XPK Start: Wed Apr 22 16:10:36 UTC 2026 2026-04-22 16:11:04.708657: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303) I0422 16:11:04.931543 133937573807936 max_utils.py:273] Attempting to initialize the jax distributed system... INFO:2026-04-22 16:11:13,974:jax._src.distributed:149: Starting JAX distributed service on [::]:8482 I0422 16:11:13.974259 133937573807936 distributed.py:149] Starting JAX distributed service on [::]:8482 INFO:2026-04-22 16:11:13,976:jax._src.distributed:166: Connecting to JAX distributed service on mt-03-sft-linen-ckpt-wu7mh-slice-job-0-0.mt-03-sft-linen-ckpt-wu7mh:8482 I0422 16:11:13.976588 133937573807936 distributed.py:166] Connecting to JAX distributed service on mt-03-sft-linen-ckpt-wu7mh-slice-job-0-0.mt-03-sft-linen-ckpt-wu7mh:8482 I0422 16:11:15.500575 133937573807936 max_utils.py:284] Jax distributed system initialized! I0422 16:11:20.738698 133937573807936 max_utils.py:800] System Information: Jax Version: 0.8.3 I0422 16:11:20.738806 133937573807936 max_utils.py:801] System Information: Jaxlib Version: 0.8.3 I0422 16:11:20.738856 133937573807936 max_utils.py:802] System Information: Jax Backend: PJRT C API TFRT TPU v6 lite Built on Dec 15 2025 14:03:46 (1765836226) cl/844590465 I0422 16:11:20.742256 133937573807936 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:11:20.837944 133937573807936 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:11:20.940022 133937573807936 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:11:21.997695 133937573807936 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:11:21.998156 133937573807936 base_pytree_checkpoint_handler.py:411] Created BasePyTreeCheckpointHandler: use_ocdbt=True, use_zarr3=True, pytree_metadata_options=PyTreeMetadataOptions(support_rich_types=False), array_metadata_store=<orbax.checkpoint._src.metadata.array_metadata_store.Store object at 0x79d00fd7a4e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:11:21.998218 133937573807936 abstract_checkpointer.py:35] orbax-checkpoint version: 0.11.28 W0422 16:11:22.555235 133937573807936 checkpoint.py:202] Metadata file does not exist: gs://lance-maxtext/pt_seed_ckpts/pt_seed_ckpts/pt_seed_ckpt_gpt352k_linen/checkpoints/9/items/_CHECKPOINT_METADATA I0422 16:11:23.115635 1894 google_auth_provider.cc:181] Running on GCE, using service account 562977990677-compute@developer.gserviceaccount.com I0422 16:11:24.285800 133937573807936 checkpointer.py:304] Restoring checkpoint from gs://lance-maxtext/pt_seed_ckpts/pt_seed_ckpts/pt_seed_ckpt_gpt352k_linen/checkpoints/9/items. W0422 16:11:26.161304 133937573807936 transform_utils.py:230] The transformations API will eventually be replaced by an upgraded design. The current API will not be removed until this point, but it will no longer be actively worked on. I0422 16:11:26.161731 133937573807936 transform_utils.py:288] The following keys are not loaded from the original tree after applying specified transforms: params/params/decoder/dropout/rngs/aqt/count, params/params/decoder/dropout/rngs/aqt/key, params/params/decoder/dropout/rngs/dropout/count, params/params/decoder/dropout/rngs/dropout/key, params/params/decoder/dropout/rngs/params/count, params/params/decoder/dropout/rngs/params/key, params/params/decoder/layers/dropout/rngs/aqt/count, params/params/decoder/layers/dropout/rngs/aqt/key, params/params/decoder/layers/dropout/rngs/dropout/count, params/params/decoder/layers/dropout/rngs/dropout/key, params/params/decoder/layers/dropout/rngs/params/count, params/params/decoder/layers/dropout/rngs/params/key, params/params/decoder/layers/mlp/dropout/rngs/aqt/count, params/params/decoder/layers/mlp/dropout/rngs/aqt/key, params/params/decoder/layers/mlp/dropout/rngs/dropout/count, params/params/decoder/layers/mlp/dropout/rngs/dropout/key, params/params/decoder/layers/mlp/dropout/rngs/params/count, params/params/decoder/layers/mlp/dropout/rngs/params/key, params/params/decoder/layers/rngs/aqt/count, params/params/decoder/layers/rngs/aqt/key, params/params/decoder/layers/rngs/dropout/count, params/params/decoder/layers/rngs/dropout/key, params/params/decoder/layers/rngs/params/count, params/params/decoder/layers/rngs/params/key, params/params/decoder/rngs/aqt/count, params/params/decoder/rngs/aqt/key, params/params/decoder/rngs/dropout/count, params/params/decoder/rngs/dropout/key, params/params/decoder/rngs/params/count, params/params/decoder/rngs/params/key I0422 16:11:26.630742 133937573807936 checkpointer.py:318] Finished