sgoodfriend
commited on
Commit
•
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Parent(s):
be9c115
PPO playing PongNoFrameskip-v4 from https://github.com/sgoodfriend/rl-algo-impls/tree/e47a44c4d891f48885af0b1605b30d19fc67b5af
Browse files- README.md +7 -7
- compare_runs.py +11 -7
- huggingface_publish.py +8 -7
- replay.meta.json +1 -1
- replay.mp4 +0 -0
README.md
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@@ -1,7 +1,7 @@
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---
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library_name: rl-algo-impls
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tags:
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-
-
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name:
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type:
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---
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# **PPO** Agent playing **
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This is a trained model of a **PPO** agent playing **
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All models trained at this commit can be found at https://api.wandb.ai/links/sgoodfriend/v4wd7cp5.
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@@ -32,7 +32,7 @@ This model was trained from 3 trainings of **PPO** agents using different initia
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| algo | env | seed | reward_mean | reward_std | eval_episodes | best | wandb_url |
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|:-------|:-------------------|-------:|--------------:|-------------:|----------------:|:-------|:-----------------------------------------------------------------------------|
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| ppo | PongNoFrameskip-v4 | 1 | 21 | 0 | 16 | * | [wandb](https://wandb.ai/sgoodfriend/rl-algo-impls-benchmarks/runs/2bvab97i) |
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| ppo | PongNoFrameskip-v4 | 2 | 20.875 | 0.
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| ppo | PongNoFrameskip-v4 | 3 | 21 | 0 | 16 | | [wandb](https://wandb.ai/sgoodfriend/rl-algo-impls-benchmarks/runs/197tllk4) |
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training is deterministic, different hardware will give different results.
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```
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python train.py --algo ppo --env
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```
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Setup hasn't been completely worked out yet, so you might be best served by using Google
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---
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library_name: rl-algo-impls
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tags:
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+
- PongNoFrameskip-v4
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: PongNoFrameskip-v4
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type: PongNoFrameskip-v4
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---
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# **PPO** Agent playing **PongNoFrameskip-v4**
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This is a trained model of a **PPO** agent playing **PongNoFrameskip-v4** using the [/sgoodfriend/rl-algo-impls](https://github.com/sgoodfriend/rl-algo-impls) repo.
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All models trained at this commit can be found at https://api.wandb.ai/links/sgoodfriend/v4wd7cp5.
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| algo | env | seed | reward_mean | reward_std | eval_episodes | best | wandb_url |
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|:-------|:-------------------|-------:|--------------:|-------------:|----------------:|:-------|:-----------------------------------------------------------------------------|
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| ppo | PongNoFrameskip-v4 | 1 | 21 | 0 | 16 | * | [wandb](https://wandb.ai/sgoodfriend/rl-algo-impls-benchmarks/runs/2bvab97i) |
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| ppo | PongNoFrameskip-v4 | 2 | 20.875 | 0.330719 | 16 | | [wandb](https://wandb.ai/sgoodfriend/rl-algo-impls-benchmarks/runs/hjag7zwi) |
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| ppo | PongNoFrameskip-v4 | 3 | 21 | 0 | 16 | | [wandb](https://wandb.ai/sgoodfriend/rl-algo-impls-benchmarks/runs/197tllk4) |
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training is deterministic, different hardware will give different results.
