Adding polynet config

configs/experiment/routing/polynet.yaml

@@ -0,0 +1,43 @@
+# @package _global_
+
+defaults:
+  - override /model: polynet.yaml
+  - override /env: tsp.yaml
+  - override /callbacks: default.yaml
+  - override /trainer: default.yaml
+  - override /logger: wandb.yaml
+
+env:
+  generator_params:
+    num_loc: 50
+
+logger:
+  wandb:
+    project: "rl4co"
+    tags: ["polynet", "${env.name}"]
+    group: "${env.name}${env.generator_params.num_loc}"
+    name: "polynet-${env.name}${env.generator_params.num_loc}-${model.k}"
+
+model:
+  k: 100
+  val_num_solutions: ${model.k}
+  batch_size: 512
+  val_batch_size: 1024
+  test_batch_size: 1024
+  train_data_size: 1_280_000
+  val_data_size: 10_000
+  test_data_size: 10_000
+  optimizer_kwargs:
+    lr: 1e-4
+    weight_decay: 1e-6
+  lr_scheduler:
+    "MultiStepLR"
+  lr_scheduler_kwargs:
+    milestones: [80, 95]
+    gamma: 0.1
+
+trainer:
+  max_epochs: 100
+
+seed: 1234
+

configs/model/polynet.yaml

@@ -0,0 +1,11 @@
+_target_: rl4co.models.PolyNet
+
+# During val/test only we apply dihedral transformations
+num_augment: 8
+
+metrics:
+  train: ["loss", "reward"]
+  val: ["reward", "max_reward", "max_aug_reward"]
+  test: ${model.metrics.val}
+  log_on_step: True
+