Neural Network (Keras)

Keras, the high-level interface to the TensorFlow machine learning library, uses Graphviz to visualize how the neural networks connect. This is particularly useful for non-linear neural networks, with merges and forks in the directed graph.

This is a simple neural network (from Keras Functional API) for ranking customer issue tickets by priority and routing to which department can handle the ticket. Generated using Keras' model_to_dot function.

This model has three inputs:

  • issue title text
  • issue body test
  • issue tags

and two outputs:

  • predicted priority
  • predicted department

Each node is labelled with the shape (length, width) of its input and output matrices. None is shown where the shape is undecided yet, where the shape depends on the final data you train this model against.

[Input .gv File] [SVG] [Raster Image]

neural-network.gv.txt
digraph G {
  concentrate=True;
  rankdir=TB;
  node [shape=record];
  140087530674552 [label="title: InputLayer\n|{input:|output:}|{{[(?, ?)]}|{[(?, ?)]}}"];
  140087537895856 [label="body: InputLayer\n|{input:|output:}|{{[(?, ?)]}|{[(?, ?)]}}"];
  140087531105640 [label="embedding_2: Embedding\n|{input:|output:}|{{(?, ?)}|{(?, ?, 64)}}"];
  140087530711024 [label="embedding_3: Embedding\n|{input:|output:}|{{(?, ?)}|{(?, ?, 64)}}"];
  140087537980360 [label="lstm_2: LSTM\n|{input:|output:}|{{(?, ?, 64)}|{(?, 128)}}"];
  140087531256464 [label="lstm_3: LSTM\n|{input:|output:}|{{(?, ?, 64)}|{(?, 32)}}"];
  140087531106200 [label="tags: InputLayer\n|{input:|output:}|{{[(?, 12)]}|{[(?, 12)]}}"];
  140087530348048 [label="concatenate_1: Concatenate\n|{input:|output:}|{{[(?, 128), (?, 32), (?, 12)]}|{(?, 172)}}"];
  140087530347992 [label="priority: Dense\n|{input:|output:}|{{(?, 172)}|{(?, 1)}}"];
  140087530711304 [label="department: Dense\n|{input:|output:}|{{(?, 172)}|{(?, 4)}}"];
  140087530674552 -> 140087531105640;
  140087537895856 -> 140087530711024;
  140087531105640 -> 140087537980360;
  140087530711024 -> 140087531256464;
  140087537980360 -> 140087530348048;
  140087531256464 -> 140087530348048;
  140087531106200 -> 140087530348048;
  140087530348048 -> 140087530347992;
  140087530348048 -> 140087530711304;
}

Last modified May 10, 2021: Move gallery to Docsy (164fb41)