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Upload README.md with huggingface_hub

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  1. README.md +18 -13
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  type: OpenAI/Gym/MuJoCo-Hopper-v3
22
  metrics:
23
  - type: mean_reward
24
- value: 3903.22 +/- 1.71
25
  name: mean_reward
26
  ---
27
 
@@ -53,6 +53,7 @@ wget https://mujoco.org/download/mujoco210-linux-x86_64.tar.gz -O mujoco.tar.gz
53
  tar -xf mujoco.tar.gz -C ~/.mujoco
54
  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin" >> ~/.bashrc
55
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin
 
56
  pip3 install DI-engine[common_env]
57
 
58
  ```
@@ -76,9 +77,9 @@ import torch
76
 
77
  # Pull model from files which are git cloned from huggingface
78
  policy_state_dict = torch.load("pytorch_model.bin", map_location=torch.device("cpu"))
79
- cfg = EasyDict(Config.file_to_dict("policy_config.py"))
80
  # Instantiate the agent
81
- agent = SACAgent(env="hopper", exp_name="Hopper-v3-TD3", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
82
  # Continue training
83
  agent.train(step=5000)
84
  # Render the new agent performance
@@ -104,7 +105,7 @@ from huggingface_ding import pull_model_from_hub
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  # Pull model from Hugggingface hub
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  policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/Hopper-v3-TD3")
106
  # Instantiate the agent
107
- agent = TD3Agent(env="hopper", exp_name="Hopper-v3-TD3", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
108
  # Continue training
109
  agent.train(step=5000)
110
  # Render the new agent performance
@@ -130,7 +131,7 @@ from ding.bonus import TD3Agent
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  from huggingface_ding import push_model_to_hub
131
 
132
  # Instantiate the agent
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- agent = TD3Agent(env="hopper", exp_name="Hopper-v3-TD3")
134
  # Train the agent
135
  return_ = agent.train(step=int(10000000), collector_env_num=4, evaluator_env_num=4, debug=False)
136
  # Push model to huggingface hub
@@ -164,12 +165,14 @@ wget https://mujoco.org/download/mujoco210-linux-x86_64.tar.gz -O mujoco.tar.gz
164
  tar -xf mujoco.tar.gz -C ~/.mujoco
165
  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin" >> ~/.bashrc
166
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin
 
167
  pip3 install DI-engine[common_env]
168
  ''',
169
  usage_file_by_git_clone="./td3/hopper_td3_deploy.py",
170
  usage_file_by_huggingface_ding="./td3/hopper_td3_download.py",
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  train_file="./td3/hopper_td3.py",
172
- repo_id="OpenDILabCommunity/Hopper-v3-TD3"
 
173
  )
174
 
175
  ```
@@ -194,10 +197,11 @@ exp_config = {
194
  'cfg_type': 'BaseEnvManagerDict'
195
  },
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  'stop_value': 6000,
 
197
  'env_id': 'Hopper-v3',
198
  'collector_env_num': 8,
199
  'evaluator_env_num': 8,
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- 'n_evaluator_episode': 8
201
  },
202
  'policy': {
203
  'model': {
@@ -251,9 +255,10 @@ exp_config = {
251
  'render_freq': -1,
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  'mode': 'train_iter'
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  },
 
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  'cfg_type': 'InteractionSerialEvaluatorDict',
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- 'n_episode': 8,
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- 'stop_value': 6000
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  }
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  },
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  'other': {
@@ -301,14 +306,14 @@ exp_config = {
301
  - **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/Hopper-v3-TD3/blob/main/policy_config.py)
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  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/Hopper-v3-TD3/blob/main/replay.mp4)
303
  <!-- Provide the size information for the model. -->
304
- - **Parameters total size:** 818.02 KB
305
- - **Last Update Date:** 2023-04-14
306
 
307
  ## Environments
308
  <!-- Address questions around what environment the model is intended to be trained and deployed at, including the necessary information needed to be provided for future users. -->
309
  - **Benchmark:** OpenAI/Gym/MuJoCo
310
  - **Task:** Hopper-v3
311
  - **Gym version:** 0.25.1
312
- - **DI-engine version:** v0.4.7
313
- - **PyTorch version:** 1.7.1
314
  - **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/mujoco.html)
 
