Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
ray.tune.error.TuneError: The Trainable/training function is too large for grpc resource limit. Check that its definition is not implicitly capturing a large array or other object in scope. Tip: use tune.with_parameters() to put large objects in the Ray object store.
Original exception: Traceback (most recent call last):
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\experiment\experiment.py", line 150, in init
self._run_identifier = Experiment.register_if_needed(run)
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\experiment\experiment.py", line 352, in register_if_needed
register_trainable(name, run_object)
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 112, in register_trainable
_global_registry.register(TRAINABLE_CLASS, name, trainable)
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 239, in register
self.flush_values()
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 277, in flush_values
_internal_kv_put(
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray_private\client_mode_hook.py", line 103, in wrapper
return func(*args, **kwargs)
File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\experimental\internal_kv.py", line 94, in _internal_kv_put
return global_gcs_client.internal_kv_put(key, value, overwrite, namespace) == 0
File "python\ray_raylet.pyx", line 2690, in ray._raylet._auto_reconnect.wrapper
File "python\ray_raylet.pyx", line 2667, in ray._raylet._auto_reconnect.wrapper
File "python\ray_raylet.pyx", line 2804, in ray._raylet.GcsClient.internal_kv_put
File "python\ray_raylet.pyx", line 580, in ray._raylet.check_status
ray.exceptions.RpcError: Sent message larger than max (845965369 vs. 536870912)
ray.tune.error.TuneError: The Trainable/training function is too large for grpc resource limit. Check that its definition is not implicitly capturing a large array or other object in scope. Tip: use tune.with_parameters() to put large objects in the Ray object store. Original exception: Traceback (most recent call last): File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\experiment\experiment.py", line 150, in init self._run_identifier = Experiment.register_if_needed(run) File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\experiment\experiment.py", line 352, in register_if_needed register_trainable(name, run_object) File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 112, in register_trainable _global_registry.register(TRAINABLE_CLASS, name, trainable) File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 239, in register self.flush_values() File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\tune\registry.py", line 277, in flush_values _internal_kv_put( File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray_private\client_mode_hook.py", line 103, in wrapper return func(*args, **kwargs) File "C:\ProgramData\anaconda3\envs\myenv\lib\site-packages\ray\experimental\internal_kv.py", line 94, in _internal_kv_put return global_gcs_client.internal_kv_put(key, value, overwrite, namespace) == 0 File "python\ray_raylet.pyx", line 2690, in ray._raylet._auto_reconnect.wrapper File "python\ray_raylet.pyx", line 2667, in ray._raylet._auto_reconnect.wrapper File "python\ray_raylet.pyx", line 2804, in ray._raylet.GcsClient.internal_kv_put File "python\ray_raylet.pyx", line 580, in ray._raylet.check_status ray.exceptions.RpcError: Sent message larger than max (845965369 vs. 536870912)