XPK Start: Sat Apr 25 07:28:16 UTC 2026 `rope_parameters`'s factor field must be a float >= 1, got 40 `rope_parameters`'s beta_fast field must be a float, got 32 `rope_parameters`'s beta_slow field must be a float, got 1 DeepseekV32Config got `key=rope_scaling` in kwargs but hasn't set it as attribute. For RoPE standardization you need to set `self.rope_parameters` in model's config. 2026-04-25 07:28:48.728037: 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 07:28:48.920186 134886577321792 max_utils.py:273] Attempting to initialize the jax distributed system... I0425 07:28:57.958318 134886577321792 distributed.py:149] Starting JAX distributed service on [::]:8482 I0425 07:28:57.960808 134886577321792 distributed.py:172] Connecting to JAX distributed service on mt-02-sft-nnx-ckpt-gorby-slice-job-0-0.mt-02-sft-nnx-ckpt-gorby:8482 I0425 07:28:59.311442 134886577321792 max_utils.py:284] Jax distributed system initialized! I0425 07:29:05.617343 134886577321792 max_utils.py:800] System Information: Jax Version: 0.9.2 I0425 07:29:05.617453 134886577321792 max_utils.py:801] System Information: Jaxlib Version: 0.9.2 I0425 07:29:05.617498 134886577321792 max_utils.py:802] System Information: Jax Backend: PJRT C API TFRT TPU v6 lite Built on Apr 6 2026 20:48:10 (1775533690) cl/895581894 I0425 07:29:05.621390 134886577321792 maxtext_utils.py:1604] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1) I0425 07:29:06.225123 134886577321792 maxtext_utils.py:1604] Num_devices: 32, shape (1, 4, 1, 8, 1, 1, 1, 1, 1, 1, 1, 1) I0425 07:29:07.307809 134886577321792 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 07:29:07.308307 134886577321792 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 0x7aad0412eab0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 07:29:07.308366 134886577321792 abstract_checkpointer.py:35] orbax-checkpoint version: 0.11.28 W0425 07:29:07.821048 134886577321792 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 07:29:08.483604 1948 google_auth_provider.cc:181] Running on GCE, using service account 562977990677-compute@developer.gserviceaccount.com I0425 07:29:09.581291 134886577321792 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 07:29:10.491613 134886577321792 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 07:29:10.492033 134886577321792 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 07:29:11.571966 134886577321792 checkpointer.py:318] Finished restoring checkpoint in 2.36 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 07:29:11.646567 134886577321792 config.py:112] TensorFlow version 2.20.0 available. I0425 07:29:11.647092 134886577321792 config.py:125] JAX version 0.9.2 available. I0425 07:29:12.075546 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k/resolve/main/README.md "HTTP/1.1 307 Temporary Redirect" I0425 07:29:12.083643 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/api/resolve-cache/datasets/HuggingFaceH4/ultrachat_200k/8049631c405ae6576f93f445c6b8166f76f5505a/README.md "HTTP/1.1 200 OK" I0425 07:29:12.091920 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/resolve-cache/datasets/HuggingFaceH4/ultrachat_200k/8049631c405ae6576f93f445c6b8166f76f5505a/README.md "HTTP/1.1 200 OK" I0425 07:29:12.202731 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k/resolve/8049631c405ae6576f93f445c6b8166f76f5505a/ultrachat_200k.py "HTTP/1.1 404 Not Found" I0425 07:29:12.506572 134886577321792 _client.py:1025] HTTP Request: HEAD https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/HuggingFaceH4/ultrachat_200k/HuggingFaceH4/ultrachat_200k.py "HTTP/1.1 404 Not Found" I0425 07:29:12.622684 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/datasets/HuggingFaceH4/ultrachat_200k/revision/8049631c405ae6576f93f445c6b8166f76f5505a "HTTP/1.1 200 OK" I0425 07:29:12.728108 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k/resolve/8049631c405ae6576f93f445c6b8166f76f5505a/.huggingface.yaml "HTTP/1.1 404 Not Found" I0425 07:29:12.901769 134886577321792 _client.py:1025] HTTP Request: GET https://datasets-server.huggingface.co/info?dataset=HuggingFaceH4/ultrachat_200k "HTTP/1.1 200 OK" I0425 07:29:13.010915 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/datasets/HuggingFaceH4/ultrachat_200k/tree/8049631c405ae6576f93f445c6b8166f76f5505a/data?recursive=true&expand=false "HTTP/1.1 200 OK" I0425 07:29:13.122482 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/datasets/HuggingFaceH4/ultrachat_200k/tree/8049631c405ae6576f93f445c6b8166f76f5505a?recursive=false&expand=false "HTTP/1.1 200 OK" I0425 07:29:13.233986 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k/resolve/8049631c405ae6576f93f445c6b8166f76f5505a/dataset_infos.json "HTTP/1.1 404 Not Found" I0425 07:29:13.413851 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/config.json "HTTP/1.1 200 OK" I0425 07:29:13.523652 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/config.json "HTTP/1.1 200 OK" I0425 07:29:13.630084 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer_config.json "HTTP/1.1 200 OK" I0425 07:29:13.778411 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer_config.json "HTTP/1.1 200 