input shape of convolutional neural network in keras
Make sure your image size is same as the size your Input layer is expecting. Classification architectures, in general, are not flexible to the spatial dimensions of your input. So, that is important. Otherwise you will get a shape mismatch error.
In case you want to change the input shape of your model, that is possible to do. It's hard to say exactly how it will affect your classification. You have to, probably, also tune your CNN filters so that the filters are not bigger than your feature maps. Otherwise that might downgrade your performance. But you can try that out and see what happens.
I am trying to build a image classifier using cnn. My images are of (256,256) pixel size. 
What will happen if i train the cnn by setting the input shape as (64,64) or (128,128), since (256,256) will take a lot of time to process?