From 8d6df2b27644f6c8a4922262b9d78166d5bf614d Mon Sep 17 00:00:00 2001
From: Dominik Jain <d.jain@appliedai.de>
Date: Mon, 8 Jan 2024 18:12:43 +0100
Subject: [PATCH] Add high-level discrete example (CartPole) for README

---
 examples/discrete/discrete_dqn_hl.py | 55 ++++++++++++++++++++++++++++
 1 file changed, 55 insertions(+)
 create mode 100644 examples/discrete/discrete_dqn_hl.py

diff --git a/examples/discrete/discrete_dqn_hl.py b/examples/discrete/discrete_dqn_hl.py
new file mode 100644
index 0000000..c6092f2
--- /dev/null
+++ b/examples/discrete/discrete_dqn_hl.py
@@ -0,0 +1,55 @@
+from tianshou.highlevel.config import SamplingConfig
+from tianshou.highlevel.env import (
+    EnvFactoryGymnasium,
+    VectorEnvType,
+)
+from tianshou.highlevel.experiment import DQNExperimentBuilder, ExperimentConfig
+from tianshou.highlevel.params.policy_params import DQNParams
+from tianshou.highlevel.trainer import (
+    EpochStopCallbackRewardThreshold,
+    EpochTestCallbackDQNSetEps,
+    EpochTrainCallbackDQNSetEps,
+)
+from tianshou.utils.logging import run_main
+
+
+def main():
+    experiment = (
+        DQNExperimentBuilder(
+            EnvFactoryGymnasium(task="CartPole-v1", seed=0, venv_type=VectorEnvType.DUMMY),
+            ExperimentConfig(
+                persistence_enabled=False,
+                watch=True,
+                watch_render=1 / 35,
+                watch_num_episodes=100,
+            ),
+            SamplingConfig(
+                num_epochs=10,
+                step_per_epoch=10000,
+                batch_size=64,
+                num_train_envs=10,
+                num_test_envs=100,
+                buffer_size=20000,
+                step_per_collect=10,
+                update_per_step=1 / 10,
+            ),
+        )
+        .with_dqn_params(
+            DQNParams(
+                lr=1e-3,
+                discount_factor=0.9,
+                estimation_step=3,
+                target_update_freq=320,
+            ),
+        )
+        .with_model_factory_default(hidden_sizes=(64, 64))
+        .with_epoch_train_callback(EpochTrainCallbackDQNSetEps(0.3))
+        .with_epoch_test_callback(EpochTestCallbackDQNSetEps(0.0))
+        .with_epoch_stop_callback(EpochStopCallbackRewardThreshold(195))
+        .build()
+    )
+    experiment.run()
+
+
+if __name__ == "__main__":
+    run_main(main)