NLP / test.py
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from transformers import AutoTokenizer
from onnxruntime import InferenceSession
import numpy as np
import subprocess
import os
#create onnx model using
if not os.path.exists("zs_model_onnx"):
try:
subprocess.run(['python3','-m','transformers.onnx',
'--model=facebook/bart-large-mnli',
'--feature=sequence-classification',
'zs_model_onnx/'])
except:
pass
#create session of saved onnx model
session = InferenceSession("zs_model_onnx/model.onnx")
#tokenizer for the chkpt
tokenizer=AutoTokenizer.from_pretrained('zs_model_dir')
# ONNX Runtime expects NumPy arrays as input
inputs = tokenizer("Using DistilBERT with ONNX Runtime!","you know how", return_tensors="np")
input_feed = {
"input_ids": np.array(inputs['input_ids']),
"attention_mask": np.array((inputs['attention_mask']))
}
#output
outputs = session.run(output_names=["logits"], input_feed=dict(input_feed))
print(outputs)