Add post-process labels stage #4
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pmhalvor
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pmhalvor
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Oct 5, 2024
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| def create_dataset(dataset_id): | ||
| try: | ||
| dataset_path = f"{client.project}.{dataset_id}" | ||
| dataset = bigquery.Dataset(dataset_path) | ||
| dataset.location = "US" | ||
| dataset = client.create_dataset(dataset, timeout=30) | ||
| print(f"Created dataset {client.project}.{dataset.dataset_id}") | ||
| except Conflict as e: | ||
| if "Already Exists" in str(e): | ||
| dataset = client.get_dataset(dataset_id) | ||
| print(f"Dataset {client.project}.{dataset.dataset_id} already exists. Continuing.") | ||
| else: | ||
| raise e | ||
|
|
||
| return dataset |
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Swap to first check if the table exists, then try to make table only when it does not, instead of the other way around, requiring a try/except.
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| def run(args): | ||
| dataset = create_dataset(args.dataset_id) | ||
| table = create_table(dataset.dataset_id, args.table_id) | ||
| return table |
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Expand to include checks for all stags that will be writing to gcp
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Final stage of the pipeline.
Will need to decide on how and what to store in the final outputs.
If we are storing all intermediate stage outputs, we can just join on key or encounter ids, to avoid storing duplicate audio data. Only need to store encounter id and pooled-classification (average).
Need to think about this a bit before implementing.