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app.py
CHANGED
@@ -5,6 +5,7 @@ import os
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import yaml
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from pathlib import Path
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from loguru import logger
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SPACE_REPO = "c-gohlke/litrl"
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SPACE_REPO_TYPE = "space"
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@@ -20,7 +21,22 @@ login( # type: ignore[no-untyped-call]
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new_session=False,
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)
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def get_best_gif(env: str) -> Path:
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hf_env_results_path = f"models/{env}/results.yaml"
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local_env_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_env_results_path)
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with open(local_env_results_path, "r") as f:
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@@ -32,13 +48,11 @@ def get_best_gif(env: str) -> Path:
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model_results = yaml.load(f, Loader=yaml.FullLoader)
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best_model = max(model_results, key=lambda model: model_results[model])
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hf_gif_path = f"models/{env}/{best_model_type}/{best_model}/demo.
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return Path(hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_gif_path))
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def get_environments() -> list[str]:
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environments = []
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files = hf_api.list_repo_files(MODEL_REPO, repo_type=MODEL_REPO_TYPE)
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for file in files:
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vals = file.split("/")
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@@ -47,45 +61,57 @@ def get_environments() -> list[str]:
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environments.append(vals[1])
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return environments
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def get_gif_paths(environments: list[str]) -> dict[str,
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for env in environments:
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return
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def run_demo() -> None:
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environments = get_environments()
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gif_paths = get_gif_paths(environments)
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def api_get_text(env_id: str)->
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logger.info(f"Getting text for {env_id}")
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return
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def api_predict(env_id: str)->
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if env_id not in gif_paths:
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return None
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return gr.
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with gr.Blocks() as demo:
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md = gr.Markdown("# Greetings from LitRL!")
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env = gr.Dropdown(choices=
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button = gr.Button(value="Submit")
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cartpole_out = gr.
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button.click(
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fn=api_get_text,
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inputs=env,
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outputs=md,
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api_name="get_text",
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)
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button.click(
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fn=api_predict,
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inputs=env,
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outputs=cartpole_out,
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api_name="predict",
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)
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if __name__ == "__main__":
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run_demo()
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import yaml
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from pathlib import Path
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from loguru import logger
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from PIL import Image
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SPACE_REPO = "c-gohlke/litrl"
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SPACE_REPO_TYPE = "space"
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new_session=False,
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)
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# def get_best_gif(env: str) -> Path:
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# hf_env_results_path = f"models/{env}/results.yaml"
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# local_env_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_env_results_path)
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# with open(local_env_results_path, "r") as f:
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# env_results = yaml.load(f, Loader=yaml.FullLoader)
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# best_model_type = max(env_results, key=lambda model: env_results[model])
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# model_results_path = f"models/{env}/{best_model_type}/results.yaml"
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# local_model_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=model_results_path)
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# with open(local_model_results_path, "r") as f:
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# model_results = yaml.load(f, Loader=yaml.FullLoader)
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# best_model = max(model_results, key=lambda model: model_results[model])
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# hf_gif_path = f"models/{env}/{best_model_type}/{best_model}/demo.gif"
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# return Path(hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_gif_path))
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def get_best_mp4(env: str) -> Path:
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hf_env_results_path = f"models/{env}/results.yaml"
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local_env_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_env_results_path)
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with open(local_env_results_path, "r") as f:
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model_results = yaml.load(f, Loader=yaml.FullLoader)
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best_model = max(model_results, key=lambda model: model_results[model])
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hf_gif_path = f"models/{env}/{best_model_type}/{best_model}/demo.mp4"
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return Path(hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_gif_path))
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def get_environments() -> list[str]:
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environments: list[str] = []
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files = hf_api.list_repo_files(MODEL_REPO, repo_type=MODEL_REPO_TYPE)
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for file in files:
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vals = file.split("/")
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environments.append(vals[1])
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return environments
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# def get_gif_paths(environments: list[str]) -> dict[str, Path]:
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# gif_paths: dict[str, Path] = {}
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# for env in environments:
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# gif_paths[env] = get_best_gif(env)
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# return gif_paths
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def get_mp4_paths(environments: list[str]) -> dict[str, Path]:
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mp4_paths: dict[str, Path] = {}
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for env in environments:
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mp4_paths[env] = get_best_mp4(env)
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return mp4_paths
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def run_demo() -> None:
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environments = get_environments()
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# gif_paths = get_gif_paths(environments)
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mp4_paths = get_mp4_paths(environments)
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def api_get_text(env_id: str)-> gr.Markdown:
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logger.info(f"Getting text for {env_id}")
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return gr.Markdown("# Greetings from LitRL!")
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def api_predict(env_id: str)-> bytes:
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# if env_id not in gif_paths:
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# logger.error(f"Environment {env_id} not found in {gif_paths}")
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# return None
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# return Image.open(gif_paths[env_id], formats=["gif"])
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if env_id not in mp4_paths:
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logger.error(f"Environment {env_id} not found in {mp4_paths}")
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return None
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return gr.Video(mp4_paths[env_id])
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with gr.Blocks() as demo:
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md = gr.Markdown("# Greetings from LitRL!")
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env = gr.Dropdown(choices=list(mp4_paths.keys()), value="CartPole-v1", label="Environment")
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button = gr.Button(value="Submit")
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cartpole_out = gr.Video(mp4_paths[env.value], autoplay=True)
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button.click( # type: ignore[no-untyped-call]
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fn=api_get_text,
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inputs=env,
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outputs=md,
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api_name="get_text",
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)
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button.click( # type: ignore[no-untyped-call]
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fn=api_predict,
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inputs=env,
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outputs=cartpole_out,
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api_name="predict",
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)
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demo.launch() # type: ignore[no-untyped-call]
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if __name__ == "__main__":
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run_demo()
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