XPK Start: Wed Apr 22 16:07:58 UTC 2026 2026-04-22 16:08:26.902786: 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 16:08:27.135569 132469194254144 max_utils.py:273] Attempting to initialize the jax distributed system... INFO:2026-04-22 16:08:36,175:jax._src.distributed:149: Starting JAX distributed service on [::]:8482 I0422 16:08:36.175970 132469194254144 distributed.py:149] Starting JAX distributed service on [::]:8482 INFO:2026-04-22 16:08:36,178:jax._src.distributed:166: Connecting to JAX distributed service on mt-02-sft-nnx-ckpt-3i92f-slice-job-0-0.mt-02-sft-nnx-ckpt-3i92f:8482 I0422 16:08:36.178389 132469194254144 distributed.py:166] Connecting to JAX distributed service on mt-02-sft-nnx-ckpt-3i92f-slice-job-0-0.mt-02-sft-nnx-ckpt-3i92f:8482 I0422 16:08:37.947251 132469194254144 max_utils.py:284] Jax distributed system initialized! I0422 16:08:44.199944 132469194254144 max_utils.py:800] System Information: Jax Version: 0.8.3 I0422 16:08:44.200048 132469194254144 max_utils.py:801] System Information: Jaxlib Version: 0.8.3 I0422 16:08:44.200087 132469194254144 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 16:08:44.203473 132469194254144 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:08:44.297101 132469194254144 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:08:44.396409 132469194254144 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0422 16:08:45.437436 132469194254144 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:08:45.437885 132469194254144 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 0x787a2d9c5d90>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:08:45.437948 132469194254144 abstract_checkpointer.py:35] orbax-checkpoint version: 0.11.28 W0422 16:08:45.967672 132469194254144 checkpoint.py:202] Metadata file does not exist: gs://lance-maxtext/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_feat_nnx_trainstate_and_training_loop_20260411_044231_08_checkpoint_async_true/checkpoints/9/items/_CHECKPOINT_METADATA I0422 16:08:46.836793 1946 google_auth_provider.cc:181] Running on GCE, using service account 562977990677-compute@developer.gserviceaccount.com I0422 16:08:48.041592 132469194254144 checkpointer.py:304] Restoring checkpoint from gs://lance-maxtext/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_feat_nnx_trainstate_and_training_loop_20260411_044231_08_checkpoint_async_true/checkpoints/9/items. W0422 16:08:48.979326 132469194254144 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 16:08:48.979758 132469194254144 transform_utils.py:288] The following keys are not loaded from the original tree after applying specified transforms: decoder/decoder_norm/bias/value, decoder/decoder_norm/scale/value, decoder/dropout/rngs/aqt/count/value, decoder/dropout/rngs/aqt/key/value, decoder/dropout/rngs/dropout/count/value, decoder/dropout/rngs/dropout/key/value, decoder/dropout/rngs/params/count/value, decoder/dropout/rngs/params/key/value, decoder/layers/dropout/rngs/aqt/count/value, decoder/layers/dropout/rngs/aqt/key/value, decoder/layers/dropout/rngs/dropout/count/value, decoder/layers/dropout/rngs/dropout/key/value, decoder/layers/dropout/rngs/params/count/value, decoder/layers/dropout/rngs/params/key/value, decoder/layers/mlp/dropout/rngs/aqt/count/value, decoder/layers/mlp/dropout/rngs/aqt/key/value, decoder/layers/mlp/dropout/rngs/dropout/count/value, decoder/layers/mlp/dropout/rngs/dropout/key/value, decoder/layers/mlp/dropout/rngs/params/count/value, decoder/layers/mlp/dropout/rngs/params/key/value, decoder/layers/mlp/mlp_layer_norm/bias/value, decoder/layers/mlp/mlp_layer_norm/scale/value, decoder/layers/mlp/wi/bias/value, decoder/layers/mlp/wi/kernel/value, decoder/layers/mlp/wo/bias/value, decoder/layers/mlp/wo/kernel/value, decoder/layers/pre_self_attention_norm/bias/value, decoder/layers/pre_self_attention_norm/scale/value, decoder/layers/rngs/aqt/count/value, decoder/layers/rngs/aqt/key/value, decoder/layers/rngs/dropout/count/value, decoder/layers/rngs/dropout/key/value, decoder/layers/rngs/params/count/value, decoder/layers/rngs/params/key/value, decoder/layers/self_attention/out/bias/value, decoder/layers/self_attention/out/kernel/value, decoder/layers/self_attention/qkv_proj/bias/value, decoder/layers/self_attention/qkv_proj/kernel/value, decoder/position_embedder/embedding/value, decoder/rngs/aqt/count/value, decoder/rngs/aqt/key/value, decoder/rngs/dropout/count/value, decoder/rngs/dropout/key/value, decoder/rngs/params/count/value, decoder/rngs/params/key/value, token_embedder/embedding/value I0422 16:08:49.746564 132469194254144 checkpointer.py:318] Finished restoring checkpoint in 2.09 seconds from gs://lance-maxtext/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_ckpt_feat_nnx_trainstate_and_training_loop_20260411_044231/nnx_feat_nnx_trainstate_and_training_loop_20260411_044231_08_checkpoint_async_true/checkpoints/9/items. I0422 16:08:49.814837 132469194254144 config.py:112] TensorFlow version 2.20.0 available. I0422 16:08:49.815346 132469194254144 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 16:08:55.478698 132469194254144 packing.py:209] PackAndBatchOperation is deprecated. Please use lazy_dataset.FirstFitPackIterDataset instead. I0422 16:08:55.478930 132469194254144 data_loader.py:408] Adding CopyNumPyArrayToSharedMemory MapTransform. I0422 16:08:55.871267 132469194254144 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:08:55.871413 132469194254144 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 0x787a2d9c5d90>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:08:55.871458 132469194254144 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0422 16:08:55.871493 132469194254144 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 0x787a2d9c5d90>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0422 16:08:55.871537 132469194254144 checkpoint_manager.py:702] [process=4][thread=MainThread] CheckpointManager init: checkpointers=None, item_names=None, item_handlers={'model_params': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b8d370>, 'optimizer_state': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b900b0>, 'custom_metadata': <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b90080>}, handler_registry=None I0422 16:08:55.871743 132469194254144 composite_checkpoint_handler.py:237] Deferred registration for item: "model_params". