Hands-On Convolutional Neural Networks with TensorFlow

Feeding data with placeholders

Placeholders are Tensor-like objects. They are a contract between you and TensorFlow that says when you run your computation graph in a session, you will supply or feed data into that placeholder so that your graph can run successfully.

They are Tensor-like objects as they behave like Tensors, meaning you can pass them around in places where you would put a Tensor.

By using placeholders, we can supply external inputs into our graph that might change each time we run our graph. The natural use for them is as a way to supply data and labels into our model as the data and labels we supply will generally be different each time we want to run our graph.

When creating a placeholder, we must supply the datatype that ...