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| # ======= PREPARING THE PIPELINE ======= | |
| import torch | |
| import os | |
| from utils.preprocess import get_preprocess | |
| from utils.model import get_model | |
| dump_path = "./dumps/" | |
| vocab_path = os.path.join(dump_path, "vocab.pt") | |
| model_path = os.path.join(dump_path, "model.pt") | |
| params_path = os.path.join(dump_path, "params.json") | |
| preprocess = get_preprocess(vocab_path) | |
| model = get_model(model_path, params_path) | |
| def predict(text): | |
| x = preprocess(text) | |
| x = torch.tensor([x]) | |
| y = model(x) | |
| y = y.detach().numpy().tolist()[0] | |
| return y | |
| # ======= CREATING APP ======= | |
| from fastapi import FastAPI | |
| app = FastAPI() | |
| def main(text: str): | |
| return predict(text) |