Spaces:
Running
Running
made progress bar optional
Browse filesPREVIOUSLY:
progress bar always showed
NOW:
progress using 'verbose=False' argument disables progress bar
semncg.py
CHANGED
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@@ -415,7 +415,7 @@ class SemNCG(evaluate.Metric):
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`tokenize_sentences`=False -> references: List[List[str]]
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k (int, optional): The rank threshold used for evaluating gains (typically top-k sentences). Default is 3.
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gpu (DEVICE_TYPE, optional): Whether to use GPU for computation. Default is False.
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verbose (bool, optional): Whether to print verbose logs. Default is False.
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batch_size (int, optional): The batch size for encoding sentences. Default is 32.
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tokenize_sentences (bool, optional): Whether to tokenize sentences. If True, sentences are tokenized before
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processing. Default is True.
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@@ -484,7 +484,10 @@ class SemNCG(evaluate.Metric):
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iterable_obj = zip(predictions, references, documents)
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out = []
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for idx, (pred, ref, doc) in tqdm(
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if not pre_compute_embeddings: # Compute embeddings
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ref_sentences = tokenize_and_prep_document(ref, tokenize_sentences)
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`tokenize_sentences`=False -> references: List[List[str]]
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k (int, optional): The rank threshold used for evaluating gains (typically top-k sentences). Default is 3.
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gpu (DEVICE_TYPE, optional): Whether to use GPU for computation. Default is False.
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verbose (bool, optional): Whether to print verbose logs and use a progress bar. Default is False.
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batch_size (int, optional): The batch size for encoding sentences. Default is 32.
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tokenize_sentences (bool, optional): Whether to tokenize sentences. If True, sentences are tokenized before
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processing. Default is True.
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iterable_obj = zip(predictions, references, documents)
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out = []
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for idx, (pred, ref, doc) in tqdm(
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enumerate(iterable_obj),
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total=N,
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disable=not verbose):
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if not pre_compute_embeddings: # Compute embeddings
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ref_sentences = tokenize_and_prep_document(ref, tokenize_sentences)
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