xinnn32

/

BlockAssist

like 0

• "ray.rllib.policy.sample_batch.SampleBatch",
• "ray.cloudpickle.cloudpickle._builtin_type",
• "gymnasium.spaces.tuple.Tuple",
• "ray.rllib.evaluation.collectors.simple_list_collector.SimpleListCollector",
• "mbag.rllib.bc.BCTorchPolicy",
• "builtins.str",
• "numpy.dtype",
• "numpy.core.multiarray.scalar",
• "ray.cloudpickle.cloudpickle_fast._function_setstate",
• "numpy.core.numeric._frombuffer",
• "gymnasium.spaces.box.Box",
• "mbag.rllib.callbacks.MbagCallbacks",
• "mbag.rllib.data_augmentation.randomly_permute_block_types",
• "mbag.environment.goals.goal_transform.TransformedGoalGenerator",
• "ray.rllib.core.learner.learner.TorchCompileWhatToCompile",
• "ray.cloudpickle.cloudpickle._make_function",
• "gymnasium.spaces.discrete.Discrete"

How to fix it?

• "gymnasium.spaces.box.Box",
• "mbag.rllib.bc.BC",
• "numpy.core.multiarray.scalar",
• "gymnasium.spaces.discrete.Discrete",
• "mbag.rllib.bc.BCConfig",
• "packaging.version.Version",
• "ray.cloudpickle.cloudpickle._make_cell",
• "packaging._structures.NegativeInfinityType",
• "ray.rllib.policy.sample_batch.SampleBatch",
• "mbag.rllib.callbacks.MbagCallbacks",
• "mbag.rllib.bc.BCTorchPolicy",
• "builtins.int",
• "ray.rllib.policy.policy.PolicySpec",
• "mbag.rllib.data_augmentation.randomly_permute_block_types",
• "ray.cloudpickle.cloudpickle._builtin_type",
• "ray.cloudpickle.cloudpickle._make_function",
• "packaging.version._Version",
• "numpy.core.numeric._frombuffer",
• "builtins.str",
• "collections.defaultdict",
• "gymnasium.spaces.tuple.Tuple",
• "ray.cloudpickle.cloudpickle._make_empty_cell",
• "numpy.dtype",
• "ray.rllib.core.learner.learner.TorchCompileWhatToCompile",
• "ray.cloudpickle.cloudpickle_fast._function_setstate",
• "packaging._structures.InfinityType",
• "mbag.environment.goals.goal_transform.TransformedGoalGenerator",
• "ray.rllib.evaluation.collectors.simple_list_collector.SimpleListCollector"

How to fix it?