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Upload README.md with huggingface_hub

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  1. README.md +16 -14
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  type: OpenAI/Gym/Box2d-LunarLander-v2
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  metrics:
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  - type: mean_reward
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- value: 246.12 +/- 10.8
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  name: mean_reward
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  ---
27
 
@@ -67,10 +67,10 @@ import torch
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  # Pull model from files which are git cloned from huggingface
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  policy_state_dict = torch.load("pytorch_model.bin", map_location=torch.device("cpu"))
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- cfg = EasyDict(Config.file_to_dict("policy_config.py"))
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  # Instantiate the agent
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  agent = DDPGAgent(
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- env="lunarlander_continuous",
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  exp_name="LunarLander-v2-DDPG",
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  cfg=cfg.exp_config,
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  policy_state_dict=policy_state_dict
@@ -101,7 +101,7 @@ from huggingface_ding import pull_model_from_hub
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  policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/LunarLander-v2-DDPG")
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  # Instantiate the agent
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  agent = DDPGAgent(
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- env="lunarlander_continuous",
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  exp_name="LunarLander-v2-DDPG",
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  cfg=cfg.exp_config,
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  policy_state_dict=policy_state_dict
@@ -131,7 +131,7 @@ from ding.bonus import DDPGAgent
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  from huggingface_ding import push_model_to_hub
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  # Instantiate the agent
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- agent = DDPGAgent("lunarlander_continuous", exp_name="LunarLander-v2-DDPG")
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  # Train the agent
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  return_ = agent.train(step=int(4000000), collector_env_num=4, evaluator_env_num=4)
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  # Push model to huggingface hub
@@ -148,7 +148,8 @@ push_model_to_hub(
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  usage_file_by_git_clone="./ddpg/lunarlander_ddpg_deploy.py",
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  usage_file_by_huggingface_ding="./ddpg/lunarlander_ddpg_download.py",
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  train_file="./ddpg/lunarlander_ddpg.py",
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- repo_id="OpenDILabCommunity/LunarLander-v2-DDPG"
 
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  )
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  ```
@@ -172,11 +173,11 @@ exp_config = {
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  'retry_waiting_time': 0.1,
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  'cfg_type': 'BaseEnvManagerDict'
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  },
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- 'stop_value': 240,
 
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  'env_id': 'LunarLanderContinuous-v2',
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  'collector_env_num': 8,
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  'evaluator_env_num': 8,
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- 'n_evaluator_episode': 8,
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  'act_scale': True
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  },
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  'policy': {
@@ -231,9 +232,10 @@ exp_config = {
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  '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': 240
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  }
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  },
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  'other': {
@@ -281,14 +283,14 @@ exp_config = {
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  - **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/LunarLander-v2-DDPG/blob/main/policy_config.py)
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  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/LunarLander-v2-DDPG/blob/main/replay.mp4)
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  <!-- Provide the size information for the model. -->
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- - **Parameters total size:** 57.52 KB
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- - **Last Update Date:** 2023-04-11
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287
  ## Environments
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  <!-- 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. -->
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  - **Benchmark:** OpenAI/Gym/Box2d
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  - **Task:** LunarLander-v2
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  - **Gym version:** 0.25.1
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- - **DI-engine version:** v0.4.6
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- - **PyTorch version:** 1.7.1
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  - **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/lunarlander.html)
 
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  type: OpenAI/Gym/Box2d-LunarLander-v2
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  metrics:
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  - type: mean_reward
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+ value: 264.9 +/- 18.41
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  name: mean_reward
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  ---
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67
 
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  # Pull model from files which are git cloned from huggingface
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  policy_state_dict = torch.load("pytorch_model.bin", map_location=torch.device("cpu"))
70
+ cfg = EasyDict(Config.file_to_dict("policy_config.py").cfg_dict)
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  # Instantiate the agent
72
  agent = DDPGAgent(
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+ env_id="LunarLanderContinuous-v2",
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  exp_name="LunarLander-v2-DDPG",
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  cfg=cfg.exp_config,
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  policy_state_dict=policy_state_dict
 
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  policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/LunarLander-v2-DDPG")
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  # Instantiate the agent
103
  agent = DDPGAgent(
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+ env_id="LunarLanderContinuous-v2",
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  exp_name="LunarLander-v2-DDPG",
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  cfg=cfg.exp_config,
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  policy_state_dict=policy_state_dict
 
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  from huggingface_ding import push_model_to_hub
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  # Instantiate the agent
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+ agent = DDPGAgent(env_id="LunarLanderContinuous-v2", exp_name="LunarLander-v2-DDPG")
135
  # Train the agent
136
  return_ = agent.train(step=int(4000000), collector_env_num=4, evaluator_env_num=4)
137
  # Push model to huggingface hub
 
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  usage_file_by_git_clone="./ddpg/lunarlander_ddpg_deploy.py",
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  usage_file_by_huggingface_ding="./ddpg/lunarlander_ddpg_download.py",
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  train_file="./ddpg/lunarlander_ddpg.py",
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+ repo_id="OpenDILabCommunity/LunarLander-v2-DDPG",
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+ create_repo=False
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  )
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  ```
 
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  'retry_waiting_time': 0.1,
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  'cfg_type': 'BaseEnvManagerDict'
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  },
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+ 'stop_value': 260,
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+ 'n_evaluator_episode': 8,
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  'env_id': 'LunarLanderContinuous-v2',
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  'collector_env_num': 8,
180
  'evaluator_env_num': 8,
 
181
  'act_scale': True
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  },
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  'policy': {
 
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  'render_freq': -1,
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  'mode': 'train_iter'
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  },
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+ 'figure_path': None,
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  'cfg_type': 'InteractionSerialEvaluatorDict',
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+ 'stop_value': 260,
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+ 'n_episode': 8
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  }
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  },
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  'other': {
 
283
  - **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/LunarLander-v2-DDPG/blob/main/policy_config.py)
284
  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/LunarLander-v2-DDPG/blob/main/replay.mp4)
285
  <!-- Provide the size information for the model. -->
286
+ - **Parameters total size:** 115.03 KB
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+ - **Last Update Date:** 2023-09-22
288
 
289
  ## Environments
290
  <!-- 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. -->
291
  - **Benchmark:** OpenAI/Gym/Box2d
292
  - **Task:** LunarLander-v2
293
  - **Gym version:** 0.25.1
294
+ - **DI-engine version:** v0.4.9
295
+ - **PyTorch version:** 2.0.1+cu117
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  - **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/lunarlander.html)