How does Keras 1d convolution layer work with word embeddings – text classification problem? (Filters, kernel size, and all hyperparameter)

I am currently developing a text classification tool using Keras. It works (it works fine and I got up to 98.7 validation accuracy) but I can’t wrap my head around about how exactly 1D-convolution layer works with text data.

ValueError at /image/ Tensor Tensor(“activation_5/Softmax:0”, shape=(?, 4), dtype=float32) is not an element of this graph

I am building an image processing classifier and this code is an API to predict the image class of the image the whole code is running except this line (pred = model.predict_classes(test_image)) this API is made in Django framework and am using python 2.7