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Functions2,539 in github.com/Yonv1943/Python

⨍ Functions 2,539◇ Types & classes 504

↓ 1 callersFunctionrun

()

Plan/TUTO_mnist_1layers.py:230

↓ 1 callersFunctionrun

()

Plan/TUTO_mnist_3layers.py:222

↓ 1 callersFunctionrun

()

Demo/TUTO_edge_detection.py:67

↓ 1 callersFunctionrun

()

Demo/DEMO_url_get_image_urllib.requests.py:74

↓ 1 callersFunctionrun

()

Demo/TUTO_tensorflow_variable.py:10

↓ 1 callersFunctionrun

()

Demo/DEMO_images_show_mp_cv2.py:32

↓ 1 callersFunctionrun

()

Demo/DEMO_edge_detection.py:204

↓ 1 callersFunctionrun

()

Demo/DEMO_images_load_order_mp_cv2.py:59

↓ 1 callersFunctionrun__demo

()

ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/run.py:77

↓ 1 callersFunctionrun__pipe

()

Demo_deep_learning/DEMO_multi_processing.py:82

↓ 1 callersFunctionrun__pipe

()

Demo/DEMO_multi_processing.py:82

↓ 1 callersFunctionrun__pipe

()

ElegantRL/Beta/DeepLearning/DEMO_multi_processing.py:82

↓ 1 callersFunctionrun__pipe

()

ElegantRL/AgentZoo/ElegantRL-MultiGPU/DEMO_multi_processing.py:82

↓ 1 callersFunctionrun__pipeline

(video_path)

Demo/DEMO_cv2_MouseDetect.py:363

↓ 1 callersFunctionrun__train_in_fashion_mnist

(rank_id: int = -1, world_size: int = -1)

Demo_deep_learning/DEMO_DistDataParallel.py:77

↓ 1 callersFunctionrun__tutorial_discrete_action

It is a DQN tutorial, we need 1min for training. This simplify DQN can't work well on harder task. Other RL algorithms can work well on harder

Demo_deep_learning/Tutorial.py:179

↓ 1 callersFunctionrun_client

(host, port)

Demo_deep_learning/DEMO_pickle_server_client_comm.py:17

↓ 1 callersFunctionrun_client

(host, port)

Demo_camera_and_network/server_client_camera.py:66

↓ 1 callersFunctionrun_client

(host, port)

Demo_camera_and_network/server_client_socket.py:22

↓ 1 callersFunctionrun_client

(host, port)

Demo_camera_and_network/server_client_mp_connection.py:19

↓ 1 callersFunctionrun_client

(host, port)

ElegantRL/Beta/DeepLearning/DEMO_pickle_server_client_comm.py:17

↓ 1 callersFunctionrun_client

(host, port)

ElegantRL/AgentZoo/ElegantRL-MultiGPU/DEMO_pickle_server_client_comm.py:17

↓ 1 callersFunctionrun_compare_speed_of_replay_buffer

()

Demo_deep_learning/ReplayBufferComparison.py:182

↓ 1 callersFunctionrun_demo

()

Demo/DEMO_matplotlib.py:207

↓ 1 callersFunctionrun_eval

()

Demo_deep_learning/SignalDetectRNN.py:133

↓ 1 callersFunctionrun_main

()

Demo_deep_learning/classify_train_mp_ring.py:519

↓ 1 callersFunctionrun_main

()

Demo_deep_learning/classify_train_mp.py:485

↓ 1 callersFunctionrun_main

()

ElegantRL/Beta/DeepLearning/classify_train_mp_ring.py:519

↓ 1 callersFunctionrun_main

()

ElegantRL/Beta/DeepLearning/classify_train_mp.py:485

↓ 1 callersFunctionrun_main

()

ElegantRL/AgentZoo/ElegantRL-MultiGPU/classify_train_mp_ring.py:519

↓ 1 callersFunctionrun_main

()

ElegantRL/AgentZoo/ElegantRL-MultiGPU/classify_train_mp.py:485

↓ 1 callersFunctionrun_mp

()

