Datasets:

---

amir0907

/

tpuvi

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
metadata: struct<total_size: int64>
  child 0, total_size: int64
weight_map: struct<model.acoustic_connector.fc1.bias: string, model.acoustic_connector.fc1.weight: string, model (... 81511 chars omitted)
  child 0, model.acoustic_connector.fc1.bias: string
  child 1, model.acoustic_connector.fc1.weight: string
  child 2, model.acoustic_connector.fc2.bias: string
  child 3, model.acoustic_connector.fc2.weight: string
  child 4, model.acoustic_connector.norm.weight: string
  child 5, model.acoustic_tokenizer.decoder.head.conv.conv.bias: string
  child 6, model.acoustic_tokenizer.decoder.head.conv.conv.weight: string
  child 7, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear1.bias: string
  child 8, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear1.weight: string
  child 9, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear2.bias: string
  child 10, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear2.weight: string
  child 11, model.acoustic_tokenizer.decoder.stages.0.0.ffn_gamma: string
  child 12, model.acoustic_tokenizer.decoder.stages.0.0.ffn_norm.weight: string
  child 13, model.acoustic_tokenizer.decoder.stages.0.0.gamma: string
  child 14, model.acoustic_tokenizer.decoder.stages.0.0.mixer.conv.conv.conv.bias: string
  child 15, model.acoustic_tokenizer.decoder.stages.0.0.mixer.conv.conv.conv.weight: string
  child 16, model.acoustic_tokenizer.decoder.stages.0.0.norm.weight: string
  child 17, model.acoustic_tokenizer.decoder.stages.0.1.ffn.linear1.bia
...
 int64, max_segments: int64, acoustic_dim: int64, semantic_di (... 9 chars omitted)
      child 0, max_seq_len: int64
      child 1, max_latents: int64
      child 2, max_segments: int64
      child 3, acoustic_dim: int64
      child 4, semantic_dim: int64
  child 3, preprocess_metadata: struct<model_name_or_path: string, processor_name_or_path: string, compress_ratio: int64, acoustic_d (... 408 chars omitted)
      child 0, model_name_or_path: string
      child 1, processor_name_or_path: string
      child 2, compress_ratio: int64
      child 3, acoustic_dim: int64
      child 4, semantic_dim: int64
      child 5, fix_std: double
      child 6, latent_dtype: string
      child 7, speech_scaling_factor: double
      child 8, speech_bias_factor: double
      child 9, scaling_source: string
      child 10, corpus_latent_mean: double
      child 11, corpus_latent_var: double
      child 12, shapes: struct<max_seq_len: int64, max_latents: int64, max_segments: int64, acoustic_dim: int64, semantic_di (... 9 chars omitted)
          child 0, max_seq_len: int64
          child 1, max_latents: int64
          child 2, max_segments: int64
          child 3, acoustic_dim: int64
          child 4, semantic_dim: int64
      child 13, pad_token_id: int64
      child 14, augment_target_silence: bool
      child 15, normalize_target_audio: bool
components_merged: list<item: string>
  child 0, item: string
checkpoint_dir: string
tensors_changed_vs_base: int64
base_model: string
dtype: string
to
{'base_model': Value('string'), 'checkpoint_dir': Value('string'), 'dtype': Value('string'), 'components_merged': List(Value('string')), 'tensors_changed_vs_base': Value('int64'), 'training_state': {'step': Value('int64'), 'args': {'model_name_or_path': Value('string'), 'data_dir': Value('string'), 'eval_data_dir': Value('null'), 'output_dir': Value('string'), 'lazy_data': Value('bool'), 'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'buckets': Value('null'), 'auto_buckets': Value('int64'), 'per_device_batch_size': Value('int64'), 'gradient_accumulation_steps': Value('int64'), 'learning_rate': Value('float64'), 'head_lr_multiplier': Value('float64'), 'weight_decay': Value('float64'), 'adam_beta1': Value('float64'), 'adam_beta2': Value('float64'), 'adam_eps': Value('float64'), 'max_grad_norm': Value('float64'), 'num_train_epochs': Value('float64'), 'max_steps': Value('int64'), 'warmup_ratio': Value('float64'), 'warmup_steps': Value('int64'), 'lr_scheduler': Value('string'), 