{ "artifacts": [], "command": "my_main", "experiment": { "base_dir": "E:\\Ium\\ium_487197", "dependencies": [ "keras==2.12.0", "numpy==1.23.5", "pandas==1.5.3", "sacred==0.8.4", "scikit-learn==1.2.2", "tensorflow-intel==2.12.0" ], "mainfile": "ium_sacred.py", "name": "s487197-train", "repositories": [], "sources": [ [ "ium_sacred.py", "_sources\\ium_sacred_823e254d1aa3fd8c744516bf9f9eba26.py" ] ] }, "fail_trace": [ "Traceback (most recent call last):\n", " File \"C:\\Users\\JaSzw\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\wrapt\\wrappers.py\", line 578, in __call__\n return self._self_wrapper(self.__wrapped__, self._self_instance,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\JaSzw\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sacred\\config\\captured_function.py\", line 42, in captured_function\n result = wrapped(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"E:\\Ium\\ium_487197\\ium_sacred.py\", line 80, in my_main\n print(his['loss'])\n ~~~^^^^^^^^\n", "TypeError: tuple indices must be integers or slices, not str\n" ], "heartbeat": "2023-05-12T01:59:35.227619", "host": { "ENV": {}, "cpu": "AMD Ryzen 9 5900HX with Radeon Graphics", "gpus": { "driver_version": "512.74", "gpus": [ { "model": "NVIDIA GeForce RTX 3080 Laptop GPU", "persistence_mode": false, "total_memory": 8192 } ] }, "hostname": "AcerNitro5WL", "os": [ "Windows", "Windows-10-10.0.22621-SP0" ], "python_version": "3.11.2" }, "meta": { "command": "my_main", "named_configs": [], "options": { "--beat-interval": null, "--capture": null, "--comment": null, "--debug": false, "--enforce_clean": false, "--file_storage": null, "--force": false, "--help": false, "--id": null, "--loglevel": null, "--mongo_db": null, "--name": null, "--pdb": false, "--print-config": false, "--priority": null, "--queue": false, "--s3": null, "--sql": null, "--tiny_db": null, "--unobserved": false } }, "resources": [], "result": null, "start_time": "2023-05-12T01:59:29.000086", "status": "FAILED", "stop_time": "2023-05-12T01:59:35.726077" }