Demo/DEMO_mp_Array_Pipe.py:40

↓ 1 callersFunctionrun_server

(host, port)

Demo_deep_learning/DEMO_pickle_server_client_comm.py:33

↓ 1 callersFunctionrun_server

(host, port)

Demo_camera_and_network/server_client_camera.py:81

↓ 1 callersFunctionrun_server

(host, port)

Demo_camera_and_network/server_client_socket.py:38

↓ 1 callersFunctionrun_server

(host, port)

Demo_camera_and_network/server_client_mp_connection.py:35

↓ 1 callersFunctionrun_server

(host, port)

ElegantRL/Beta/DeepLearning/DEMO_pickle_server_client_comm.py:33

↓ 1 callersFunctionrun_server

(host, port)

ElegantRL/AgentZoo/ElegantRL-MultiGPU/DEMO_pickle_server_client_comm.py:33

↓ 1 callersFunctionrun_single_camera

()

Demo_camera_and_network/ip_camera.py:60

↓ 1 callersFunctionrun_train

()

Demo_deep_learning/SignalDetectRNN.py:57

↓ 1 callersFunctionrun_train_lstm

()

Demo_deep_learning/Demo_RNN_time_seq_predict.py:99

↓ 1 callersFunctionrun_train_lstm

()

Demo_deep_learning/RNN_demo_time_seq_predict.py:98

↓ 1 callersFunctionrun_without_torch_distributed_run

(gpu_ids: Tuple[int, ...] = (0, 1, 2, 3))

Demo_deep_learning/DEMO_DistDataParallel.py:169

↓ 1 callersMethodsample_all

(self)

ElegantRL/Example_SingleFilePPO.py:330

↓ 1 callersMethodsample_all

sample all the data in ReplayBuffer (for on-policy) :return torch.Tensor reward: reward.shape==(now_len, 1) :return torch.Tensor m

ElegantRL/replay.py:117

↓ 1 callersMethodsample_all

(self)

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/tutorial/agent.py:463

↓ 1 callersMethodsample_all

(self)

ElegantRL/Beta/elegantrl2/tutorial/agent.py:427

↓ 1 callersMethodsample_all

(self)

ElegantRL/AgentZoo/ElegantRL-MultiGPU/tutorial/agent.py:463

↓ 1 callersMethodsample_for_ppo

(self)

ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/agent.py:1075

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve', fig_name='plot_learning_curve.jpg')

ElegantRL/run.py:1096

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve', fig_name='plot_learning_curve.jpg')

ElegantRL/Beta/run.py:1087

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve', fig_name='plot_learning_curve.jpg')

ElegantRL/Beta/elegantrl/run.py:1085

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve')

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/run.py:536

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve', fig_name='plot_learning_curve.jpg')

ElegantRL/Beta/elegantrl2/run.py:758

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve', fig_name='plot_learning_curve.jpg')

ElegantRL/elegantrl2/evaluator.py:122

↓ 1 callersFunctionsave_learning_curve

(recorder, cwd='.', save_title='learning curve')

ElegantRL/AgentZoo/ElegantRL-MultiGPU/run.py:714

↓ 1 callersMethodsave_load_model

save or load model files :str cwd: current working directory, we save model file here :bool if_save: save model or load model

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/agent.py:82

↓ 1 callersMethodsave_load_model

save or load model files :str cwd: current working directory, we save model file here :bool if_save: save model or load model

ElegantRL/AgentZoo/ElegantRL-MultiGPU/agent.py:117

↓ 1 callersMethodsave_npy__draw_plot

(self)

ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/run.py:925

↓ 1 callersMethodsave_npy_draw_plot

(self)

ElegantRL/AgentZoo/ElegantRL-MultiGPU/run.py:679

↓ 1 callersMethodsave_or_load_model

(self, cwd, if_save)

ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/agent.py:209

↓ 1 callersFunctionseed

(m1, m2)

Plan/DEMO-EvArea-cv2-mp-np.py:33

↓ 1 callersMethodselect

(self)

