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#!/usr/bin/env python3
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import os
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import sys
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import numpy as np
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os.environ["OMP_NUM_THREADS"] = "1"
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import onnxruntime as ort
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def read(sz):
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dd = []
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gt = 0
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while gt < sz * 4:
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st = os.read(0, sz * 4 - gt)
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assert(len(st) > 0)
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dd.append(st)
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gt += len(st)
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return np.frombuffer(b''.join(dd), dtype=np.float32)
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def write(d):
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os.write(1, d.tobytes())
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def run_loop(m):
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ishapes = [[1]+ii.shape[1:] for ii in m.get_inputs()]
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keys = [x.name for x in m.get_inputs()]
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print("ready to run onnx model", keys, ishapes, file=sys.stderr)
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while 1:
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inputs = []
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for shp in ishapes:
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ts = np.product(shp)
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#print("reshaping %s with offset %d" % (str(shp), offset), file=sys.stderr)
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inputs.append(read(ts).reshape(shp))
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ret = m.run(None, dict(zip(keys, inputs)))
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#print(ret, file=sys.stderr)
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for r in ret:
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write(r)
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if __name__ == "__main__":
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print(ort.get_available_providers(), file=sys.stderr)
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if 'OpenVINOExecutionProvider' in ort.get_available_providers() and 'ONNXCPU' not in os.environ:
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print("OnnxJit is using openvino", file=sys.stderr)
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options = ort.SessionOptions()
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options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
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provider = 'OpenVINOExecutionProvider'
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else:
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print("OnnxJit is using CPU", file=sys.stderr)
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options = ort.SessionOptions()
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options.intra_op_num_threads = 4
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options.inter_op_num_threads = 8
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provider = 'CPUExecutionProvider'
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ort_session = ort.InferenceSession(sys.argv[1], options)
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ort_session.set_providers([provider], None)
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run_loop(ort_session)
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