Deploy Triton Inference Server on Railway

import numpy as np from pytriton.decorators import batch from pytriton.model_config import ModelConfig, Tensor from pytriton.triton import Triton @batch def _add_sub(**inputs): a_batch, b_batch = inputs.values() add_batch = a_batch + b_batch sub_batch = a_batch - b_batch return {"add": add_batch, "sub": sub_batch} with Triton() as triton: print("Loading AddSub model") triton.bind( model_name="AddSub", infer_func=_add_sub, inputs=[ Tensor(name="input_a", dtype=np.float32, shape=(-1,)), Tensor(name="input_b", dtype=np.float32, shape=(-1,)), ], outputs=[ Tensor(name="add", dtype=np.float32, shape=(-1,)), Tensor(name="sub", dtype=np.float32, shape=(-1,)), ], config=ModelConfig(max_batch_size=128), strict=True, ) print("Serving model") triton.serve() Starts the Triton Inference Server Loads…