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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) |