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b8d370>` 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 16:08:55.871785 132469194254144 composite_checkpoint_handler.py:237] Deferred registration for item: "optimizer_state". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b900b0>` 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 16:08:55.871813 132469194254144 composite_checkpoint_handler.py:237] Deferred registration for item: "custom_metadata". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b90080>` 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 16:08:55.871837 132469194254144 composite_checkpoint_handler.py:237] Deferred registration for item: "metrics". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b913a0>` 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 16:08:55.871864 132469194254144 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 0x786224b8d370>, ('model_params', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b8d370>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b900b0>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x786224b900b0>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b90080>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b90080>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b913a0>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x786224b913a0>}). I0422 16:08:55.873370 132469194254144 async_checkpointer.py:177] [process=4][thread=MainThread] Using barrier_sync_fn: <function get_barrier_sync_fn.<locals>._fn at 0x78622517aca0> timeout: 600 secs and primary_host=0 for async checkpoint writes I0422 16:08:58.494444 132469194254144 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_02_sft_nnx_ckpt/checkpoints I0422 16:08:58.931023 132469194254144 checkpoint_manager.py:921] [process=4][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_02_sft_nnx_ckpt/checkpoints: <orbax.checkpoint.checkpoint_manager.CheckpointManager object at 0x786224b90050> I0422 16:08:58.931361 132469194254144 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 16:08:59.348639 132469194254144 peft_trainer.py:600] Compiled train_step cache size: 0 Training: 0%| | 0/5 [00:00<?, ?step/s]I0422 16:08:59.352929 132469194254144 metric_logger.py:289] number parameters: 0.000 billion I0422 16:08:59.355198 132316006487808 grain_pool.py:367] Grain pool will use 1 processes. I0422 16:08:59.381774 132316006487808 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 16:08:59.386781 132316006487808 grain_pool.py:448] Grain pool started all child processes. 2026-04-22 16:09:03.292686: 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 16:09:03.338041: 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 16:09:04.318394: 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 16:09:08.544645: 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 16:09:14.413355 132469194254144 utils.py:86] Train loop finished in: 15.0594 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=29, process_index=6, coords=(1,7,0), core_on_chip=0), TpuDevice(id=15, process_index=3, coords=(3,3,0), core_on_chip=0), TpuDevice(id=23, process_index=5, coords=(3,5,0), 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=2, process_index=1, coords=(2,0,0), core_on_chip=0), TpuDevice(id=26, process_index=7, coords=(2,6,0), core_on_chip=0), TpuDevice(id=31, process_index=7, coords=(3,7,0), core_on_chip=0), TpuDevice(id=16, process_index=4, coords=(0,4,0), core_on_chip=0), TpuDevice(id=24, process_index=6, coords=(0,6,0), core_on_chip=0), TpuDevice(id=18, process_index=5, coords=(2,4,0), core_on_chip=0), TpuDevice(id=1, process_index=0, coords=(1,0,0), core_on_chip=0), TpuDevice(id=27, process_index=7, coords=(3,6,0), core_on_chip=0), TpuDevice(id=12, process_index=2, coords=(0,3,0), core_on_chip=0), TpuDevice(id=11, process_index=3, coords=(3,2,0), core_on_chip=0), TpuDevice(id=3, process_index=1, coords=(3,0,0), core_on_chip=0), TpuDevice(id=13, process_index=2, coords=(1,3,0), core_on_chip=0), TpuDevice(id=17, process_index=4, coords=(1,4,0), core_on_chip=0), TpuDevice(id=25, process_index=6, coords=(1,6,0), core_on_chip=0), TpuDevice(id=19, process_index=5, coords=(3,4,0), core_on_chip=0), TpuDevice(id=4, process_index=0, coords=(0,1,0), core_on_chip=0), TpuDevice(id=0, process_index=0, coords=(0,0,0), core_on_chip=0), TpuDevice(id=7, process_index=1, coords=(3,1,0), core_on_chip=0), TpuDevice(id=8, process_index=2, coords=(0,2,0), core_on_chip=0), TpuDevice(id=20, process_index=4, coords=(0,5,0), core_on_chip=0), TpuDevice(id=28, process_index=6, coords=(0,7,0), core_on_chip=0), TpuDevice(id=14, process_index=3, coords=(2,3,0), core_on_chip=0), TpuDevice(id=5, process_index=0, coords=(1,1,0), core_on_chip=0), TpuDevice(id=22, process_index=5, coords=(2,5,0), core_on_chip=0), TpuDevice(id=6, process_index=1, coords=(2,1,0), core_on_chip=0), TpuDevice(id=30, process_index=7, coords=(2,7,0), core_on_chip=0)} I0422 16:09:14.763186 132316006487808 grain_pool.py:542] Grain pool is exiting. I0422 16:09:14.763298 132316006487808 grain_pool.py:547] Shutting down multiprocessing system. I0422 16:09:20.604577 132316006487808 grain_pool.py:547] Shutting down multiprocessing system. Training: 0%| | 0/5 [00:24<?, ?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 16:09:34 UTC 2026 EXIT_CODE=1