21
  type: OpenAI/Gym/MuJoCo-Hopper-v3
22
  metrics:
23
  - type: mean_reward
24
+ value: 3671.44 +/- 201.96
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  name: mean_reward
26
  ---
27
 
 
53
  tar -xf mujoco.tar.gz -C ~/.mujoco
54
  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin" >> ~/.bashrc
55
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin
56
+ pip3 install "cython<3"
57
  pip3 install DI-engine[common_env]
58
 
59
  ```
 
77
 
78
  # Pull model from files which are git cloned from huggingface
79
  policy_state_dict = torch.load("pytorch_model.bin", map_location=torch.device("cpu"))
80
+ cfg = EasyDict(Config.file_to_dict("policy_config.py").cfg_dict)
81
  # Instantiate the agent
82
+ agent = SACAgent(env_id="Hopper-v3", exp_name="Hopper-v3-TD3", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
83
  # Continue training
84
  agent.train(step=5000)
85
  # Render the new agent performance
 
105
  # Pull model from Hugggingface hub
106
  policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/Hopper-v3-TD3")
107
  # Instantiate the agent
108
+ agent = TD3Agent(env_id="Hopper-v3", exp_name="Hopper-v3-TD3", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
109
  # Continue training
110
  agent.train(step=5000)
111
  # Render the new agent performance
 
131
  from huggingface_ding import push_model_to_hub
132
 
133
  # Instantiate the agent
134
+ agent = TD3Agent(env_id="Hopper-v3", exp_name="Hopper-v3-TD3")
135
  # Train the agent
136
  return_ = agent.train(step=int(10000000), collector_env_num=4, evaluator_env_num=4, debug=False)
137
  # Push model to huggingface hub
 
165
  tar -xf mujoco.tar.gz -C ~/.mujoco
166
  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin" >> ~/.bashrc
167
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mjpro210/bin:~/.mujoco/mujoco210/bin
168
+ pip3 install "cython<3"
169
  pip3 install DI-engine[common_env]
170
  ''',
171
  usage_file_by_git_clone="./td3/hopper_td3_deploy.py",
172
  usage_file_by_huggingface_ding="./td3/hopper_td3_download.py",
173
  train_file="./td3/hopper_td3.py",
174
+ repo_id="OpenDILabCommunity/Hopper-v3-TD3",
175
+ create_repo=False
176
  )
177
 
178
  ```
 
197
  'cfg_type': 'BaseEnvManagerDict'
198
  },
199
  'stop_value': 6000,
200
+ 'n_evaluator_episode': 8,
201
  'env_id': 'Hopper-v3',
202
  'collector_env_num': 8,
203
  'evaluator_env_num': 8,
204
+ 'env_wrapper': 'mujoco_default'
205
  },
206
  'policy': {
207
  'model': {
 
255
  'render_freq': -1,
256
  'mode': 'train_iter'
257
  },
258
+ 'figure_path': None,
259
  'cfg_type': 'InteractionSerialEvaluatorDict',
260
+ 'stop_value': 6000,
261
+ 'n_episode': 8
262
  }
263
  },
264
  'other': {
 
306
  - **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/Hopper-v3-TD3/blob/main/policy_config.py)
307
  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/Hopper-v3-TD3/blob/main/replay.mp4)
308
  <!-- Provide the size information for the model. -->
309
+ - **Parameters total size:** 1636.04 KB
310
+ - **Last Update Date:** 2023-09-21
311
 
312
  ## Environments
313
  <!-- Address questions around what environment the model is intended to be trained and deployed at, including the necessary information needed to be provided for future users. -->
314
  - **Benchmark:** OpenAI/Gym/MuJoCo
315
  - **Task:** Hopper-v3
316
  - **Gym version:** 0.25.1
317
+ - **DI-engine version:** v0.4.9
318
+ - **PyTorch version:** 2.0.1+cu117
319
  - **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/mujoco.html)