches and multiply with Expanding Gamma
- Random Batching
- Just add all the batches
pip install -r requirements.txt