How to apply different kernels for each example in a batch

[1chimaruGin (Ichimaru Gin)]

Apply different convolutions to a batch of tensors

So, you have filters in a tensor w of shape: [batch_size, out_channels, in_channels, kernel_height, kernel_width], and images in a tensor x of shape: [batch_size, in_channels, in_height, in_width], and you want an output of shape: [batch_size, out_channels, out_height, out_width], where the i_th output is the convolution of the i_th image by the i_th filter ? You can do it by merging the batch and channel dimensions together, and use a grouped convolution, with groups=batch_size : o = to…