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\r\n[?2004l\r# Log the sbatch script\r\ncat $0\r\n\r\nmodule unload mpi/openmpi/5.0\r\nmodule unload devel/cuda/12.4\r\nsource .venv_jafar/bin/activate\r\n\r\nws_dir='/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/'\r\ntf_records_dir=$ws_dir/data/knoms_tfrecords_200_shards\r\n\r\njob_name=$SLURM_JOB_NAME\r\nslurm_job_id=$SLURM_JOB_ID\r\n\r\ntags=("overfit_sample", "tokenizer", "debug", "alfred")\r\n\r\nCHECKPOINT_DIR=$ws_dir/checkpoints/$job_name_$slurm_job_id\r\nmkdir -p $CHECKPOINT_DIR\r\n\r\nenv | grep SLURM\r\n\r\npython train_tokenizer_single_sample.py \\r\n --ckpt_dir $CHECKPOINT_DIR \\r\n --batch_size=1 \\r\n --min_lr=4.3e-5 \\r\n --max_lr=4.3e-4 \\r\n --log_image_interval=10 \\r\n --log \\r\n --entity instant-uv \\r\n --project jafar \\r\n --name $job_name \\r\n --tags $tags \\r\n --model_dim 256 \\r\n --num_heads 4 \\r\n --data_dir $tf_records_dir\r\n
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SLURM_STEP_NUM_TASKS=1\r\nSLURM_JOB_USER=tum_ind3695\r\nSLURM_TASKS_PER_NODE=1\r\nSLURM_JOB_UID=991285\r\nSLURM_TASK_PID=707800\r\nSLURM_JOB_GPUS=3\r\nSLURM_LOCALID=0\r\nSLURM_SUBMIT_DIR=/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar_run_overfit\r\nSLURMD_NODENAME=hkn0505\r\nSLURM_JOB_START_TIME=1751037996\r\nSLURM_STEP_NODELIST=hkn0505\r\nSLURM_CLUSTER_NAME=hk\r\nSLURM_JOB_END_TIME=1751039796\r\nSLURM_PMI2_SRUN_PORT=39147\r\nSLURM_CPUS_ON_NODE=8\r\nSLURM_JOB_CPUS_PER_NODE=8\r\nSLURM_GPUS_ON_NODE=1\r\nSLURM_GTIDS=0\r\nSLURM_JOB_PARTITION=accelerated\r\nSLURM_TRES_PER_TASK=cpu=8\r\nSLURM_OOM_KILL_STEP=0\r\nSLURM_JOB_NUM_NODES=1\r\nSLURM_STEPID=4294967290\r\nSLURM_JOBID=3299579\r\nSLURM_PTY_PORT=34619\r\nSLURM_JOB_QOS=normal\r\nSLURM_LAUNCH_NODE_IPADDR=10.0.7.201\r\nSLURM_PTY_WIN_ROW=68\r\nSLURM_PMI2_PROC_MAPPING=(vector,(0,1,1))\r\nSLURMD_DEBUG=2\r\nSLURM_PROCID=0\r\nSLURM_CPUS_PER_TASK=8\r\nSLURM_NTASKS=1\r\nSLURM_TOPOLOGY_ADDR=hkibb.hkibbi1.hkibbi1e10.hkn0505\r\nSLURM_TOPOLOGY_ADDR_PATTERN=switch.switch.switch.node\r\nSLURM_SRUN_COMM_HOST=10.0.7.201\r\nSLURM_SCRIPT_CONTEXT=prolog_task\r\nSLURM_PTY_WIN_COL=175\r\nSLURM_NODELIST=hkn0505\r\nSLURM_SRUN_COMM_PORT=41999\r\nSLURM_STEP_ID=4294967290\r\nSLURM_JOB_ACCOUNT=hk-project-p0023960\r\nSLURM_PRIO_PROCESS=0\r\nSLURM_NPROCS=1\r\nSLURM_NNODES=1\r\nSLURM_SUBMIT_HOST=hkn1993.localdomain\r\nSLURM_JOB_ID=3299579\r\nSLURM_NODEID=0\r\nSLURM_STEP_NUM_NODES=1\r\nSLURM_STEP_TASKS_PER_NODE=1\r\nSLURM_MPI_TYPE=pmi2\r\nSLURM_PMI2_STEP_NODES=hkn0505\r\nSLURM_CONF=/etc/slurm/slurm.conf\r\nSLURM_JOB_NAME=interactive\r\nSLURM_NTASKS_PER_NODE=1\r\nSLURM_STEP_LAUNCHER_PORT=41999\r\nSLURM_JOB_GID=502289\r\nSLURM_JOB_NODELIST=hkn0505\r\n
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2025-06-27 17:32:32.410771: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\r\nWARNING: All log messages before absl::InitializeLog() is called are written to STDERR\r\nE0000 00:00:1751038352.423499 710438 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\r\nE0000 00:00:1751038352.427576 710438 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\r\nW0000 00:00:1751038352.439609 710438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\r\nW0000 00:00:1751038352.439631 710438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\r\nW0000 00:00:1751038352.439633 710438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\r\nW0000 00:00:1751038352.439635 710438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\r\n
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W0000 00:00:1751038356.161548 710438 gpu_device.cc:2341] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\r\nSkipping registering GPU devices...\r\n
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Running on 1 devices.\r\n
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wandb: Currently logged in as: avocadoali (instant-uv) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin\r\n
