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Copy file name to clipboardExpand all lines: cloudbuild/subsystembenchmarks/subsystembenchmarks_schema.json
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"fields": [
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{"name": "benchmark_case_id", "type": "STRING", "description": "Stable benchmark case identifier encoding every swept parameter."},
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{"name": "benchmark_group", "type": "STRING", "description": "pytest-benchmark's group label, which publish_case_metadata sets to the case scenario: read for dataloading, checkpoint_write for checkpointing. Same value as workload_scenario; filter on workload_family and workload_implementation to tell the loaders within a subsystem apart."},
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{"name": "workload_implementation", "type": "STRING", "description": "Library or integration executing the workload, matching the run.py --group suffix: huggingface_datasets, webdataset, or pytorch_lightning."},
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{"name": "workload_implementation", "type": "STRING", "description": "Library or integration executing the workload, matching the run.py --group suffix: huggingface_datasets, webdataset, pytorch_lightning, or ray_data."},
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{"name": "workload_scenario", "type": "STRING", "description": "Operation exercised within the workload implementation, named by the scenario in the group's configs.yaml: read for dataloading, checkpoint_write for checkpointing."},
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{"name": "config_sweep_axis", "type": "STRING", "description": "Configuration axis that produced this case, or baseline for the implicit baseline case."},
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{"name": "workload_family", "type": "STRING", "description": "Broad benchmark row family: data_loading or checkpointing. With workload_implementation it identifies the runnable group, which benchmark_group also carries verbatim (note data_loading here against the dataloading directory the group name uses)."},
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{"name": "requirements_resolved", "type": "STRING", "description": "JSON list from pip describing final installed distribution names and resolved versions."},
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{"name": "config_sweep_axes_requested", "type": "STRING", "description": "Normalized requested config sweep axes, or all when the complete group was selected; baseline is included automatically."},
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{"name": "measurement_round_count", "type": "INTEGER", "description": "Number of measured rounds represented by the round-duration statistics. A round is one timed unit of the workload: one full-corpus iteration for dataloading, one checkpoint operation for checkpointing."},
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{"name": "dataloader_num_workers", "type": "INTEGER", "description": "Populated by dataloading. DataLoader worker process count per distributed rank; 0 means in-process loading. Shared name with the macrobenchmarks schema."},
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{"name": "dataloader_num_workers", "type": "INTEGER", "description": "Populated by dataloading. DataLoader worker process count per distributed rank (or Ray Data reader task concurrency); 0 means in-process loading or library-default concurrency. Shared name with the macrobenchmarks schema."},
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{"name": "batch_size_samples", "type": "INTEGER", "description": "Populated by dataloading. Number of samples yielded per data batch."},
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{"name": "sample_sequence_length_tokens", "type": "INTEGER", "description": "Populated by dataloading/huggingface_datasets. Number of tokens in each generated dataset sample."},
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{"name": "sample_sequence_length_tokens", "type": "INTEGER", "description": "Populated by dataloading/huggingface_datasets and dataloading/ray_data. Number of tokens in each generated dataset sample."},
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{"name": "dataset_format", "type": "STRING", "description": "Populated by dataloading. On-GCS representation of the generated dataset, pairing stored payload with container: pretok_parquet, text_parquet, pretok_jsonl, image_tar_jpeg, image_tar_png, image_tar_npy, or image_tar_gz_jpeg. Image payload encoding rides here rather than in a column of its own, matching how pretok_ and text_ already distinguish payloads sharing a container."},
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{"name": "parquet_row_group_size_rows", "type": "INTEGER", "description": "Populated by dataloading/huggingface_datasets. Number of rows per Parquet row group; not applicable to non-Parquet formats."},
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{"name": "parquet_row_group_size_rows", "type": "INTEGER", "description": "Populated by dataloading/huggingface_datasets and dataloading/ray_data. Number of rows per Parquet row group; not applicable to non-Parquet formats."},
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{"name": "dataset_file_count", "type": "INTEGER", "description": "Populated by dataloading. Number of files in the generated dataset."},
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{"name": "dataset_size_bytes", "type": "INTEGER", "description": "Populated by dataloading. Total stored size in bytes of the generated GCS dataset objects. Shared name with the macrobenchmarks schema."},
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{"name": "dataset_sample_count", "type": "INTEGER", "description": "Populated by dataloading. Total number of samples in the generated dataset; every measured round must yield this count."},
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