restoring checkpoint in 2.73 seconds from gs://lance-maxtext/pt_seed_ckpts/pt_seed_ckpts/pt_seed_ckpt_gpt352k_linen/checkpoints/9/items. I0422 16:11:26.698730 133937573807936 config.py:112] TensorFlow version 2.20.0 available. I0422 16:11:26.699244 133937573807936 config.py:125] JAX version 0.8.3 available. /deps/src/maxtext/input_pipeline/input_pipeline_utils.py:467: UserWarning: WARNING: Inefficient dataloading. Your train or eval dataset contains 3 shards, smaller than number of host loading data. This is known to lead to inefficient dataloading. Seegithub.com/google/maxtext/blob/main/getting_started/Data_Input_Pipeline.md#multihost-dataloading-best-practice warnings.warn( E0422 16:11:32.236613 133937573807936 packing.py:209] PackAndBatchOperation is deprecated. Please use lazy_dataset.FirstFitPackIterDataset instead. I0422 16:11:32.236829 133937573807936 data_loader.py:408] Adding CopyNumPyArrayToSharedMemory MapTransform. I0422 16:11:32.627610 133937573807936 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:11:32.627752 133937573807936 base_pytree_checkpoint_handler.py:411] Created BasePyTreeCheckpointHandler: use_ocdbt=True, use_zarr3=False, pytree_metadata_options=PyTreeMetadataOptions(support_rich_types=False), array_metadata_store=<orbax.checkpoint._src.metadata.array_metadata_store.Store object at 0x79d00fd7a4e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:11:32.627795 133937573807936 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:11:32.627830 133937573807936 base_pytree_checkpoint_handler.py:411] Created BasePyTreeCheckpointHandler: use_ocdbt=True, use_zarr3=False, pytree_metadata_options=PyTreeMetadataOptions(support_rich_types=False), array_metadata_store=<orbax.checkpoint._src.metadata.array_metadata_store.Store object at 0x79d00fd7a4e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:11:32.627872 133937573807936 checkpoint_manager.py:702] [process=6][thread=MainThread] CheckpointManager init: checkpointers=None, item_names=None, item_handlers={'model_params': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89a375070>, 'optimizer_state': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89b458b00>, 'custom_metadata': <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b899930e60>}, handler_registry=None I0422 16:11:32.628086 133937573807936 composite_checkpoint_handler.py:237] Deferred registration for item: "model_params". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89a375070>` for item "model_params" and save args `<class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>` and restore args `<class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>` to `_handler_registry`. I0422 16:11:32.628144 133937573807936 composite_checkpoint_handler.py:237] Deferred registration for item: "optimizer_state". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89b458b00>` for item "optimizer_state" and save args `<class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>` and restore args `<class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>` to `_handler_registry`. I0422 16:11:32.628173 133937573807936 composite_checkpoint_handler.py:237] Deferred registration for item: "custom_metadata". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b899930e60>` for item "custom_metadata" and save args `<class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>` and restore args `<class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>` to `_handler_registry`. I0422 16:11:32.628198 133937573807936 composite_checkpoint_handler.py:237] Deferred registration for item: "metrics". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b89a3751f0>` for item "metrics" and save args `<class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>` and restore args `<class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>` to `_handler_registry`. I0422 16:11:32.628226 133937573807936 composite_checkpoint_handler.py:505] Initialized registry DefaultCheckpointHandlerRegistry({('model_params', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89a375070>, ('model_params', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89a375070>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89b458b00>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x79b89b458b00>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b899930e60>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b899930e60>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b89a3751f0>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x79b89a3751f0>}). I0422 16:11:32.628626 133937573807936 async_checkpointer.py:177] [process=6][thread=MainThread] Using barrier_sync_fn: <function get_barrier_sync_fn.