XPK Start: Sat Apr 25 15:17:54 UTC 2026 2026-04-25 15:18:23.140980: 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) I0425 15:18:23.364139 138860013045568 max_utils.py:273] Attempting to initialize the jax distributed system... INFO:2026-04-25 15:18:32,406:jax._src.distributed:149: Starting JAX distributed service on [::]:8482 I0425 15:18:32.406263 138860013045568 distributed.py:149] Starting JAX distributed service on [::]:8482 INFO:2026-04-25 15:18:32,408:jax._src.distributed:166: Connecting to JAX distributed service on mt-02-sft-nnx-ckpt-hlx8o-slice-job-0-0.mt-02-sft-nnx-ckpt-hlx8o:8482 I0425 15:18:32.408667 138860013045568 distributed.py:166] Connecting to JAX distributed service on mt-02-sft-nnx-ckpt-hlx8o-slice-job-0-0.mt-02-sft-nnx-ckpt-hlx8o:8482 I0425 15:18:33.809052 138860013045568 max_utils.py:284] Jax distributed system initialized! I0425 15:18:39.880568 138860013045568 max_utils.py:800] System Information: Jax Version: 0.8.3 I0425 15:18:39.880694 138860013045568 max_utils.py:801] System Information: Jaxlib Version: 0.8.3 I0425 15:18:39.880736 138860013045568 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 I0425 15:18:39.884079 138860013045568 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0425 15:18:39.978833 138860013045568 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0425 15:18:40.078334 138860013045568 maxtext_utils.py:1631] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1) I0425 15:18:41.121332 138860013045568 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 15:18:41.121795 138860013045568 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 0x7e4a2b0f09e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 15:18:41.121856 138860013045568 abstract_checkpointer.py:35] orbax-checkpoint version: 0.11.28 W0425 15:18:41.675082 138860013045568 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 I0425 15:18:42.217955 1936 google_auth_provider.cc:181] Running on GCE, using service account 562977990677-compute@developer.gserviceaccount.com I0425 15:18:43.433146 138860013045568 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. W0425 15:18:44.325033 138860013045568 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. I0425 15:18:44.325442 138860013045568 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 I0425 15:18:44.830486 138860013045568 checkpointer.py:318] Finished restoring checkpoint in 1.78 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. I0425 15:18:44.899416 138860013045568 config.py:112] TensorFlow version 2.20.0 available. I0425 15:18:44.899923 138860013045568 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( E0425 15:18:50.392829 138860013045568 packing.py:209] PackAndBatchOperation is deprecated. Please use lazy_dataset.FirstFitPackIterDataset instead. I0425 15:18:50.393048 138860013045568 data_loader.py:408] Adding CopyNumPyArrayToSharedMemory MapTransform. I0425 15:18:50.779408 138860013045568 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 15:18:50.779551 138860013045568 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 0x7e4a2b0f09e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 15:18:50.779596 138860013045568 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 15:18:50.779629 138860013045568 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 0x7e4a2b0f09e0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 15:18:50.779689 138860013045568 checkpoint_manager.py:702] [process=5][thread=MainThread] CheckpointManager init: checkpointers=None, item_names=None, item_handlers={'model_params': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb8066c0>, 'optimizer_state': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb805190>, 'custom_metadata': <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805220>}, handler_registry=None I0425 15:18:50.779964 138860013045568 composite_checkpoint_handler.py:237] Deferred registration for item: "model_params". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb8066c0>` 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`. I0425 15:18:50.780028 138860013045568 composite_checkpoint_handler.py:237] Deferred registration for item: "optimizer_state". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb805190>` 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`. I0425 15:18:50.780073 138860013045568 composite_checkpoint_handler.py:237] Deferred registration for item: "custom_metadata". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805220>` 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`. I0425 15:18:50.780104 138860013045568 composite_checkpoint_handler.py:237] Deferred registration for item: "metrics". