Add sb3 learn progress bar

config_examples/config_freqai.example.json

@@ -73,7 +73,8 @@
                 10,
                 20
             ],
-            "plot_feature_importances": 0
+            "plot_feature_importances": 0,
+            "progress_bar": false
         },
         "data_split_parameters": {
             "test_size": 0.33,

docs/freqai-parameter-table.md

@@ -85,6 +85,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 | `net_arch` | Network architecture which is well described in [`stable_baselines3` doc](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#examples). In summary: `[<shared layers>, dict(vf=[<non-shared value network layers>], pi=[<non-shared policy network layers>])]`. By default this is set to `[128, 128]`, which defines 2 shared hidden layers with 128 units each.
 | `randomize_starting_position` | Randomize the starting point of each episode to avoid overfitting. <br> **Datatype:** bool. <br> Default: `False`.
 | `drop_ohlc_from_features` | Do not include the normalized ohlc data in the feature set passed to the agent during training (ohlc will still be used for driving the environment in all cases) <br> **Datatype:** Boolean. <br> **Default:** `False`
+| `progress_bar` | Display a progress bar with the current progress, elapsed time and estimated remaining time. <br> **Datatype:** Boolean. <br> Default: `False`.
 
 ### Additional parameters
 

freqtrade/constants.py

@@ -599,6 +599,7 @@ CONF_SCHEMA = {
                         "policy_type": {"type": "string", "default": "MlpPolicy"},
                         "net_arch": {"type": "array", "default": [128, 128]},
                         "randomize_startinng_position": {"type": "boolean", "default": False},
+                        "progress_bar": {"type": "boolean", "default": False},
                         "model_reward_parameters": {
                             "type": "object",
                             "properties": {

freqtrade/freqai/prediction_models/ReinforcementLearner.py

@@ -71,7 +71,8 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
 
         model.learn(
             total_timesteps=int(total_timesteps),
-            callback=[self.eval_callback, self.tensorboard_callback]
+            callback=[self.eval_callback, self.tensorboard_callback],
+            progress_bar=self.freqai_info["rl_config"]["progress_bar"]
         )
 
         if Path(dk.data_path / "best_model.zip").is_file():

requirements-freqai-rl.txt

@@ -8,3 +8,6 @@ sb3-contrib==1.7.0; python_version < '3.11'
 # Gym is forced to this version by stable-baselines3.
 setuptools==65.5.1 # Should be removed when gym is fixed.
 gym==0.21; python_version < '3.11'
+# Progress bar for stable-baselines3 and sb3-contrib
+tqdm==4.65.0; python_version < '3.11'
+rich==13.3.3; python_version < '3.11'