'min_lr_ratio': Value('float64'), 'seed': Value('int64'), 'ce_loss_weight': Value('float64'), 'diffusion_loss_weight': Value('float64'), 'ddpm_batch_mul': Value('int64'), 'ce_chunk_size': Value('int64'), 'no_semantic': Value('bool'), 'no_latent_noise': Value('bool'), 'freeze_components': Value('null'), 'freeze_llm_layers': Value('null'), 'train_llm_layers': Value('null'), 'freeze_head_layers': Value('null'), 'freeze_embeddings': Value('bool'), 'freeze_lm_head': Value('bool'), 'freeze_regex': Value('null'), 'bf16': Value('bool'), 'gradient_checkpointing': Value('bool'), 'no_spmd': Value('bool'), 'logging_steps': Value('int64'), 'save_steps': Value('int64'), 'save_total_limit': Value('int64'), 'eval_steps': Value('int64'), 'eval_batches': Value('int64'), 'resume_from_checkpoint': Value('null'), 'dataloader_workers': Value('int64'), 'profile_first_steps': Value('int64')}, 'shapes': {'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64')}, 'preprocess_metadata': {'model_name_or_path': Value('string'), 'processor_name_or_path': Value('string'), 'compress_ratio': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64'), 'fix_std': Value('float64'), 'latent_dtype': Value('string'), 'speech_scaling_factor': Value('float64'), 'speech_bias_factor': Value('float64'), 'scaling_source': Value('string'), 'corpus_latent_mean': Value('float64'), 'corpus_latent_var': Value('float64'), 'shapes': {'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64')}, 'pad_token_id': Value('int64'), 'augment_target_silence': Value('bool'), 'normalize_target_audio': Value('bool')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              metadata: struct<total_size: int64>
                child 0, total_size: int64
              weight_map: struct<model.acoustic_connector.fc1.bias: string, model.acoustic_connector.fc1.weight: string, model (... 81511 chars omitted)
                child 0, model.acoustic_connector.fc1.bias: string
                child 1, model.acoustic_connector.fc1.weight: string
                child 2, model.acoustic_connector.fc2.bias: string
                child 3, model.acoustic_connector.fc2.weight: string
                child 4, model.acoustic_connector.norm.weight: string
                child 5, model.acoustic_tokenizer.decoder.head.conv.conv.bias: string
                child 6, model.acoustic_tokenizer.decoder.head.conv.conv.weight: string
                child 7, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear1.bias: string
                child 8, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear1.weight: string
                child 9, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear2.bias: string
                child 10, model.acoustic_tokenizer.decoder.stages.0.0.ffn.linear2.weight: string
                child 11, model.acoustic_tokenizer.decoder.stages.0.0.ffn_gamma: string
                child 12, model.acoustic_tokenizer.decoder.stages.0.0.ffn_norm.weight: string
                child 13, model.acoustic_tokenizer.decoder.stages.0.0.gamma: string
                child 14, model.acoustic_tokenizer.decoder.stages.0.0.mixer.conv.conv.conv.bias: string
                child 15, model.acoustic_tokenizer.decoder.stages.0.0.mixer.conv.conv.conv.weight: string
                child 16, model.acoustic_tokenizer.decoder.stages.0.0.norm.weight: string
                child 17, model.acoustic_tokenizer.decoder.stages.0.1.ffn.linear1.bia
              ...
               int64, max_segments: int64, acoustic_dim: int64, semantic_di (... 9 chars omitted)
                    child 0, max_seq_len: int64
                    child 1, max_latents: int64
                    child 2, max_segments: int64
                    child 3, acoustic_dim: int64
                    child 4, semantic_dim: int64
                child 3, preprocess_metadata: struct<model_name_or_path: string, processor_name_or_path: string, compress_ratio: int64, acoustic_d (... 408 chars omitted)
                    child 0, model_name_or_path: string
                    child 1, processor_name_or_path: string