ElegantRL/test.py:120

↓ 1 callersMethodselect

(self)

ElegantRL/Beta/test.py:120

↓ 1 callersMethodselect

(self)

ElegantRL/Beta/elegantrl/test.py:120

↓ 1 callersMethodselect

(self)

ElegantRL/Beta/elegantrl2/test.py:120

↓ 1 callersMethodselect

(self)

ElegantRL/elegantrl2/test.py:120

↓ 1 callersMethodselect1

(self)

ElegantRL/test.py:123

↓ 1 callersMethodselect1

(self)

ElegantRL/Beta/test.py:123

↓ 1 callersMethodselect1

(self)

ElegantRL/Beta/elegantrl/test.py:123

↓ 1 callersMethodselect1

(self)

ElegantRL/Beta/elegantrl2/test.py:123

↓ 1 callersMethodselect1

(self)

ElegantRL/elegantrl2/test.py:123

↓ 1 callersMethodselect_action

Select actions for exploration `array state` state.shape==(state_dim, ) return `array action` action.shape==(action_dim, ), -1 <

ElegantRL/agent.py:52

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/agent.py:528

↓ 1 callersMethodselect_action

Select actions for exploration `array state` state.shape==(state_dim, ) return `array action` action.shape==(action_dim, ), -1 <

ElegantRL/Beta/agent.py:54

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/agent.py:540

↓ 1 callersMethodselect_action

Select actions for exploration `array state` state.shape==(state_dim, ) return `array action` action.shape==(action_dim, ), -1 <

ElegantRL/Beta/elegantrl/agent.py:52

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/agent.py:528

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/tutorial/agent.py:25

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/tutorial/agent.py:59

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/tutorial/agent.py:332

↓ 1 callersMethodselect_action

Select actions for exploration :array state: state.shape==(state_dim, ) :return array action: action.shape==(action_dim, ), (actio

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/agent.py:40

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/agent.py:144

↓ 1 callersMethodselect_action

select action for PPO :array state: state.shape==(state_dim, ) :return array action: state.shape==(action_dim, ) :retur

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/agent.py:768

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/tutorial/agent.py:25

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/tutorial/agent.py:59

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl/2021-04-04 ElegantRL/tutorial/agent.py:332

↓ 1 callersMethodselect_action

Select actions for exploration `array state` state.shape==(state_dim, ) return `array action` action.shape==(action_dim, ), -1 <

ElegantRL/Beta/elegantrl2/agent.py:56

↓ 1 callersMethodselect_action

`array state` state.shape = (state_dim, ) return `array action` action.shape = (action_dim, ) return `array noise` noise.s

ElegantRL/Beta/elegantrl2/agent.py:532

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl2/tutorial/agent.py:35

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/elegantrl2/tutorial/agent.py:266

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/Beta/other/Example_SingleFilePPO.py:89

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/tutorial/agent.py:35

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/tutorial/agent.py:266

↓ 1 callersMethodselect_action

Select actions for exploration `array state` state.shape==(state_dim, ) return `array action` action.shape==(action_dim, ), -1 <

ElegantRL/elegantrl2/agent.py:55

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/elegantrl2/agent.py:303

↓ 1 callersMethodselect_action

`array state` state.shape = (state_dim, ) return `array action` action.shape = (action_dim, ) return `array noise` noise.s

ElegantRL/elegantrl2/agent.py:607

↓ 1 callersMethodselect_action

Select actions for exploration :array state: state.shape==(state_dim, ) :return array action: action.shape==(action_dim, ), (actio

ElegantRL/AgentZoo/ElegantRL-MultiGPU/agent.py:65

↓ 1 callersMethodselect_action

(self, state)

ElegantRL/AgentZoo/ElegantRL-MultiGPU/agent.py:175

↓ 1 callersMethodselect_action

select action for PPO :array state: state.shape==(state_dim, ) :return array action: state.shape==(action_dim, ) :retur

ElegantRL/AgentZoo/ElegantRL-MultiGPU/agent.py:780

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