Update app.py
Browse files
app.py
CHANGED
@@ -72,14 +72,12 @@ def predict(cfg, sequence):
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cfg.max_length += 1
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seed_everything(cfg.seed)
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-
error
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df = pd.DataFrame({cfg.sequence_col: [sequence]})
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tokenizer = AutoTokenizer.from_pretrained(
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cfg.model_path, padding_side=cfg.padding_side
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)
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cfg.tokenizer = tokenizer
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-
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dataset = PLTNUMDataset(cfg, df, train=False)
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dataloader = DataLoader(
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dataset,
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@@ -93,7 +91,6 @@ def predict(cfg, sequence):
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model = PLTNUM_PreTrainedModel.from_pretrained(cfg.model_path, cfg=cfg)
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model.to(cfg.device)
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# predictions = predict_fn(loader, model, cfg)
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model.eval()
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predictions = []
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@@ -110,7 +107,7 @@ def predict(cfg, sequence):
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outputs = {}
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outputs["raw prediction values"] = predictions
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outputs["binary prediction values"] = [1 if x > 0.5 else 0 for x in predictions]
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return outputs
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# Gradio Interface
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cfg.max_length += 1
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seed_everything(cfg.seed)
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df = pd.DataFrame({cfg.sequence_col: [sequence]})
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tokenizer = AutoTokenizer.from_pretrained(
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cfg.model_path, padding_side=cfg.padding_side
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)
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cfg.tokenizer = tokenizer
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dataset = PLTNUMDataset(cfg, df, train=False)
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dataloader = DataLoader(
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dataset,
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model = PLTNUM_PreTrainedModel.from_pretrained(cfg.model_path, cfg=cfg)
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model.to(cfg.device)
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model.eval()
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predictions = []
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outputs = {}
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outputs["raw prediction values"] = predictions
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outputs["binary prediction values"] = [1 if x > 0.5 else 0 for x in predictions]
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+
return str(outputs)
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# Gradio Interface
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