feat(training): release V0.9.1 避障训练与基础策略迁移

2026-09-08 10:50:13 +08:00
parent fa5485049a
commit 438e56bcc8
113 changed files with 15027 additions and 539 deletions
@@ -0,0 +1,43 @@
+"""Resource-limited CPU single-file decoder; no network or neighboring model lookup."""
+
+import contextlib
+import json
+import os
+import resource
+import sys
+from pathlib import Path
+
+# Apply limits before importing tensor/protobuf runtimes. Thread env also set by parent.
+resource.setrlimit(resource.RLIMIT_CPU, (40, 40))
+resource.setrlimit(resource.RLIMIT_AS, (8 * 1024**3, 8 * 1024**3))
+resource.setrlimit(resource.RLIMIT_FSIZE, (16 * 1024**2, 16 * 1024**2))
+resource.setrlimit(resource.RLIMIT_NOFILE, (64, 64))
+resource.setrlimit(resource.RLIMIT_CORE, (0, 0))
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+ROOT = Path(__file__).resolve().parents[1]
+for root in (ROOT, ROOT.parent):
+    sys.path.insert(0, str(root))
+
+if __name__ == "__main__":
+    try:
+        payload = json.loads(sys.stdin.read(4096))
+        with contextlib.redirect_stdout(sys.stderr):
+            import torch
+            from pretrained_upload import import_upload
+
+            torch.set_num_threads(1)
+            manifest = import_upload(
+                payload["path"], payload["format"], payload["template"], payload["directory"]
+            )
+        print(json.dumps(manifest))
+    except Exception as error:
+        # Do not echo untrusted pickle/tensor names or absolute local paths.
+        from pretrained import PretrainedError
+
+        message = (
+            str(error)
+            if isinstance(error, PretrainedError)
+            else "文件解析失败；请提供受支持的自包含Go2 legacy47 actor"
+        )
+        print(json.dumps({"error": message[:500]}))
+        sys.exit(1)