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```
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python train.py --algo ppo --env PongNoFrameskip-v4 --seed 1
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```
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Setup hasn't been completely worked out yet, so you might be best served by using Google
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compare_runs.py
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@@ -143,16 +143,16 @@ if __name__ == "__main__":
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help="WandB tag for experiment commit (i.e. benchmark_5540e1f)",
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)
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parser.add_argument(
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-
"--
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type=str,
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nargs="*",
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help="Environments to exclude from comparison",
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)
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# parser.set_defaults(
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# wandb_hostname_tag=["
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# wandb_control_tag=["
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# wandb_experiment_tag=["
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# exclude_envs=[
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# )
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args = parser.parse_args()
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print(args)
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runs_by_run_group: Dict[RunGroup, RunGroupRuns] = {}
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wandb_hostname_tags = set(args.wandb_hostname_tag)
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for r in all_runs:
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wandb_tags = set(r.config.get("wandb_tags", []))
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if not wandb_tags or not wandb_hostname_tags & wandb_tags:
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continue
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rg = RunGroup(r.config["algo"], r.config["env"])
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if args.exclude_envs and rg.env_id in args.exclude_envs:
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continue
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if rg not in runs_by_run_group:
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runs_by_run_group[rg] = RunGroupRuns(
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rg,
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)
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runs_by_run_group[rg].add_run(r)
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df = RunGroupRuns.data_frame(runs_by_run_group.values()).round(decimals=2)
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help="WandB tag for experiment commit (i.e. benchmark_5540e1f)",
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)
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parser.add_argument(
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"--exclude-envs",
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type=str,
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nargs="*",
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help="Environments to exclude from comparison",
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)
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# parser.set_defaults(
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# wandb_hostname_tag=["host_150-230-44-105", "host_155-248-214-128"],
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# wandb_control_tag=["benchmark_fbc943f"],
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# wandb_experiment_tag=["benchmark_f59bf74"],
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# exclude_envs=[],
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# )
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args = parser.parse_args()
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print(args)
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runs_by_run_group: Dict[RunGroup, RunGroupRuns] = {}
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wandb_hostname_tags = set(args.wandb_hostname_tag)
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for r in all_runs:
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if r.state != "finished":
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continue
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wandb_tags = set(r.config.get("wandb_tags", []))
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if not wandb_tags or not wandb_hostname_tags & wandb_tags:
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continue
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rg = RunGroup(r.config["algo"], r.config.get("env_id") or r.config["env"])
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if args.exclude_envs and rg.env_id in args.exclude_envs:
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continue
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if rg not in runs_by_run_group:
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runs_by_run_group[rg] = RunGroupRuns(
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rg,
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args.wandb_control_tag,
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args.wandb_experiment_tag,
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)
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runs_by_run_group[rg].add_run(r)
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df = RunGroupRuns.data_frame(runs_by_run_group.values()).round(decimals=2)
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huggingface_publish.py
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@@ -38,12 +38,12 @@ def publish(
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api = wandb.Api()
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runs = [api.run(rp) for rp in wandb_run_paths]
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algo = runs[0].config["algo"]
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-
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evaluations = [
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evaluate_model(
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EvalArgs(
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algo,
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-
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seed=r.config.get("seed", None),
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render=False,
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best=True,
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github_url = "https://github.com/sgoodfriend/rl-algo-impls"
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commit_hash = run_metadata.get("git", {}).get("commit", None)
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card_text = model_card_text(
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algo,
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github_url,
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commit_hash,
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wandb_report_url,
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metadata = {
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"library_name": "rl-algo-impls",
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"tags": [
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-
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algo,
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"deep-reinforcement-learning",
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"reinforcement-learning",
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"name": "reinforcement-learning",