<locals>._fn at 0x79b4340585e0> timeout: 600 secs and primary_host=0 for async checkpoint writes I0422 16:11:35.153164 133937573807936 checkpoint_manager.py:1788] Found 0 checkpoint steps in gs://lance-maxtext/pt_ckpt_xpk_feat_nnx_set_defaults_true_20260422_154655/pt_sft_nnx_xpk_feat_nnx_set_defaults_true_20260422_154655_03_sft_linen_ckpt/checkpoints I0422 16:11:35.593201 133937573807936 checkpoint_manager.py:921] [process=6][thread=MainThread] CheckpointManager created, primary_host=0, CheckpointManagerOptions=CheckpointManagerOptions(save_interval_steps=10000, max_to_keep=None, keep_time_interval=None, keep_period=None, should_keep_fn=None, best_fn=None, best_mode='max', keep_checkpoints_without_metrics=True, step_prefix=None, step_format_fixed_length=None, step_name_format=None, create=True, cleanup_tmp_directories=False, save_on_steps=frozenset(), single_host_load_and_broadcast=False, todelete_subdir=None, todelete_full_path=None, enable_hns=False, enable_background_delete=False, read_only=False, enable_async_checkpointing=True, async_options=None, multiprocessing_options=MultiprocessingOptions(primary_host=0, active_processes=None, barrier_sync_key_prefix=None), should_save_fn=None, file_options=FileOptions(path_permission_mode=None), save_root_metadata=True, temporary_path_class=None, save_decision_policy=None, preservation_policy=None, prevent_write_metrics=False, enable_should_save_is_saving_in_progress_check=True, enable_per_process_directory_creation=False), root_directory=gs://lance-maxtext/pt_ckpt_xpk_feat_nnx_set_defaults_true_20260422_154655/pt_sft_nnx_xpk_feat_nnx_set_defaults_true_20260422_154655_03_sft_linen_ckpt/checkpoints: <orbax.checkpoint.checkpoint_manager.CheckpointManager object at 0x79b899931af0> I0422 16:11:35.593734 133937573807936 peft_trainer.py:590] Training with mesh: Mesh('diloco': 1, 'data': 4, 'stage': 1, 'fsdp': 8, 'fsdp_transpose': 1, 'sequence': 1, 'context': 1, 'context_autoregressive': 1, 'tensor': 1, 'tensor_transpose': 1, 'tensor_sequence': 1, 'expert': 1, 'autoregressive': 1, axis_types=(Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto, Auto)) I0422 16:11:36.011493 133937573807936 peft_trainer.py:600] Compiled train_step cache size: 0 Training: 0%| | 0/5 [00:00<?, ?step/s]I0422 16:11:36.015735 133937573807936 metric_logger.py:289] number parameters: 0.000 billion I0422 16:11:36.018117 133786596210432 grain_pool.py:367] Grain pool will use 1 processes. I0422 16:11:36.047574 133786596210432 grain_pool.py:440] Grain pool will start child processes. Per train step: Total TFLOPs: 0.00 split as 54.29% learnable weight flops and 45.71% attention flops I0422 16:11:36.052773 133786596210432 grain_pool.py:448] Grain pool started all child processes. 2026-04-22 16:11:39.986994: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. 2026-04-22 16:11:40.032198: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI AVX512_BF16 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. 2026-04-22 16:11:41.018030: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. 2026-04-22 16:11:45.255634: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303) I0422 16:11:51.142873 133937573807936 utils.py:86] Train loop finished in: 15.1260 seconds Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in _run_code File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 216, in <module> app.run(main) File "/usr/local/lib/python3.12/site-packages/absl/app.py", line 316, in run _run_main(main, args) File "/usr/local/lib/python3.12/site-packages/absl/app.py", line 261, in _run_main sys.exit(main(argv)) ^^^^^^^^^^ File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 212, in main train(mt_config, goodput_recorder) File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 189, in train trainer = train_model(mt_config, trainer, mesh) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 175, in train_model trainer.train(trainer.data_hooks.train_data_iterator, trainer.data_hooks.eval_data_iterator) File "/usr/local/lib/python3.12/site-packages/tunix/sft/peft_trainer.py", line 659, in train train_example = sharding_utils.shard_input( ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/tunix/sft/sharding_utils.py", line 58, in shard_input return