Parallelizing inputs to ONNX model
I am trying to run inference using ONNX Model and I want to give multiple inputs to the model and expect it to generate a list of the outputs, is it possible?Example :inputs = tokenizer([“Using RoBERTa with ONNX Runtime!”, “Hello”, ‘Whats up’]), return_tensors=‘np’)modified_inps = {‘input_ids’ : [np.array(inp, dtype=np.int64) for inp in inputs[‘input_ids’]],‘attention_mask’ : [np.array(mask, dtype=np.int64) for mask in inputs[‘attention_mask’]]}outputs = session.run(output_names=[“logits”], input_feed=modified_inps)Expected Output:[[<logit_0>, <logit_1>],[<logit_0>, <logit_1>],[<logit_0>, <logit_1>]]