Upload policy_checkpoints/NutAssemblySquare/v0/wandb/run-20241111_213035-kyr0wjsm/files/code/train.py with huggingface_hub

policy_checkpoints/NutAssemblySquare/v0/wandb/run-20241111_213035-kyr0wjsm/files/code/train.py

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+import sys
+# use line-buffering for both stdout and stderr
+sys.stdout = open(sys.stdout.fileno(), mode='w', buffering=1)
+sys.stderr = open(sys.stderr.fileno(), mode='w', buffering=1)
+
+import hydra
+import pathlib
+
+from omegaconf import OmegaConf
+
+from adaflow.workspace.base_workspace import BaseWorkspace
+
+# allows arbitrary python code execution in configs using the ${eval:''} resolver
+OmegaConf.register_new_resolver("eval", eval, replace=True)
+
+@hydra.main(
+    version_base=None,
+    config_path=str(pathlib.Path(__file__).parent.joinpath(
+        'adaflow','config'))
+)
+def main(cfg: OmegaConf):
+    # resolve immediately so all the ${now:} resolvers
+    # will use the same time.
+    # save dict as json
+    OmegaConf.resolve(cfg)
+    cls = hydra.utils.get_class(cfg._target_)
+    if cfg.training.resume_dir is not None: 
+        workspace: BaseWorkspace = cls(cfg, output_dir=cfg.training.resume_dir)
+    else: 
+        workspace: BaseWorkspace = cls(cfg)
+    
+    workspace.run()
+
+if __name__ == "__main__":
+    main()