The graph-conv-memory-paper from smorad

The Rllib example is broken with Ray 1.6.0?

Hi Team,

I am trying to reproduce the result with your Rllib example with Rllib 1.6.0. However, I am seeing serialization errors. Which RLlib version did your team use? And which python version you were running? Starting with Rllib 1.6.0, it requires to be running with Python 3.8+

Given Rllib example

import torch
import torch_geometric

from ray import tune
from ray.rllib.examples.env.stateless_cartpole import StatelessCartPole

from models.ray_graph import RayObsGraph
from models.edge_selectors.temporal import TemporalBackedge

our_gnn = torch_geometric.nn.Sequential(
    "x, adj, weights, B, N",
    [
        (torch_geometric.nn.DenseGraphConv(32, 32), "x, adj -> x"),
        (torch.nn.Tanh()),
        (torch_geometric.nn.DenseGraphConv(32, 32), "x, adj -> x"),
        (torch.nn.Tanh()),
    ],
)
ray_cfg = {
   "env": StatelessCartPole, # Replace this with your desired env
   "framework": "torch",
   "model": {
      "custom_model": RayObsGraph,
      "custom_model_config": {
         "gnn_input_size": 32,
         "gnn_output_size": 32,
         "gnn": our_gnn,
         "edge_selectors": TemporalBackedge([1])
      }
   }
}
tune.run("PPO", config=ray_cfg)

Serialization errors

== Status ==
Memory usage on this node: 12.2/125.7 GiB
Using FIFO scheduling algorithm.
Resources requested: 0/64 CPUs, 0/2 GPUs, 0.0/73.03 GiB heap, 0.0/35.29 GiB objects (0.0/1.0 accelerator_type:G)
Result logdir: .../ray_results/PPO
Number of trials: 1/1 (1 PENDING)
+-----------------------------------+----------+-------+
| Trial name                        | status   | loc   |
|-----------------------------------+----------+-------|
| PPO_StatelessCartPole_d2ce0_00000 | PENDING  |       |
+-----------------------------------+----------+-------+


2021-10-01 14:46:04,966 ERROR trial_runner.py:773 -- Trial PPO_StatelessCartPole_d2ce0_00000: Error processing event.
Traceback (most recent call last):
  File "/.../lib/python3.8/site-packages/ray/tune/trial_runner.py", line 739, in _process_trial
    results = self.trial_executor.fetch_result(trial)
  File "/.../lib/python3.8/site-packages/ray/tune/ray_trial_executor.py", line 746, in fetch_result
    result = ray.get(trial_future[0], timeout=DEFAULT_GET_TIMEOUT)
  File "/.../lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 82, in wrapper
    return func(*args, **kwargs)
  File "/.../lib/python3.8/site-packages/ray/worker.py", line 1623, in get
    raise value
ray.exceptions.RayActorError: The actor died because of an error raised in its creation task, ray::PPO.__init__() (pid=1114116, ip=10.1.14.58)
  Some of the input arguments for this task could not be computed:
ray.exceptions.RaySystemError: System error: No module named 'Sequential_d2ce07'
traceback: Traceback (most recent call last):
  File "/.../lib/python3.8/site-packages/ray/serialization.py", line 254, in deserialize_objects
    obj = self._deserialize_object(data, metadata, object_ref)
  File "/.../lib/python3.8/site-packages/ray/serialization.py", line 190, in _deserialize_object
    return self._deserialize_msgpack_data(data, metadata_fields)
  File "/.../python3.8/site-packages/ray/serialization.py", line 168, in _deserialize_msgpack_data
    python_objects = self._deserialize_pickle5_data(pickle5_data)
  File "/.../python3.8/site-packages/ray/serialization.py", line 158, in _deserialize_pickle5_data
    obj = pickle.loads(in_band)
ModuleNotFoundError: No module named 'Sequential_d2ce07'
Result for PPO_StatelessCartPole_d2ce0_00000:
  {}

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The Rllib example is broken with Ray 1.6.0?

Given Rllib example

Serialization errors

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