Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
@@ -21,7 +21,7 @@ model-index:
|
|
21 |
type: OpenAI/Gym/ClassicControl-Pendulum-v1
|
22 |
metrics:
|
23 |
- type: mean_reward
|
24 |
-
value: -
|
25 |
name: mean_reward
|
26 |
---
|
27 |
|
@@ -67,9 +67,9 @@ import torch
|
|
67 |
|
68 |
# Pull model from files which are git cloned from huggingface
|
69 |
policy_state_dict = torch.load("pytorch_model.bin", map_location=torch.device("cpu"))
|
70 |
-
cfg = EasyDict(Config.file_to_dict("policy_config.py"))
|
71 |
# Instantiate the agent
|
72 |
-
agent = DDPGAgent(
|
73 |
# Continue training
|
74 |
agent.train(step=5000)
|
75 |
# Render the new agent performance
|
@@ -95,7 +95,7 @@ from huggingface_ding import pull_model_from_hub
|
|
95 |
# Pull model from Hugggingface hub
|
96 |
policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/Pendulum-v1-DDPG")
|
97 |
# Instantiate the agent
|
98 |
-
agent = DDPGAgent(
|
99 |
# Continue training
|
100 |
agent.train(step=5000)
|
101 |
# Render the new agent performance
|
@@ -121,7 +121,7 @@ from ding.bonus import DDPGAgent
|
|
121 |
from huggingface_ding import push_model_to_hub
|
122 |
|
123 |
# Instantiate the agent
|
124 |
-
agent = DDPGAgent("
|
125 |
# Train the agent
|
126 |
return_ = agent.train(step=int(4000000))
|
127 |
# Push model to huggingface hub
|
@@ -138,7 +138,8 @@ push_model_to_hub(
|
|
138 |
usage_file_by_git_clone="./ddpg/pendulum_ddpg_deploy.py",
|
139 |
usage_file_by_huggingface_ding="./ddpg/pendulum_ddpg_download.py",
|
140 |
train_file="./ddpg/pendulum_ddpg.py",
|
141 |
-
repo_id="OpenDILabCommunity/Pendulum-v1-DDPG"
|
|
|
142 |
)
|
143 |
|
144 |
```
|
@@ -163,10 +164,11 @@ exp_config = {
|
|
163 |
'cfg_type': 'BaseEnvManagerDict'
|
164 |
},
|
165 |
'stop_value': -250,
|
|
|
|
|
166 |
'collector_env_num': 8,
|
167 |
'evaluator_env_num': 5,
|
168 |
-
'act_scale': True
|
169 |
-
'n_evaluator_episode': 5
|
170 |
},
|
171 |
'policy': {
|
172 |
'model': {
|
@@ -215,9 +217,10 @@ exp_config = {
|
|
215 |
'render_freq': -1,
|
216 |
'mode': 'train_iter'
|
217 |
},
|
|
|
218 |
'cfg_type': 'InteractionSerialEvaluatorDict',
|
219 |
-
'
|
220 |
-
'
|
221 |
}
|
222 |
},
|
223 |
'other': {
|
@@ -257,7 +260,7 @@ exp_config = {
|
|
257 |
|
258 |
**Training Procedure**
|
259 |
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
260 |
-
- **Weights & Biases (wandb):** [monitor link](https://wandb.ai/
|
261 |
|
262 |
## Model Information
|
263 |
<!-- Provide the basic links for the model. -->
|
@@ -266,14 +269,14 @@ exp_config = {
|
|
266 |
- **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/Pendulum-v1-DDPG/blob/main/policy_config.py)
|
267 |
- **Demo:** [video](https://huggingface.co/OpenDILabCommunity/Pendulum-v1-DDPG/blob/main/replay.mp4)
|
268 |
<!-- Provide the size information for the model. -->
|
269 |
-
- **Parameters total size:**
|
270 |
-
- **Last Update Date:** 2023-
|
271 |
|
272 |
## Environments
|
273 |
<!-- 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. -->
|
274 |
- **Benchmark:** OpenAI/Gym/ClassicControl
|
275 |
- **Task:** Pendulum-v1
|
276 |
- **Gym version:** 0.25.1
|
277 |
-
- **DI-engine version:** v0.4.
