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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
name: string
backend: struct<name: string, version: string, _target_: string, task: string, library: string, model_type: s (... 667 chars omitted)
child 0, name: string
child 1, version: string
child 2, _target_: string
child 3, task: string
child 4, library: string
child 5, model_type: string
child 6, model: string
child 7, processor: string
child 8, device: string
child 9, device_ids: null
child 10, seed: int64
child 11, inter_op_num_threads: null
child 12, intra_op_num_threads: null
child 13, model_kwargs: struct<>
child 14, processor_kwargs: struct<>
child 15, no_weights: bool
child 16, device_map: null
child 17, torch_dtype: null
child 18, eval_mode: bool
child 19, to_bettertransformer: bool
child 20, low_cpu_mem_usage: null
child 21, attn_implementation: null
child 22, cache_implementation: null
child 23, autocast_enabled: bool
child 24, autocast_dtype: null
child 25, torch_compile: bool
child 26, torch_compile_target: string
child 27, torch_compile_config: struct<>
child 28, quantization_scheme: null
child 29, quantization_config: struct<>
child 30, deepspeed_inference: bool
child 31, deepspeed_inference_config: struct<>
child 32, peft_type: null
child 33, peft_config: struct<>
scenario: struct<name: string, _target_: string, max_steps: int64, warmup_steps: int64, dataset_shapes: struct (... 466 chars omitted)
child 0, name: string
child 1, _target_: string
child 2, max_steps: int64
child 3, wa
...
hild 9, stdev: double
child 10, stdev_: double
child 2, throughput: struct<unit: string, value: double>
child 0, unit: string
child 1, value: double
child 3, energy: null
child 4, efficiency: null
child 2, train: struct<memory: struct<unit: string, max_ram: double, max_global_vram: null, max_process_vram: null, (... 307 chars omitted)
child 0, memory: struct<unit: string, max_ram: double, max_global_vram: null, max_process_vram: null, max_reserved: n (... 25 chars omitted)
child 0, unit: string
child 1, max_ram: double
child 2, max_global_vram: null
child 3, max_process_vram: null
child 4, max_reserved: null
child 5, max_allocated: null
child 1, latency: struct<unit: string, values: list<item: double>, count: int64, total: double, mean: double, p50: dou (... 74 chars omitted)
child 0, unit: string
child 1, values: list<item: double>
child 0, item: double
child 2, count: int64
child 3, total: double
child 4, mean: double
child 5, p50: double
child 6, p90: double
child 7, p95: double
child 8, p99: double
child 9, stdev: double
child 10, stdev_: double
child 2, throughput: struct<unit: string, value: double>
child 0, unit: string
child 1, value: double
child 3, energy: null
child 4, efficiency: null
to
{'config': {'name': Value('string'), 'backend': {'name': Value('string'), 'version': Value('string'), '_target_': Value('string'), 'task': Value('string'), 'library': Value('string'), 'model_type': Value('string'), 'model': Value('string'), 'processor': Value('string'), 'device': Value('string'), 'device_ids': Value('null'), 'seed': Value('int64'), 'inter_op_num_threads': Value('null'), 'intra_op_num_threads': Value('null'), 'model_kwargs': {}, 'processor_kwargs': {}, 'no_weights': Value('bool'), 'device_map': Value('null'), 'torch_dtype': Value('null'), 'eval_mode': Value('bool'), 'to_bettertransformer': Value('bool'), 'low_cpu_mem_usage': Value('null'), 'attn_implementation': Value('null'), 'cache_implementation': Value('null'), 'autocast_enabled': Value('bool'), 'autocast_dtype': Value('null'), 'torch_compile': Value('bool'), 'torch_compile_target': Value('string'), 'torch_compile_config': {}, 'quantization_scheme': Value('null'), 'quantization_config': {}, 'deepspeed_inference': Value('bool'), 'deepspeed_inference_config': {}, 'peft_type': Value('null'), 'peft_config': {}}, 'scenario': {'name': Value('string'), '_target_': Value('string'), 'max_steps': Value('int64'), 'warmup_steps': Value('int64'), 'dataset_shapes': {'dataset_size': Value('int64'), 'sequence_length': Value('int64'), 'num_choices': Value('int64')}, 'training_arguments': {'per_device_train_batch_size': Value('int64'), 'gradient_accumulation_steps': Value('int64'), 'output_dir': Value('string'), 'evaluation
...
