RunNX/assets/complex_graph.dot at main · JGalego/RunNX · GitHub

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digraph G {
  rankdir=TB;
  node [shape=box, style=rounded];

  "image_input" [shape=ellipse, color=green, label="image_input"];
  "mask_input" [shape=ellipse, color=green, label="mask_input"];
  "conv1_weight" [shape=diamond, color=blue, label="conv1_weight"];
  "conv1_bias" [shape=diamond, color=blue, label="conv1_bias"];
  "fc_bias" [shape=diamond, color=blue, label="fc_bias"];
  "fc_weight" [shape=diamond, color=blue, label="fc_weight"];
  "conv1" [label="conv1\n(Conv)"];
  "relu1" [label="relu1\n(Relu)"];
  "maxpool1" [label="maxpool1\n(MaxPool)"];
  "global_avg_pool" [label="global_avg_pool\n(GlobalAveragePool)"];
  "flatten" [label="flatten\n(Flatten)"];
  "fc_classifier" [label="fc_classifier\n(MatMul)"];
  "add_bias" [label="add_bias\n(Add)"];
  "upsample" [label="upsample\n(Upsample)"];
  "mask_attention" [label="mask_attention\n(Mul)"];
  "seg_conv" [label="seg_conv\n(Conv)"];
  "classification" [shape=ellipse, color=red, label="classification"];
  "segmentation" [shape=ellipse, color=red, label="segmentation"];

  "image_input" -> "conv1";
  "conv1_weight" -> "conv1";
  "conv1_bias" -> "conv1";
  "conv1" -> "conv1_output";
  "conv1_output" -> "relu1";
  "relu1" -> "relu1_output";
  "relu1_output" -> "maxpool1";
  "maxpool1" -> "maxpool1_output";
  "maxpool1_output" -> "global_avg_pool";
  "global_avg_pool" -> "gap_output";
  "gap_output" -> "flatten";
  "flatten" -> "flatten_output";
  "flatten_output" -> "fc_classifier";
  "fc_weight" -> "fc_classifier";
  "fc_classifier" -> "fc_output";
  "fc_output" -> "add_bias";
  "fc_bias" -> "add_bias";
  "add_bias" -> "classification";
  "maxpool1_output" -> "upsample";
  "upsample" -> "upsample_output";
  "upsample_output" -> "mask_attention";
  "mask_input" -> "mask_attention";
  "mask_attention" -> "masked_features";
  "masked_features" -> "seg_conv";
  "seg_conv" -> "segmentation";
}