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TFException: Shape [-1,24] has negative dimensions #24
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Hi, Thank you for you question. It seems to me that you forgot to add a custom placeholder in your Internal Brain. In Embedding the trained model itself it says you need to add a float placeholder called |
Please let us know if you are able to get the epsilon parameter to work for you to run the agent natively. |
Ah yep sure enough that's the problem. I remember setting that on the Ball3Ddemo but overlooked it on my own scene, it would be awesome if there was a warning about that built in |
I have similar issues with "Shape [-1,24] has negative dimensions", and after set "graph placeholders" like in Ball3D I get from unity console this error: TFException: Attempting to use uninitialized value dense/kernel |
This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs. |
I was running a training session in the PPO notebook and stopped it , then exported the graph
but when I use this .bytes file in Unity I get
TFException: Shape [-1,24] has negative dimensions [[Node: epsilon = Placeholder[dtype=DT_FLOAT, shape=[?,24], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] TensorFlow.TFStatus.CheckMaybeRaise (TensorFlow.TFStatus incomingStatus, System.Boolean last) (at <6ed6db22f8874deba74ffe3e566039be>:0) TensorFlow.TFSession.Run (TensorFlow.TFOutput[] inputs, TensorFlow.TFTensor[] inputValues, TensorFlow.TFOutput[] outputs, TensorFlow.TFOperation[] targetOpers, TensorFlow.TFBuffer runMetadata, TensorFlow.TFBuffer runOptions, TensorFlow.TFStatus status) (at <6ed6db22f8874deba74ffe3e566039be>:0) TensorFlow.TFSession+Runner.Run (TensorFlow.TFStatus status) (at <6ed6db22f8874deba74ffe3e566039be>:0) CoreBrainInternal.DecideAction () (at Assets/ML-Agents/Scripts/CoreBrainInternal.cs:244) Brain.DecideAction () (at Assets/ML-Agents/Scripts/Brain.cs:308) Academy.DecideAction () (at Assets/ML-Agents/Scripts/Academy.cs:250) Academy.RunMdp () (a
not sure why this has a -1 value, I've stopped training prematurely on the Ball3D demo without any problems, anyone have any ideas?
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