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Local Mode - TypeError: unhashable type: 'list'

See original GitHub issue

I’m training an A3C trainer with Pytorch and tune.run().

     tune.run(a3c.A3CTrainer, local_dir=".", stop={"episode_reward_mean": 0.5}, 
     resources_per_trial={"cpu":1, "gpu":1},
     config={"env": "my_env",  
                             "use_pytorch": True,
                             "model": {"custom_model": "my_model"},
                             "num_workers": 1,
                             "train_batch_size": 32,
                             "sample_batch_size": 16,
                             "num_envs_per_worker": 1,
            })

I’m getting the error File "/mnt/miniconda/envs/proteus_rl_env/lib/python3.6/site-packages/ray/rllib/optimizers/async_gradients_optimizer.py", line 43, in step pending_gradients[future] = e TypeError: unhashable type: 'list'

The same code with another trainer, i.e, PGTrainer is working:

     tune.run(pg.PGTrainer, local_dir=".", stop={"episode_reward_mean": 0.5}, 
     resources_per_trial={"cpu":1, "gpu":1},
     config={"env": "my_env",  
                             "use_pytorch": True,
                             "model": {"custom_model": "my_model"},
                            "num_workers": 1,
                             "train_batch_size": 32,
                             "sample_batch_size": 16,
                             "num_envs_per_worker": 1,
                             })

Are there some specific changes to be done while running the A3C trainer?

Any leads will be appreciated!

Issue Analytics

State:
Created 4 years ago
Comments:6 (6 by maintainers)

Top GitHub Comments

1reaction

richardliawcommented, Aug 6, 2019

OK this should be fixed in the release; closing for now but reopen if needed.

0reactions

richardliawcommented, Aug 3, 2019

I think this is fixed in the upcoming release (0.7.3). If you need the feature now, you can install the latest snapshot of master (https://ray.readthedocs.io/en/latest/installation.html#trying-snapshots-from-master)