OK" I0425 07:29:13.890016 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/models/meta-llama/Llama-2-7b-chat-hf/tree/main/additional_chat_templates?recursive=false&expand=false "HTTP/1.1 404 Not Found" I0425 07:29:13.992513 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/models/meta-llama/Llama-2-7b-chat-hf/tree/main?recursive=true&expand=false "HTTP/1.1 200 OK" I0425 07:29:14.104771 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer.model "HTTP/1.1 302 Found" I0425 07:29:14.215060 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/api/models/meta-llama/Llama-2-7b-chat-hf/xet-read-token/f5db02db724555f92da89c216ac04704f23d4590 "HTTP/1.1 200 OK" I0425 07:29:14.831534 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer.json "HTTP/1.1 200 OK" I0425 07:29:14.949763 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer.json "HTTP/1.1 200 OK" I0425 07:29:15.345341 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/added_tokens.json "HTTP/1.1 404 Not Found" I0425 07:29:15.453159 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/special_tokens_map.json "HTTP/1.1 200 OK" I0425 07:29:15.557679 134886577321792 _client.py:1025] HTTP Request: GET https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/special_tokens_map.json "HTTP/1.1 200 OK" I0425 07:29:15.669539 134886577321792 _client.py:1025] HTTP Request: HEAD https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/chat_template.jinja "HTTP/1.1 404 Not Found" /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 07:29:15.782246 134886577321792 packing.py:209] PackAndBatchOperation is deprecated. Please use lazy_dataset.FirstFitPackIterDataset instead. I0425 07:29:15.782457 134886577321792 data_loader.py:408] Adding CopyNumPyArrayToSharedMemory MapTransform. I0425 07:29:16.207437 134886577321792 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 07:29:16.207586 134886577321792 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 0x7aad0412eab0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 07:29:16.207634 134886577321792 pytree_checkpoint_handler.py:577] save_device_host_concurrent_bytes=None I0425 07:29:16.207668 134886577321792 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 0x7aad0412eab0>, enable_pinned_host_transfer=False, save_concurrent_bytes: 96000000000 (89.4 GiB), restore_concurrent_bytes: 96000000000 (89.4 GiB) I0425 07:29:16.207715 134886577321792 checkpoint_manager.py:702] [process=3][thread=MainThread] CheckpointManager init: checkpointers=None, item_names=None, item_handlers={'model_params': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa68473d760>, 'optimizer_state': <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa213314b60>, 'custom_metadata': <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa2133194f0>}, handler_registry=None I0425 07:29:16.207985 134886577321792 composite_checkpoint_handler.py:237] Deferred registration for item: "model_params". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa68473d760>` 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 07:29:16.208037 134886577321792 composite_checkpoint_handler.py:237] Deferred registration for item: "optimizer_state". Adding handler `<orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa213314b60>` 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 07:29:16.208067 134886577321792 composite_checkpoint_handler.py:237] Deferred registration for item: "custom_metadata". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa2133194f0>` 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 07:29:16.208093 134886577321792 composite_checkpoint_handler.py:237] Deferred registration for item: "metrics". Adding handler `<orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa21331a7e0>` 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 07:29:16.208120 134886577321792 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 0x7aa68473d760>, ('model_params', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa68473d760>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeSaveArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa213314b60>, ('optimizer_state', <class 'orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeRestoreArgs'>): <orbax.checkpoint._src.handlers.pytree_checkpoint_handler.PyTreeCheckpointHandler object at 0x7aa213314b60>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa2133194f0>, ('custom_metadata', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa2133194f0>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonSaveArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa21331a7e0>, ('metrics', <class 'orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonRestoreArgs'>): <orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler object at 0x7aa21331a7e0>}). I0425 07:29:16.208509 134886577321792 async_checkpointer.py:177] [process=3][thread=MainThread] Using barrier_sync_fn: <function get_barrier_sync_fn.