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805e80>` 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`. I0425 15:18:50.780143 138860013045568 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 0x7e31bb8066c0>, ('model_params', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb8066c0>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb805190>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7e31bb805190>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805220>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805220>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805e80>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7e31bb805e80>}). I0425 15:18:50.781781 138860013045568 async_checkpointer.py:177] [process=5][thread=MainThread] Using barrier_sync_fn: <function get_barrier_sync_fn.<locals>._fn at 0x7e31bbf66ca0> timeout: 600 secs and primary_host=0 for async checkpoint writes I0425 15:18:53.474487 138860013045568 checkpoint_manager.py:1788] Found 0 checkpoint steps in gs://lance-maxtext/pt_ckpt_xpk_feat_nnx_set_defaults_true_20260425_150421/pt_sft_nnx_xpk_feat_nnx_set_defaults_true_20260425_150421_02_sft_nnx_ckpt/checkpoints I0425 15:18:53.476646 138860013045568 checkpoint_manager.py:921] [process=5][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_20260425_150421/pt_sft_nnx_xpk_feat_nnx_set_defaults_true_20260425_150421_02_sft_nnx_ckpt/checkpoints: <orbax.checkpoint.checkpoint_manager.CheckpointManager object at 0x7e31bb8052b0> I0425 15:18:53.476916 138860013045568 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)) I0425 15:18:53.895905 138860013045568 peft_trainer.py:600] Compiled train_step cache size: 0 Training: 0%| | 0/5 [00:00<?, ?step/s]I0425 15:18:53.900058 138860013045568 metric_logger.py:289] number parameters: 0.000 billion I0425 15:18:53.902446 138707528107776 grain_pool.py:367] Grain pool will use 1 processes. I0425 15:18:53.931769 138707528107776 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 I0425 15:18:53.936915 138707528107776 grain_pool.py:448] Grain pool started all child processes. 2026-04-25 15:18:57.837753: 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`. 2026-04-25 15:18:57.882016: 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. 2026-04-25 15:18:58.863018: 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`. 2026-04-25 15:19:03.088816: 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) I0425 15:19:08.940771 138860013045568 utils.py:86] Train loop finished in: 15.0396 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=13, process_index=2, coords=(1,3,0), core_on_chip=0), TpuDevice(id=21, process_index=4, coords=(1,5,0), core_on_chip=0), TpuDevice(id=7, process_index=1, coords=(3,1,0), core_on_chip=0), TpuDevice(id=15, process_index=3, coords=(3,3,0), core_on_chip=0), TpuDevice(id=1, process_index=0, coords=(1,0,0), core_on_chip=0), TpuDevice(id=3, process_index=1, coords=(3,0,0), core_on_chip=0), TpuDevice(id=23, process_index=5, coords=(3,5,0), core_on_chip=0), TpuDevice(id=28, process_index=6, coords=(0,7,0), core_on_chip=0), TpuDevice(id=29, process_index=6, coords=(1,7,0), 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=10, process_index=3, coords=(2,2,0), core_on_chip=0), TpuDevice(id=18, process_index=5, coords=(2,4,0), core_on_chip=0), TpuDevice(id=24, process_index=6, coords=(0,6,0), core_on_chip=0), TpuDevice(id=8, process_index=2, coords=(0,2,0), core_on_chip=0), TpuDevice(id=5, process_index=0, coords=(1,1,0), 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), TpuDevice(id=4, process_index=0, coords=(0,1,0), core_on_chip=0), TpuDevice(id=17, process_index=4, coords=(1,4,0), core_on_chip=0), TpuDevice(id=11, process_index=3, coords=(3,2,0), core_on_chip=0), TpuDevice(id=19, process_index=5, coords=(3,4,0), core_on_chip=0), TpuDevice(id=9, process_index=2, coords=(1,2,0), 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=20, process_index=4, coords=(0,5,0), core_on_chip=0), TpuDevice(id=14, process_index=3, coords=(2,3,0), core_on_chip=0), TpuDevice(id=22, process_index=5, coords=(2,5,0), core_on_chip=0), TpuDevice(id=26, process_index=7, coords=(2,6,0), core_on_chip=0), TpuDevice(id=0, process_index=0, coords=(0,0,0), core_on_chip=0), TpuDevice(id=25, process_index=6, coords=(1,6,0), core_on_chip=0), TpuDevice(id=2, process_index=1, coords=(2,0,0), core_on_chip=0)} I0425 15:19:09.289175 138707528107776 grain_pool.py:542] Grain pool is exiting. I0425 15:19:09.289280 138707528107776 grain_pool.py:547] Shutting down multiprocessing system. I0425 15:19:15.135399 138707528107776 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: Sat Apr 25 15:19:25 UTC 2026 EXIT_CODE=1