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},
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"dataset": {
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"name":
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"type":
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},
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}
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],
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repo_id=huggingface_repo,
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folder_path=repo_dir_path,
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path_in_repo="",
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commit_message=f"{algo.upper()} playing {
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token=huggingface_token,
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)
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print(f"Pushed model to the hub: {repo_url}")
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api = wandb.Api()
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runs = [api.run(rp) for rp in wandb_run_paths]
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algo = runs[0].config["algo"]
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hyperparam_id = runs[0].config["env"]
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evaluations = [
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evaluate_model(
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EvalArgs(
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algo,
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hyperparam_id,
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seed=r.config.get("seed", None),
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render=False,
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best=True,
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github_url = "https://github.com/sgoodfriend/rl-algo-impls"
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commit_hash = run_metadata.get("git", {}).get("commit", None)
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env_id = runs[0].config.get("env_id") or runs[0].config["env"]
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card_text = model_card_text(
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algo,
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env_id,
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github_url,
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commit_hash,
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wandb_report_url,
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metadata = {
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"library_name": "rl-algo-impls",
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"tags": [
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env_id,
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algo,
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"deep-reinforcement-learning",
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"reinforcement-learning",
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"name": "reinforcement-learning",
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},
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"dataset": {
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"name": env_id,
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"type": env_id,
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},
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}
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],
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repo_id=huggingface_repo,
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folder_path=repo_dir_path,
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path_in_repo="",
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commit_message=f"{algo.upper()} playing {env_id} from {github_url}/tree/{commit_hash}",
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token=huggingface_token,
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)
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print(f"Pushed model to the hub: {repo_url}")
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replay.meta.json
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{"content_type": "video/mp4", "encoder_version": {"backend": "ffmpeg", "version": "b'ffmpeg version 5.1.2 Copyright (c) 2000-2022 the FFmpeg developers\\nbuilt with clang version 14.0.6\\nconfiguration: --prefix=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_pl --cc=arm64-apple-darwin20.0.0-clang --cxx=arm64-apple-darwin20.0.0-clang++ --nm=arm64-apple-darwin20.0.0-nm --ar=arm64-apple-darwin20.0.0-ar --disable-doc --disable-openssl --enable-demuxer=dash --enable-hardcoded-tables --enable-libfreetype --enable-libfontconfig --enable-libopenh264 --enable-cross-compile --arch=arm64 --target-os=darwin --cross-prefix=arm64-apple-darwin20.0.0- --host-cc=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_build_env/bin/x86_64-apple-darwin13.4.0-clang --enable-neon --enable-gnutls --enable-libmp3lame --enable-libvpx --enable-pthreads --enable-gpl --enable-libx264 --enable-libx265 --enable-libaom --enable-libsvtav1 --enable-libxml2 --enable-pic --enable-shared --disable-static --enable-version3 --enable-zlib --pkg-config=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_build_env/bin/pkg-config\\nlibavutil 57. 28.100 / 57. 28.100\\nlibavcodec 59. 37.100 / 59. 37.100\\nlibavformat 59. 27.100 / 59. 27.100\\nlibavdevice 59. 7.100 / 59. 7.100\\nlibavfilter 8. 44.100 / 8. 44.100\\nlibswscale 6. 7.100 / 6. 7.100\\nlibswresample 4. 7.100 / 4. 7.100\\nlibpostproc 56. 6.100 / 56. 6.100\\n'", "cmdline": ["ffmpeg", "-nostats", "-loglevel", "error", "-y", "-f", "rawvideo", "-s:v", "160x210", "-pix_fmt", "rgb24", "-framerate", "30", "-i", "-", "-vf", "scale=trunc(iw/2)*2:trunc(ih/2)*2", "-vcodec", "libx264", "-pix_fmt", "yuv420p", "-r", "30", "/var/folders/9g/my5557_91xddp6lx00nkzly80000gn/T/
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+
{"content_type": "video/mp4", "encoder_version": {"backend": "ffmpeg", "version": "b'ffmpeg version 5.1.2 Copyright (c) 2000-2022 the FFmpeg developers\\nbuilt with clang version 14.0.6\\nconfiguration: --prefix=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_pl --cc=arm64-apple-darwin20.0.0-clang --cxx=arm64-apple-darwin20.0.0-clang++ --nm=arm64-apple-darwin20.0.0-nm --ar=arm64-apple-darwin20.0.0-ar --disable-doc --disable-openssl --enable-demuxer=dash --enable-hardcoded-tables --enable-libfreetype --enable-libfontconfig --enable-libopenh264 --enable-cross-compile --arch=arm64 --target-os=darwin --cross-prefix=arm64-apple-darwin20.0.0- --host-cc=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_build_env/bin/x86_64-apple-darwin13.4.0-clang --enable-neon --enable-gnutls --enable-libmp3lame --enable-libvpx --enable-pthreads --enable-gpl --enable-libx264 --enable-libx265 --enable-libaom --enable-libsvtav1 --enable-libxml2 --enable-pic --enable-shared --disable-static --enable-version3 --enable-zlib --pkg-config=/Users/runner/miniforge3/conda-bld/ffmpeg_1671040513231/_build_env/bin/pkg-config\\nlibavutil 57. 28.100 / 57. 28.100\\nlibavcodec 59. 37.100 / 59. 37.100\\nlibavformat 59. 27.100 / 59. 27.100\\nlibavdevice 59. 7.100 / 59. 7.100\\nlibavfilter 8. 44.100 / 8. 44.100\\nlibswscale 6. 7.100 / 6. 7.100\\nlibswresample 4. 7.100 / 4. 7.100\\nlibpostproc 56. 6.100 / 56. 6.100\\n'", "cmdline": ["ffmpeg", "-nostats", "-loglevel", "error", "-y", "-f", "rawvideo", "-s:v", "160x210", "-pix_fmt", "rgb24", "-framerate", "30", "-i", "-", "-vf", "scale=trunc(iw/2)*2:trunc(ih/2)*2", "-vcodec", "libx264", "-pix_fmt", "yuv420p", "-r", "30", "/var/folders/9g/my5557_91xddp6lx00nkzly80000gn/T/tmpy4msmta0/ppo-impala-PongNoFrameskip-v4/replay.mp4"]}, "episode": {"r": 21.0, "l": 8220, "t": 30.25069}}
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replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
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