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…