ml-agentsの学習を開始できない。

ml-agentsで学習を開始しようとした所、以下のようなエラーが出ました

Traceback (most recent call last):
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer_controller.py", line 176, in start_learning
n_steps = self.advance(env_manager)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer_controller.py", line 234, in advance
new_step_infos = env_manager.get_steps()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\env_manager.py", line 113, in get_steps
new_step_infos = self._step()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\subprocess_env_manager.py", line 264, in _step
self._queue_steps()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\subprocess_env_manager.py", line 257, in _queue_steps
env_action_info = self._take_step(env_worker.previous_step)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\subprocess_env_manager.py", line 378, in _take_step
all_action_info[brain_name] = self.policies[brain_name].get_action(
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\policy\torch_policy.py", line 212, in get_action
run_out = self.evaluate(
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\policy\torch_policy.py", line 178, in evaluate
action, log_probs, entropy, memories = self.sample_actions(
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\policy\torch_policy.py", line 138, in sample_actions
actions, log_probs, entropies, memories = self.actor_critic.get_action_stats(
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\torch\networks.py", line 509, in get_action_stats
action, log_probs, entropies, actor_mem_out = super().get_action_stats(
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\torch\networks.py", line 318, in get_action_stats
action, log_probs, entropies = self.action_model(encoding, masks)
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\torch\action_model.py", line 195, in forward
log_probs, entropies = self._get_probs_and_entropy(actions, dists)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\torch\action_model.py", line 134, in _get_probs_and_entropy
entropies = torch.cat(entropies_list, dim=1)
RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors. Available functions are [CPU, CUDA, QuantizedCPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

CPU: registered at aten\src\ATen\CPUType.cpp:2127 [kernel]
CUDA: registered at aten\src\ATen\CUDAType.cpp:2983 [kernel]
QuantizedCPU: registered at aten\src\ATen\QuantizedCPUType.cpp:297 [kernel]
BackendSelect: fallthrough registered at ..\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback]
Named: registered at ..\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]
AutogradOther: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradCPU: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradCUDA: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradXLA: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradPrivateUse1: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradPrivateUse2: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
AutogradPrivateUse3: registered at ..\torch\csrc\autograd\generated\VariableType_2.cpp:8078 [autograd kernel]
Tracer: registered at ..\torch\csrc\autograd\generated\TraceType_2.cpp:9654 [kernel]
Autocast: registered at ..\aten\src\ATen\autocast_mode.cpp:258 [kernel]
Batched: registered at ..\aten\src\ATen\BatchingRegistrations.cpp:511 [backend fallback]
VmapMode: fallthrough registered at ..\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\user\Anaconda3\envs\yukkuri\Scripts\mlagents-learn-script.py", line 33, in <module>
sys.exit(load_entry_point('mlagents', 'console_scripts', 'mlagents-learn')())
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\learn.py", line 280, in main
run_cli(parse_command_line())
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\learn.py", line 276, in run_cli
run_training(run_seed, options)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\learn.py", line 153, in run_training
tc.start_learning(env_manager)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer_controller.py", line 201, in start_learning
self._save_models()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer_controller.py", line 84, in _save_models
self.trainers[brain_name].save_model()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer\rl_trainer.py", line 215, in save_model
model_checkpoint = self._checkpoint()
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents-envs\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\trainer\rl_trainer.py", line 189, in checkpoint
checkpoint_path = self.model_saver.save_checkpoint(self.brain_name, self.step)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\model_saver\torch_model_saver.py", line 57, in save_checkpoint
self.export(checkpoint_path, behavior_name)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\model_saver\torch_model_saver.py", line 62, in export
self.exporter.export_policy_model(output_filepath)
File "c:\ml-agents-release_12\ml-agents-release_12\ml-agents\mlagents\trainers\torch\model_serialization.py", line 107, in export_policy_model
torch.onnx.export(
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx_init.py", line 225, in export
return utils.export(model, args, f, export_params, verbose, training,
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx\utils.py", line 85, in export
_export(model, args, f, export_params, verbose, training, input_names, output_names,
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx\utils.py", line 632, in _export
_model_to_graph(model, args, verbose, input_names,
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx\utils.py", line 409, in _model_to_graph
graph, params, torch_out = _create_jit_graph(model, args,
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx\utils.py", line 379, in _create_jit_graph
graph, torch_out = _trace_and_get_graph_from_model(model, args)
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\onnx\utils.py", line 342, in _trace_and_get_graph_from_model
torch.jit._get_trace_graph(model, args, strict=False, _force_outplace=False, _return_inputs_states=True)
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\jit_trace.py", line 1148, in _get_trace_graph
outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\nn\modules\module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\jit_trace.py", line 125, in forward
graph, out = torch._C._create_graph_by_tracing(
File "C:\Users\user\Anaconda3\envs\yukkuri\lib\site-packages\torch\jit_trace.py", line 119, in wrapper
out_vars, _ = _flatten(outs)
RuntimeError: Only tuples, lists and Variables supported as JIT inputs/outputs. Dictionaries and strings are also accepted but their usage is not recommended. But got unsupported type NoneType