<locals>._fn at 0x7a8f24221620> timeout: 600 secs and primary_host=0 for async checkpoint writes I0425 07:29:18.514983 134886577321792 checkpoint_manager.py:1788] Found 0 checkpoint steps in gs://lance-maxtext/pt_ckpt_xpk_main_20260425_071506/pt_sft_nnx_xpk_main_20260425_071506_02_sft_nnx_ckpt/checkpoints I0425 07:29:18.529299 134886577321792 checkpoint_manager.py:921] [process=3][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_main_20260425_071506/pt_sft_nnx_xpk_main_20260425_071506_02_sft_nnx_ckpt/checkpoints: <orbax.checkpoint.checkpoint_manager.CheckpointManager object at 0x7aa213318890> I0425 07:29:18.529580 134886577321792 peft_trainer.py:584] Training with mesh: Mesh('diloco': 1, 'data': 4, 'stage': 1, 'fsdp': 8, 'fsdp_transpose': 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)) I0425 07:29:18.998565 134886577321792 peft_trainer.py:594] Compiled train_step cache size: 0 I0425 07:29:19.002592 134886577321792 metric_logger.py:301] number parameters: 0.000 billion I0425 07:29:19.004874 134710365775616 grain_pool.py:367] Grain pool will use 1 processes. I0425 07:29:19.054294 134710365775616 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 07:29:19.060405 134710365775616 grain_pool.py:448] Grain pool started all child processes. 2026-04-25 07:29:23.247806: 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 07:29:23.291900: 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 07:29:24.468854: 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`. `rope_parameters`'s factor field must be a float >= 1, got 40 `rope_parameters`'s beta_fast field must be a float, got 32 `rope_parameters`'s beta_slow field must be a float, got 1 DeepseekV32Config got `key=rope_scaling` in kwargs but hasn't set it as attribute. For RoPE standardization you need to set `self.rope_parameters` in model's config. 2026-04-25 07:29:30.189615: 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) 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 217, 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 213, in main train(mt_config, goodput_recorder) File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 190, in train trainer = train_model(mt_config, trainer, mesh) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/deps/src/maxtext/trainers/post_train/sft/train_sft.py", line 176, 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 652, 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 156, 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 373, 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 373, 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 985, 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 1047, 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 844, 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 2732, in device_put out_flat = dispatch._batched_device_put_impl( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/jax/_src/dispatch.py", line 602, 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 582, 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 512, in _device_put_sharding_impl raise ValueError( ValueError: When the second argument to `device_put` is a Device, the first argument must be a fully addressable array or a non-addressable array with a single device sharding. Got value with devices {TpuDevice(id=5, process_index=0, coords=(1,1,0), 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=11, process_index=3, coords=(3,2,0), core_on_chip=0), TpuDevice(id=13, process_index=2, coords=(1,3,0), core_on_chip=0), TpuDevice(id=6, process_index=1, coords=(2,1,0), 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=26, process_index=7, coords=(2,6,0), core_on_chip=0), TpuDevice(id=3, process_index=1, coords=(3,0,0), core_on_chip=0), TpuDevice(id=17, process_index=4, coords=(1,4,0), core_on_chip=0), TpuDevice(id=14, process_index=3, coords=(2,3,0), core_on_chip=0), TpuDevice(id=25, process_index=6, coords=(1,6,0), core_on_chip=0), TpuDevice(id=10, process_index=3, coords=(2,2,0), core_on_chip=0), TpuDevice(id=19, process_index=5, coords=(3,4,0), core_on_chip=0), TpuDevice(id=27, process_index=7, coords=(3,6,0), core_on_chip=0), TpuDevice(id=8, process_index=2, coords=(0,2,0), core_on_chip=0), TpuDevice(id=7, process_index=1, coords=(3,1,0), core_on_chip=0), TpuDevice(id=20, process_index=4, coords=(0,5,0), core_on_chip=0), TpuDevice(id=15, process_index=3, coords=(3,3,0), core_on_chip=0), TpuDevice(id=28, process_index=6, coords=(0,7,0), core_on_chip=0), TpuDevice(id=16, process_index=4, coords=(0,4,0), core_on_chip=0), TpuDevice(id=22, process_index=5, coords=(2,5,0), 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=12, process_index=2, coords=(0,3,0), core_on_chip=0), TpuDevice(id=23, process_index=5, coords=(3,5,0), core_on_chip=0), TpuDevice(id=1, process_index=0, coords=(1,0,0), 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=21, process_index=4, coords=(1,5,0), core_on_chip=0), TpuDevice(id=0, process_index=0, coords=(0,0,0), core_on_chip=0)} I0425 07:29:35.457305 134710365775616 grain_pool.py:542] Grain pool is exiting. I0425 07:29:35.457407 134710365775616 grain_pool.py:547] Shutting down multiprocessing system. I0425 07:29:41.231211 134710365775616 grain_pool.py:547] Shutting down multiprocessing system. /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 07:29:52 UTC 2026 EXIT_CODE=1