                    child 2, compress_ratio: int64
                    child 3, acoustic_dim: int64
                    child 4, semantic_dim: int64
                    child 5, fix_std: double
                    child 6, latent_dtype: string
                    child 7, speech_scaling_factor: double
                    child 8, speech_bias_factor: double
                    child 9, scaling_source: string
                    child 10, corpus_latent_mean: double
                    child 11, corpus_latent_var: double
                    child 12, shapes: struct<max_seq_len: int64, max_latents: int64, max_segments: int64, acoustic_dim: int64, semantic_di (... 9 chars omitted)
                        child 0, max_seq_len: int64
                        child 1, max_latents: int64
                        child 2, max_segments: int64
                        child 3, acoustic_dim: int64
                        child 4, semantic_dim: int64
                    child 13, pad_token_id: int64
                    child 14, augment_target_silence: bool
                    child 15, normalize_target_audio: bool
              components_merged: list<item: string>
                child 0, item: string
              checkpoint_dir: string
              tensors_changed_vs_base: int64
              base_model: string
              dtype: string
              to
              {'base_model': Value('string'), 'checkpoint_dir': Value('string'), 'dtype': Value('string'), 'components_merged': List(Value('string')), 'tensors_changed_vs_base': Value('int64'), 'training_state': {'step': Value('int64'), 'args': {'model_name_or_path': Value('string'), 'data_dir': Value('string'), 'eval_data_dir': Value('null'), 'output_dir': Value('string'), 'lazy_data': Value('bool'), 'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'buckets': Value('null'), 'auto_buckets': Value('int64'), 'per_device_batch_size': Value('int64'), 'gradient_accumulation_steps': Value('int64'), 'learning_rate': Value('float64'), 'head_lr_multiplier': Value('float64'), 'weight_decay': Value('float64'), 'adam_beta1': Value('float64'), 'adam_beta2': Value('float64'), 'adam_eps': Value('float64'), 'max_grad_norm': Value('float64'), 'num_train_epochs': Value('float64'), 'max_steps': Value('int64'), 'warmup_ratio': Value('float64'), 'warmup_steps': Value('int64'), 'lr_scheduler': Value('string'), 'min_lr_ratio': Value('float64'), 'seed': Value('int64'), 'ce_loss_weight': Value('float64'), 'diffusion_loss_weight': Value('float64'), 'ddpm_batch_mul': Value('int64'), 'ce_chunk_size': Value('int64'), 'no_semantic': Value('bool'), 'no_latent_noise': Value('bool'), 'freeze_components': Value('null'), 'freeze_llm_layers': Value('null'), 'train_llm_layers': Value('null'), 'freeze_head_layers': Value('null'), 'freeze_embeddings': Value('bool'), 'freeze_lm_head': Value('bool'), 'freeze_regex': Value('null'), 'bf16': Value('bool'), 'gradient_checkpointing': Value('bool'), 'no_spmd': Value('bool'), 'logging_steps': Value('int64'), 'save_steps': Value('int64'), 'save_total_limit': Value('int64'), 'eval_steps': Value('int64'), 'eval_batches': Value('int64'), 'resume_from_checkpoint': Value('null'), 'dataloader_workers': Value('int64'), 'profile_first_steps': Value('int64')}, 'shapes': {'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64')}, 'preprocess_metadata': {'model_name_or_path': Value('string'), 'processor_name_or_path': Value('string'), 'compress_ratio': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64'), 'fix_std': Value('float64'), 'latent_dtype': Value('string'), 'speech_scaling_factor': Value('float64'), 'speech_bias_factor': Value('float64'), 'scaling_source': Value('string'), 'corpus_latent_mean': Value('float64'), 'corpus_latent_var': Value('float64'), 'shapes': {'max_seq_len': Value('int64'), 'max_latents': Value('int64'), 'max_segments': Value('int64'), 'acoustic_dim': Value('int64'), 'semantic_dim': Value('int64')}, 'pad_token_id': Value('int64'), 'augment_target_silence': Value('bool'), 'normalize_target_audio': Value('bool')}}}
              because column names don't match