: Value('float64')}, 'energy': {'unit': Value('string'), 'cpu': Value('float64'), 'ram': Value('float64'), 'gpu': Value('int64'), 'total': Value('float64')}, 'efficiency': {'unit': Value('string'), 'value': Value('float64')}}, 'warmup': {'memory': {'unit': Value('string'), 'max_ram': Value('float64'), 'max_global_vram': Value('null'), 'max_process_vram': Value('null'), 'max_reserved': Value('null'), 'max_allocated': Value('null')}, 'latency': {'unit': Value('string'), 'values': List(Value('float64')), 'count': Value('int64'), 'total': Value('float64'), 'mean': Value('float64'), 'p50': Value('float64'), 'p90': Value('float64'), 'p95': Value('float64'), 'p99': Value('float64'), 'stdev': Value('float64'), 'stdev_': Value('float64')}, 'throughput': {'unit': Value('string'), 'value': Value('float64')}, 'energy': Value('null'), 'efficiency': Value('null')}, 'train': {'memory': {'unit': Value('string'), 'max_ram': Value('float64'), 'max_global_vram': Value('null'), 'max_process_vram': Value('null'), 'max_reserved': Value('null'), 'max_allocated': Value('null')}, 'latency': {'unit': Value('string'), 'values': List(Value('float64')), 'count': Value('int64'), 'total': Value('float64'), 'mean': Value('float64'), 'p50': Value('float64'), 'p90': Value('float64'), 'p95': Value('float64'), 'p99': Value('float64'), 'stdev': Value('float64'), 'stdev_': Value('float64')}, 'throughput': {'unit': Value('string'), 'value': Value('float64')}, 'energy': Value('null'), 'efficiency': Value('null')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 289, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 124, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
name: string
backend: struct<name: string, version: string, _target_: string, task: string, library: string, model_type: s (... 667 chars omitted)
child 0, name: string
child 1, version: string
child 2, _target_: string
child 3, task: string
child 4, library: string
child 5, model_type: string
child 6, model: string
child 7, processor: string
child 8, device: string
child 9, device_ids: null
child 10, seed: int64
child 11, inter_op_num_threads: null
child 12, intra_op_num_threads: null
child 13, model_kwargs: struct<>
child 14, processor_kwargs: struct<>
child 15, no_weights: bool
child 16, device_map: null
child 17, torch_dtype: null
child 18, eval_mode: bool
child 19, to_bettertransformer: bool
child 20, low_cpu_mem_usage: null
child 21, attn_implementation: null
child 22, cache_implementation: null
child 23, autocast_enabled: bool
child 24, autocast_dtype: null
child 25, torch_compile: bool
child 26, torch_compile_target: string
child 27, torch_compile_config: struct<>
child 28, quantization_scheme: null
child 29, quantization_config: struct<>
child 30, deepspeed_inference: bool
child 31, deepspeed_inference_config: struct<>
child 32, peft_type: null
child 33, peft_config: struct<>
scenario: struct<name: string, _target_: string, max_steps: int64, warmup_steps: int64, dataset_shapes: struct (... 466 chars omitted)
child 0, name: string
child 1, _target_: string
child 2, max_steps: int64
child 3, wa
...