jax.tree.map( ^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/tree.py", line 155, in map return tree_util.tree_map(f, tree, *rest, is_leaf=is_leaf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/tree_util.py", line 362, in tree_map return treedef.unflatten(f(*xs) for xs in zip(*all_leaves)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/tree_util.py", line 362, in <genexpr> return treedef.unflatten(f(*xs) for xs in zip(*all_leaves)) ^^^^^^ File "/usr/local/lib/python3.12/site-packages/tunix/sft/sharding_utils.py", line 59, in <lambda> lambda x: jax.make_array_from_process_local_data( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/array.py", line 986, in make_array_from_process_local_data out = [_array_from_process_local_data(data, s, shape) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/array.py", line 1048, in _array_from_process_local_data return make_array_from_callback(global_shape, sharding, cb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/array.py", line 845, in make_array_from_callback per_device_values = api.device_put(per_device_values, devices) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/api.py", line 2729, in device_put out_flat = dispatch._batched_device_put_impl( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/dispatch.py", line 558, in _batched_device_put_impl y = _device_put_impl(x, device=device, src=src, copy=cp, aval=aval) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/dispatch.py", line 545, in _device_put_impl return _device_put_sharding_impl(x, aval, device, copy) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/dispatch.py", line 487, in _device_put_sharding_impl raise ValueError( ValueError: device_put's first argument must be a fully addressable array, but got value with devices {TpuDevice(id=21, process_index=4, coords=(1,5,0), core_on_chip=0), TpuDevice(id=6, process_index=1, coords=(2,1,0), core_on_chip=0), TpuDevice(id=16, process_index=4, coords=(0,4,0), core_on_chip=0), TpuDevice(id=8, process_index=2, coords=(0,2,0), core_on_chip=0), TpuDevice(id=26, process_index=7, coords=(2,6,0), core_on_chip=0), TpuDevice(id=7, process_index=1, coords=(3,1,0), core_on_chip=0), TpuDevice(id=23, process_index=5, coords=(3,5,0), core_on_chip=0), TpuDevice(id=22, process_index=5, coords=(2,5,0), core_on_chip=0), TpuDevice(id=3, process_index=1, coords=(3,0,0), core_on_chip=0), TpuDevice(id=4, process_index=0, coords=(0,1,0), core_on_chip=0), TpuDevice(id=29, process_index=6, coords=(1,7,0), core_on_chip=0), TpuDevice(id=20, process_index=4, coords=(0,5,0), core_on_chip=0), TpuDevice(id=13, process_index=2, coords=(1,3,0), core_on_chip=0), TpuDevice(id=14, process_index=3, coords=(2,3,0), core_on_chip=0), TpuDevice(id=27, process_index=7, coords=(3,6,0), core_on_chip=0), TpuDevice(id=10, process_index=3, coords=(2,2,0), core_on_chip=0), TpuDevice(id=9, process_index=2, coords=(1,2,0), core_on_chip=0), TpuDevice(id=25, process_index=6, coords=(1,6,0), core_on_chip=0), TpuDevice(id=5, process_index=0, coords=(1,1,0), core_on_chip=0), TpuDevice(id=17, process_index=4, coords=(1,4,0), core_on_chip=0), TpuDevice(id=12, process_index=2, coords=(0,3,0), core_on_chip=0), TpuDevice(id=2, process_index=1, coords=(2,0,0), core_on_chip=0), TpuDevice(id=18, process_index=5, coords=(2,4,0), core_on_chip=0), TpuDevice(id=31, process_index=7, coords=(3,7,0), core_on_chip=0), TpuDevice(id=0, process_index=0, coords=(0,0,0), core_on_chip=0), TpuDevice(id=15, process_index=3, coords=(3,3,0), core_on_chip=0), TpuDevice(id=30, process_index=7, coords=(2,7,0), core_on_chip=0), TpuDevice(id=11, process_index=3, coords=(3,2,0), core_on_chip=0), TpuDevice(id=28, process_index=6, coords=(0,7,0), core_on_chip=0), TpuDevice(id=1, process_index=0, coords=(1,0,0), core_on_chip=0), TpuDevice(id=19, process_index=5, coords=(3,4,0), core_on_chip=0), TpuDevice(id=24, process_index=6, coords=(0,6,0), core_on_chip=0)} I0422 16:11:51.494646 133786596210432 grain_pool.py:542] Grain pool is exiting. I0422 16:11:51.494748 133786596210432 grain_pool.py:547] Shutting down multiprocessing system. I0422 16:11:57.373409 133786596210432 grain_pool.py:547] Shutting down multiprocessing system. Training: 0%| | 0/5 [00:25<?, ?step/s] /usr/local/lib/python3.12/multiprocessing/resource_tracker.py:279: UserWarning: resource_tracker: There appear to be 15 leaked shared_memory objects to clean up at shutdown warnings.warn('resource_tracker: There appear to be %d ' XPK End: Wed Apr 22 16:12:11 UTC 2026 EXIT_CODE=1