googlenet-simplified.m4

// Copyright 2022 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// This is a simplified visualization of the GoogLeNet model definition, which
// collapses all Inception module node clusters into a single node for ease of
// understanding and implementation.
//
// See the Makefile to generate the SVG output; this file must be pre-processed
// with M4 first.

digraph GoogLeNet {

  label = "GoogLeNet model simplified: single-node Inception modules";
  fontsize = 32;
  labelloc = "top";
  rankdir = "BT";

  stylesheet = "googlenet.css";

  // Default settings for all nodes.
  node [
    shape = "box",
    fontname = "Verdana",
    fontsize = 10,
  ];

  input [
    shape = "octagon",
  ];

  Conv_7x7 [
    label = "Conv\n7x7+2(S)",
    class = "conv",
    fillcolor = "#346df1",
  ];

  MaxPool_1 [
    label = "MaxPool\n3x3+2(S)",
    class = "pool",
  ];

  LocalRespNorm_1 [
    label = "LocalRespNorm",
    class = "localrespnorm",
  ];

  Conv_1x1 [
    label = "Conv\n1x1+1(V)",
    class = "conv",
  ];

  Conv_3x3 [
    label = "Conv\n3x3+1(S)",
    class = "conv",
  ];

  LocalRespNorm_2 [
    label = "LocalRespNorm",
    class = "localrespnorm",
  ];

  MaxPool_2 [
    label = "MaxPool\n3x3+2(S)",
    class = "pool",
  ];

  MaxPool_3 [
    label = "MaxPool\n3x3+2(S)",
    class = "pool",
  ];

  MaxPool_4 [
    label = "MaxPool\n3x3+2(S)",
    class = "pool",
  ];

  // Output 0

  output0_AveragePool [
    label = "AveragePool\n5x5+3(V)",
    class = "pool",
  ];

  output0_Conv [
    label = "Conv\n1x1+1(S)",
    class = "conv",
  ];

  output0_FC_1 [
    label = "FC",
    class = "fc",
  ];

  output0_FC_2 [
    label = "FC",
    class = "fc",
  ];

  output0_Activation [
    label = "SoftmaxActivation",
    class = "softmax",
  ];

  softmax0 [
    shape = "octagon",
  ];

  // Output 1

  output1_AveragePool [
    label = "AveragePool\n5x5+3(V)",
    class = "pool",
  ];

  output1_Conv [
    label = "Conv\n1x1+1(S)",
    class = "conv",
  ];

  output1_FC_1 [
    label = "FC",
    class = "fc",
  ];

  output1_FC_2 [
    label = "FC",
    class = "fc",
  ];

  output1_Activation [
    label = "SoftmaxActivation",
    class = "softmax",
  ];

  softmax1 [
    shape = "octagon",
  ];

  // Output 2

  output2_AveragePool [
    label = "AveragePool\n5x5+3(V)",
    class = "pool",
  ];

  output2_FC [
    label = "FC",
    class = "fc",
  ];

  output2_Activation [
    label = "SoftmaxActivation",
    class = "softmax",
  ];

  softmax2 [
    shape = "octagon",
  ];

  // All the Inception modules.

  Inception_3a [
    label = "Inception 3a",
    class = "inception",
  ];

  Inception_3b [
    label = "Inception 3b",
    class = "inception",
  ];

  Inception_4a [
    label = "Inception 4a",
    class = "inception",
  ];

  Inception_4b [
    label = "Inception 4b",
    class = "inception",
  ];

  Inception_4c [
    label = "Inception 4c",
    class = "inception",
  ];

  Inception_4d [
    label = "Inception 4d",
    class = "inception",
  ];

  Inception_4e [
    label = "Inception 4e",
    class = "inception",
  ];

  Inception_5a [
    label = "Inception 5a",
    class = "inception",
  ];

  Inception_5b [
    label = "Inception 5b",
    class = "inception",
  ];

  input ->
    Conv_7x7 ->
    MaxPool_1 ->
    LocalRespNorm_1 ->
    Conv_1x1 ->
    Conv_3x3 ->
    LocalRespNorm_2 ->
    MaxPool_2 ->
    Inception_3a ->
    Inception_3b ->
    MaxPool_3 ->
    Inception_4a ->
    Inception_4b ->
    Inception_4c ->
    Inception_4d ->
    Inception_4e ->
    MaxPool_4 ->
    Inception_5a ->
    Inception_5b;

  Inception_4a ->
    output0_AveragePool ->
    output0_Conv ->
    output0_FC_1 ->
    output0_FC_2 ->
    output0_Activation ->
    softmax0;

  Inception_4d ->
    output1_AveragePool ->
    output1_Conv ->
    output1_FC_1 ->
    output1_FC_2 ->
    output1_Activation ->
    softmax1;

  Inception_5b ->
    output2_AveragePool ->
    output2_FC ->
    output2_Activation ->
    softmax2;
}