hild 9, stdev: double
child 10, stdev_: double
child 2, throughput: struct<unit: string, value: double>
child 0, unit: string
child 1, value: double
child 3, energy: null
child 4, efficiency: null
child 2, train: struct<memory: struct<unit: string, max_ram: double, max_global_vram: null, max_process_vram: null, (... 307 chars omitted)
child 0, memory: struct<unit: string, max_ram: double, max_global_vram: null, max_process_vram: null, max_reserved: n (... 25 chars omitted)
child 0, unit: string
child 1, max_ram: double
child 2, max_global_vram: null
child 3, max_process_vram: null
child 4, max_reserved: null
child 5, max_allocated: null
child 1, latency: struct<unit: string, values: list<item: double>, count: int64, total: double, mean: double, p50: dou (... 74 chars omitted)
child 0, unit: string
child 1, values: list<item: double>
child 0, item: double
child 2, count: int64
child 3, total: double
child 4, mean: double
child 5, p50: double
child 6, p90: double
child 7, p95: double
child 8, p99: double
child 9, stdev: double
child 10, stdev_: double
child 2, throughput: struct<unit: string, value: double>
child 0, unit: string
child 1, value: double
child 3, energy: null
child 4, efficiency: null
to
{'config': {'name': Value('string'), 'backend': {'name': Value('string'), 'version': Value('string'), '_target_': Value('string'), 'task': Value('string'), 'library': Value('string'), 'model_type': Value('string'), 'model': Value('string'), 'processor': Value('string'), 'device': Value('string'), 'device_ids': Value('null'), 'seed': Value('int64'), 'inter_op_num_threads': Value('null'), 'intra_op_num_threads': Value('null'), 'model_kwargs': {}, 'processor_kwargs': {}, 'no_weights': Value('bool'), 'device_map': Value('null'), 'torch_dtype': Value('null'), 'eval_mode': Value('bool'), 'to_bettertransformer': Value('bool'), 'low_cpu_mem_usage': Value('null'), 'attn_implementation': Value('null'), 'cache_implementation': Value('null'), 'autocast_enabled': Value('bool'), 'autocast_dtype': Value('null'), 'torch_compile': Value('bool'), 'torch_compile_target': Value('string'), 'torch_compile_config': {}, 'quantization_scheme': Value('null'), 'quantization_config': {}, 'deepspeed_inference': Value('bool'), 'deepspeed_inference_config': {}, 'peft_type': Value('null'), 'peft_config': {}}, 'scenario': {'name': Value('string'), '_target_': Value('string'), 'max_steps': Value('int64'), 'warmup_steps': Value('int64'), 'dataset_shapes': {'dataset_size': Value('int64'), 'sequence_length': Value('int64'), 'num_choices': Value('int64')}, 'training_arguments': {'per_device_train_batch_size': Value('int64'), 'gradient_accumulation_steps': Value('int64'), 'output_dir': Value('string'), 'evaluation
...
: Value('float64')}, 'energy': {'unit': Value('string'), 'cpu': Value('float64'), 'ram': Value('float64'), 'gpu': Value('int64'), 'total': Value('float64')}, 'efficiency': {'unit': Value('string'), 'value': Value('float64')}}, 'warmup': {'memory': {'unit': Value('string'), 'max_ram': Value('float64'), 'max_global_vram': Value('null'), 'max_process_vram': Value('null'), 'max_reserved': Value('null'), 'max_allocated': Value('null')}, 'latency': {'unit': Value('string'), 'values': List(Value('float64')), 'count': Value('int64'), 'total': Value('float64'), 'mean': Value('float64'), 'p50': Value('float64'), 'p90': Value('float64'), 'p95': Value('float64'), 'p99': Value('float64'), 'stdev': Value('float64'), 'stdev_': Value('float64')}, 'throughput': {'unit': Value('string'), 'value': Value('float64')}, 'energy': Value('null'), 'efficiency': Value('null')}, 'train': {'memory': {'unit': Value('string'), 'max_ram': Value('float64'), 'max_global_vram': Value('null'), 'max_process_vram': Value('null'), 'max_reserved': Value('null'), 'max_allocated': Value('null')}, 'latency': {'unit': Value('string'), 'values': List(Value('float64')), 'count': Value('int64'), 'total': Value('float64'), 'mean': Value('float64'), 'p50': Value('float64'), 'p90': Value('float64'), 'p95': Value('float64'), 'p99': Value('float64'), 'stdev': Value('float64'), 'stdev_': Value('float64')}, 'throughput': {'unit': Value('string'), 'value': Value('float64')}, 'energy': Value('null'), 'efficiency': Value('null')}}}
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