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wandb: Tracking run with wandb version 0.19.11\r\nwandb: Run data is saved locally in /hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar_run_overfit/wandb/run-20250627_173237-7qr0fzyr\r\nwandb: Run `wandb offline` to turn off syncing.\r\nwandb: Syncing run interactive\r\nwandb: ⭐️ View project at https://wandb.ai/instant-uv/jafar\r\nwandb: 🚀 View run at https://wandb.ai/instant-uv/jafar/runs/7qr0fzyr\r\n
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2025-06-27 17:32:39.124222: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n
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2025-06-27 17:32:50.748109: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n
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2025-06-27 17:32:52.829743: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n
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Counting all components: ['encoder', 'vq', 'decoder']\r\nParameter counts:\r\n{'encoder': 4770688, 'vq': 32768, 'decoder': 4770672, 'total': 9574128}\r\n
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Starting training from step 0...\r\nbatch shape: (1, 16, 90, 160, 3)\r\n
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2025-06-27 17:33:08.064139: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n2025-06-27 17:33:08.064567: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n2025-06-27 17:33:08.064588: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n2025-06-27 17:33:08.064681: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n2025-06-27 17:33:08.066182: W external/xla/xla/service/gpu/autotuning/dot_search_space.cc:200] All configs were filtered out because none of them sufficiently match the hints. Maybe the hints set does not contain a good representative set of valid configs?Working around this by using the full hints set instead.\r\n
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^C2025-06-27 17:33:16.399639: F external/xla/xla/service/gpu/autotuning/gemm_fusion_autotuner.cc:1136] Non-OK-status: executable.status()\r\nStatus: INTERNAL: ptxas exited with non-zero error code 2, output: - Failure occured when compiling fusion gemm_fusion_dot.228 with config '{block_m:64,block_n:128,block_k:16,split_k:1,num_stages:4,num_warps:2,num_ctas:1}'\r\nFused HLO computation:\r\n%gemm_fusion_dot.228_computation (parameter_0.159: f32[1,16,920,256], parameter_1.159: f32[256,256]) -> f32[1,16,920,256] {\r\n %parameter_0.159 = f32[1,16,920,256]{3,2,1,0} parameter(0)\r\n %bitcast.16502 = f32[14720,256]{1,0} bitcast(%parameter_0.159), metadata={op_name="jit(train_step)/jit(main)/transpose(jvp(TokenizerVQVAE))/decoder/checkpoint/STBlock_7/add_any" source_file="/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar_run_overfit/utils/nn.py" source_line=64}\r\n %parameter_1.159 = f32[256,256]{1,0} parameter(1)\r\n %dot.1723 = f32[14720,256]{1,0} dot(%bitcast.16502, %parameter_1.159), lhs_contracting_dims={1}, rhs_contracting_dims={1}, metadata={op_name="jit(train_step)/jit(main)/transpose(jvp(TokenizerVQVAE))/decoder/checkpoint/STBlock_7/Dense_0/dot_general" source_file="/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar_run_overfit/.venv_jafar/lib/python3.10/site-packages/flax/linen/linear.py" source_line=287}\r\n ROOT %bitcast.16503 = f32[1,16,920,256]{3,2,1,0} bitcast(%dot.1723), metadata={op_name="jit(train_step)/jit(main)/transpose(jvp(TokenizerVQVAE))/decoder/checkpoint/STBlock_7/Dense_0/dot_general" source_file="/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar_run_overfit/.venv_jafar/lib/python3.10/site-packages/flax/linen/linear.py" source_line=287}\r\n}\r\n
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^C./slurm/dev/alfred/overfit_sample/train_tokenizer_overfit_sample_size_0_5.sh: line 34: 710438 Aborted (core dumped) python train_tokenizer_single_sample.py --ckpt_dir $CHECKPOINT_DIR --batch_size=1 --min_lr=4.3e-5 --max_lr=4.3e-4 --log_image_interval=10 --log --entity instant-uv --project jafar --name $job_name --tags $tags --model_dim 256 --num_heads 4 --data_dir $tf_records_dir\r\n]0;tum_ind3695@hkn0505:~/projects/jafar_run_overfit[?2004h(.venv_jafar) [tum_ind3695@hkn0505 jafar_run_overfit]$
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