|
278 |
-
- **PyTorch version:**
|
279 |
- **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/pendulum.html)
|
|
|
21 |
type: OpenAI/Gym/ClassicControl-Pendulum-v1
|
22 |
metrics:
|
23 |
- type: mean_reward
|
24 |
+
value: -185.23 +/- 138.05
|
25 |
name: mean_reward
|
26 |
---
|
27 |
|
|
|
67 |
|
68 |
# Pull model from files which are git cloned from huggingface
|
69 |
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)
|
71 |
# Instantiate the agent
|
72 |
+
agent = DDPGAgent(env_id="Pendulum-v1", exp_name="Pendulum-v1-DDPG", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
|
73 |
# Continue training
|
74 |
agent.train(step=5000)
|
75 |
# Render the new agent performance
|
|
|
95 |
# Pull model from Hugggingface hub
|
96 |
policy_state_dict, cfg = pull_model_from_hub(repo_id="OpenDILabCommunity/Pendulum-v1-DDPG")
|
97 |
# Instantiate the agent
|
98 |
+
agent = DDPGAgent(env_id="Pendulum-v1", exp_name="Pendulum-v1-DDPG", cfg=cfg.exp_config, policy_state_dict=policy_state_dict)
|
99 |
# Continue training
|
100 |
agent.train(step=5000)
|
101 |
# Render the new agent performance
|
|
|
121 |
from huggingface_ding import push_model_to_hub
|
122 |
|
123 |
# Instantiate the agent
|
124 |
+
agent = DDPGAgent(env_id="Pendulum-v1", exp_name="Pendulum-v1-DDPG")
|
125 |
# Train the agent
|
126 |
return_ = agent.train(step=int(4000000))
|
127 |
# Push model to huggingface hub
|
|
|
138 |
usage_file_by_git_clone="./ddpg/pendulum_ddpg_deploy.py",
|
139 |
usage_file_by_huggingface_ding="./ddpg/pendulum_ddpg_download.py",
|
140 |
train_file="./ddpg/pendulum_ddpg.py",
|
141 |
+
repo_id="OpenDILabCommunity/Pendulum-v1-DDPG",
|
142 |
+
create_repo=False
|
143 |
)
|
144 |
|
145 |
```
|
|
|
164 |
'cfg_type': 'BaseEnvManagerDict'
|
165 |
},
|
166 |
'stop_value': -250,
|
167 |
+
'n_evaluator_episode': 5,
|
168 |
+
'env_id': 'Pendulum-v1',
|
169 |
'collector_env_num': 8,
|
170 |
'evaluator_env_num': 5,
|
171 |
+
'act_scale': True
|
|
|
172 |
},
|
173 |
'policy': {
|
174 |
'model': {
|
|
|
217 |
'render_freq': -1,
|
218 |
'mode': 'train_iter'
|
219 |
},
|
220 |
+
'figure_path': None,
|
221 |
'cfg_type': 'InteractionSerialEvaluatorDict',
|
222 |
+
'stop_value': -250,
|
223 |
+
'n_episode': 5
|
224 |
}
|
225 |
},
|
226 |
'other': {
|
|
|
260 |
|
261 |
**Training Procedure**
|
262 |
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
263 |
+
- **Weights & Biases (wandb):** [monitor link](https://wandb.ai/zjowowen/Pendulum-v1-DDPG)
|
264 |
|
265 |
## Model Information
|
266 |
<!-- Provide the basic links for the model. -->
|
|
|
269 |
- **Configuration:** [config link](https://huggingface.co/OpenDILabCommunity/Pendulum-v1-DDPG/blob/main/policy_config.py)
|
270 |
- **Demo:** [video](https://huggingface.co/OpenDILabCommunity/Pendulum-v1-DDPG/blob/main/replay.mp4)
|
271 |
<!-- Provide the size information for the model. -->
|
272 |
+
- **Parameters total size:** 70.52 KB
|
273 |
+
- **Last Update Date:** 2023-09-22
|
274 |
|
275 |
## Environments
|
276 |
<!-- 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. -->
|
277 |
- **Benchmark:** OpenAI/Gym/ClassicControl
|
278 |
- **Task:** Pendulum-v1
|
279 |
- **Gym version:** 0.25.1
|
280 |
+
- **DI-engine version:** v0.4.9
|
281 |
+
- **PyTorch version:** 2.0.1+cu117
|
282 |
- **Doc**: [DI-engine-docs Environments link](https://di-engine-docs.readthedocs.io/en/latest/13_envs/pendulum.html)
|