converting an array of size (n,n,m) to (None,n,n,m)
The shape (None, 14,14,3) represent ,(batch_size,imgH,imgW,imgChannel) now imgH and imgW can be use interchangeably depends on the network and the problem. 
But the batchsize is given as "None" in the neural network because we don't want to restrict our batchsize to some specific value as our batchsize depends on a lot of factors like memory available for our model to run etc.
So lets say you have 4 images of size 14x14x3 then you can append each image into the array say L1, and now the L1 will have the shape 4x14x14x3 i.e you made a batch of 4 images and now you can feed this to your neural network. 
NOTE here None will be replaced by 4 and for the whole training process it will be 4. Similarly when you feed your network only one image it assumes the batchsize of 1 and set None equal to 1 giving you the shape (1X14X14X3)
I am trying to reshape an array of size (14,14,3) to (None, 14,14,3). I have seen that the output of each layer in convolutional neural network has shape in the format(None, n, n, m). 
Consider that the name of my array is arr
I tried arr[None,:,:] but it converts it to a dimension of (1,14,14,3).
How should I do it?