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I have run and modified the program using Windows, but it still does not generate Delay.txt in the folder after running.
python ddpg.py
2023-02-22 23:33:46.740377: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-22 23:33:47.139438: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:357] MLIR V1 optimization pass is not enabled
C:\Users\bill8.conda\envs\fordemo\lib\site-packages\keras\optimizers\optimizer_v2\adam.py:114: UserWarning: The lr argument is deprecated, use learning_rate instead.
super().init(name, **kwargs)
2023-02-22 23:33:47.411766: W tensorflow/c/c_api.cc:291] Operation '{name:'Adam/a_V/bias/v/Assign' id:345 op device:{requested: '', assigned: ''} def:{{{node Adam/a_V/bias/v/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](Adam/a_V/bias/v, Adam/a_V/bias/v/Initializer/zeros)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
Cannot find the weight
OMNeT++ Experiment Start.
Episode : 0 Replay Buffer 0
C:\Users\bill8.conda\envs\fordemo\lib\site-packages\keras\engine\training_v1.py:2356: UserWarning: Model.state_updates will be removed in a future version. This property should not be used in TensorFlow 2.0, as updates are applied automatically.
updates=self.state_updates,
2023-02-22 23:33:47.570289: W tensorflow/c/c_api.cc:291] Operation '{name:'a_V/Sigmoid' id:85 op device:{requested: '', assigned: ''} def:{{{node a_V/Sigmoid}} = SigmoidT=DT_FLOAT, _has_manual_control_dependencies=true}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
Traceback (most recent call last):
File "C:\omnetpp-4.6\ddpg.py", line 231, in
playGame(DDPG_config, train_indicator=1)
File "C:\omnetpp-4.6\ddpg.py", line 140, in playGame
s_t1, r_t, done = env.step(a_t[0])
File "C:\omnetpp-4.6\Environment.py", line 467, in step
om_output = file_to_csv(self.folder + OMDELAY)
File "C:\omnetpp-4.6\Environment.py", line 46, in file_to_csv
with open(file_name, 'r') as file:
FileNotFoundError: [Errno 2] No such file or directory: 'runs//t1677080026736617/Delay.txt'
I have run and modified the program using Windows, but it still does not generate Delay.txt in the folder after running.
python ddpg.py
2023-02-22 23:33:46.740377: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-22 23:33:47.139438: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:357] MLIR V1 optimization pass is not enabled
C:\Users\bill8.conda\envs\fordemo\lib\site-packages\keras\optimizers\optimizer_v2\adam.py:114: UserWarning: The
lr
argument is deprecated, uselearning_rate
instead.super().init(name, **kwargs)
2023-02-22 23:33:47.411766: W tensorflow/c/c_api.cc:291] Operation '{name:'Adam/a_V/bias/v/Assign' id:345 op device:{requested: '', assigned: ''} def:{{{node Adam/a_V/bias/v/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](Adam/a_V/bias/v, Adam/a_V/bias/v/Initializer/zeros)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
Cannot find the weight
OMNeT++ Experiment Start.
Episode : 0 Replay Buffer 0
C:\Users\bill8.conda\envs\fordemo\lib\site-packages\keras\engine\training_v1.py:2356: UserWarning:
Model.state_updates
will be removed in a future version. This property should not be used in TensorFlow 2.0, asupdates
are applied automatically.updates=self.state_updates,
2023-02-22 23:33:47.570289: W tensorflow/c/c_api.cc:291] Operation '{name:'a_V/Sigmoid' id:85 op device:{requested: '', assigned: ''} def:{{{node a_V/Sigmoid}} = SigmoidT=DT_FLOAT, _has_manual_control_dependencies=true}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
Traceback (most recent call last):
File "C:\omnetpp-4.6\ddpg.py", line 231, in
playGame(DDPG_config, train_indicator=1)
File "C:\omnetpp-4.6\ddpg.py", line 140, in playGame
s_t1, r_t, done = env.step(a_t[0])
File "C:\omnetpp-4.6\Environment.py", line 467, in step
om_output = file_to_csv(self.folder + OMDELAY)
File "C:\omnetpp-4.6\Environment.py", line 46, in file_to_csv
with open(file_name, 'r') as file:
FileNotFoundError: [Errno 2] No such file or directory: 'runs//t1677080026736617/Delay.txt'
The modified code is available at
https://github.com/bill8363/FIX_a-deep-rl-approach-for-sdn-routing-optimization/blob/main/Environment.py
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