Keras: difference of InputLayer and Input

Question

I made a model using Keras with Tensorflow. I use Inputlayer with these lines of code:

img1 = tf.placeholder(tf.float32, shape=(None, img_width, i         


        

Answer 1

• InputLayer is a layer.
• Input is a tensor.

You can only call layers passing tensors to them.

The idea is:

outputTensor = SomeLayer(inputTensor)

So, only Input can be passed because it's a tensor.

Honestly, I have no idea about the reason for the existence of InputLayer. Maybe it's supposed to be used internally. I never used it, and it seems I'll never need it.

Answer 2

According to tensorflow website, "It is generally recommend to use the functional layer API via Input, (which creates an InputLayer) without directly using InputLayer." Know more at this page here