BasicConv2d

BasicConv2d is a type of convolutional layer used in deep learning models for image classification tasks. It is a simple, yet effective, implementation of a convolutional layer that performs a 2D convolution operation on the input image. The BasicConv2d layer typically consists of a set of learnable filters or kernels, which are convolved with the input image to produce a set of output feature maps. These feature maps are then passed through a non-linear activation function to introduce non-linearity into the model. The BasicConv2d layer is often used as the first layer in a deep learning model, as it can help to extract low-level features from the input image. Overall, BasicConv2d is a widely used building block in many state-of-the-art deep learning models for image classification tasks.