# Add step info dictionary to MLflowLoggerCallback with Tune **URL:** \ **Category:** RLlib\ **Created:** [July 6, 2022, 11:25am UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740 "2022-07-06T11:25:54Z")\ **Posts on this page:** 8\ **Page:** 1
**Author:** ![fedetask](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/fedetask/32/2233_2.png) [@fedetask](https://discuss.ray.io/u/fedetask)\ **Post date:** [July 6, 2022, 11:25am UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/1 "2022-07-06T11:25:54Z")
**How severe does this issue affect your experience of using Ray?** - Medium: It contributes to significant difficulty to complete my task, but I can work around it. I am using RLlib with ML Flow, by using the `MLflowLoggerCallback` and passing it to ```python tune.run( **config, callback=MLflowLoggerCallback(experiment_name="test") ) ``` However, this makes the callback log only a few metrics that are generated by RLlib. In my environment, I return several metrics of interest in the `info` returned at each environment step. How can I have them logged by MLFlow? ---
**Author:** ![mannyv](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/mannyv/32/606_2.png) [@mannyv](https://discuss.ray.io/u/mannyv)\ **Post date:** [July 6, 2022, 12:39pm UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/2 "2022-07-06T12:39:59Z")
Hi @fedetask, You need to add a callback that adds your custom metrics. Here is an explanation: [https://docs.ray.io/en/latest/rllib/rllib-training.html#callbacks-and-custom-metrics](https://docs.ray.io/en/latest/rllib/rllib-training.html#callbacks-and-custom-metrics) Here is an example: > * * * > **[Manny is helping people do cool things with RL](https://www.buymeacoffee.com/mannyv)** > > Hey, so glad we got to connect. If you found my suggestions useful feel free to buy me a coffee! ---
**Author:** ![fedetask](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/fedetask/32/2233_2.png) [@fedetask](https://discuss.ray.io/u/fedetask)\ **Post date:** [July 6, 2022, 1:12pm UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/3 "2022-07-06T13:12:54Z")
So I should have both a `CustomCallback` and the `MLflowLoggerCallback`, right? And the custom callback will add the info to the `custom_metrics`, so they should be passed to `tune.run()` in this order: ```python tune.run(callbacks=[CustomCallback(), MLflowLoggerCallback()]) ``` am I correct? ---
**Author:** ![mannyv](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/mannyv/32/606_2.png) [@mannyv](https://discuss.ray.io/u/mannyv)\ **Post date:** [July 6, 2022, 1:25pm UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/4 "2022-07-06T13:25:48Z")
@fedetask, I do not think that is quite how it should work, but I could be wrong. In my understanding, the `MLflowLoggerCallback` is a tune callback and the `CustomCallback` is an rllib callback. I think it should look something like this. ```auto tune.run(config={..., "callbacks": CustomCallback,}, callbacks=[MLflowLoggerCallback()]) ``` ---
**Author:** ![avnishn](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/avnishn/32/1544_2.png) [@avnishn](https://discuss.ray.io/u/avnishn)\ **Post date:** [July 6, 2022, 9:37pm UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/5 "2022-07-06T21:37:20Z")
@xwjiang2010 can you please chime in here ---
**Author:** ![xwjiang2010](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/xwjiang2010/32/1476_2.png) [@xwjiang2010](https://discuss.ray.io/u/xwjiang2010)\ **Post date:** [July 7, 2022, 3:55am UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/6 "2022-07-07T03:55:24Z")
@mannyv’s understanding of the callbacks is correct. @fedetask did you get a chance to try it? ---
**Author:** ![fedetask](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/fedetask/32/2233_2.png) [@fedetask](https://discuss.ray.io/u/fedetask)\ **Post date:** [July 7, 2022, 8:50am UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/7 "2022-07-07T08:50:37Z")
Hello, Unfortunately, I am using Ray version 1.8.0; I cannot upgrade it for now. I did as @mannyv described but things still don’t work. I think the reason is that in Ray 1.8.0, the `MLflowLoggerCallback` in [mlflow.py](https://github.com/ray-project/ray/blob/ray-1.8.0/python/ray/tune/integration/mlflow.py), lines 148-160, logs stuff as follows: ```python 148 def log_trial_result(self, iteration: int, trial: "Trial", result: Dict): 149 step = result.get(TIMESTEPS_TOTAL) or result[TRAINING_ITERATION] 150 run_id = self._trial_runs[trial] 151 for key, value in result.items(): 152 try: 153 value = float(value) 154 except (ValueError, TypeError): 155 logger.debug("Cannot log key {} with value {} since the " 156 "value cannot be converted to float.".format( 157 key, value)) 158 continue 159 self.client.log_metric( 160 run_id=run_id, key=key, value=value, step=step) ``` and for `key='custom_metrics'`, `value` is a dictionary that cannot be cast to `float` in line 153 and therefore isn’t logged. I solved it by creating a new class that extends `MLflowLoggerCallback` and overriding the `log_trial_result` to allow for the `custom_metrics` dictionary to be logged. ---
**Author:** ![olipinski](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/olipinski/32/2903_2.png) [@olipinski](https://discuss.ray.io/u/olipinski)\ **Post date:** [July 19, 2022, 8:55am UTC](https://discuss.ray.io/t/add-step-info-dictionary-to-mlflowloggercallback-with-tune/6740/8 "2022-07-19T08:55:47Z")
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