import os
from pathlib import Path
import unittest
import numpy as np
from onnx import helper, onnx_pb as onnx_proto
import onnxruntime as _ort
from onnxruntime_extensions import (
onnx_op,
enable_custom_op,
PyCustomOpDef,
expand_onnx_inputs,
get_library_path as _get_library_path)
def _create_test_model(intput_dims, output_dims):
nodes = []
nodes[0:] = [helper.make_node('Identity', ['input_1'], ['identity1'])]
nodes[1:] = [helper.make_node(
'StringLength', ['identity1'], ['customout'], domain='ai.onnx.contrib')]
input0 = helper.make_tensor_value_info(
'input_1', onnx_proto.TensorProto.STRING, [None] * intput_dims)
output0 = helper.make_tensor_value_info(
'customout', onnx_proto.TensorProto.INT64, [None] * output_dims)
graph = helper.make_graph(nodes, 'test0', [input0], [output0])
model = helper.make_model(
graph, opset_imports=[helper.make_operatorsetid("", 12)])
return model
def _run_string_length(input):
model = _create_test_model(input.ndim, input.ndim)
so = _ort.SessionOptions()
so.register_custom_ops_library(_get_library_path())
sess = _ort.InferenceSession(model.SerializeToString(), so)
result = sess.run(None, {'input_1': input})
# verify
output = np.array([len(elem) for elem in input.flatten()], dtype=np.int64).reshape(input.shape)
np.testing.assert_array_equal(result, [output])
class TestStringLength(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
def test_vector_to_(self):
_run_string_length(input=np.array(["a", "ab", "abc", "abcd"]))
_run_string_length(input=np.array([" \t\n", ",.", "~!@#$%^&*()_+{}|:\"<>?[]\\;',./", "1234567890"]))
_run_string_length(input=np.array([["we", "test", "whether"], ["it", "could", "output"], ["the", "same", "shape"]]))
_run_string_length(input=np.array(["d(・`ω´・d*)", "(σ`д′)σ", "(;゚∀゚)=3ハァハァ", "(´థ౪థ)σ", "||ヽ(* ̄▽ ̄*)ノミ|Ю"]))
_run_string_length(input=np.array(["你", "好", "这是一个", "测试", ]))
_run_string_length(input=np.array(["すみません、これはテストです。"]))
_run_string_length(input=np.array(["Bonjour, c'est un test."]))
_run_string_length(input=np.array(["Hallo, das ist ein Test."]))
_run_string_length(input=np.array([" مرحبا هذا هو اختبار "]))
_run_string_length(input=np.array(["👾 🤖 🎃 😺 😸 😹 😻 😼 😽 🙀 😿 😾"]))
_run_string_length(input=np.array(["龖龘讋"]))
if __name__ == "__main__":
unittest.main()microsoft/onnxruntime-extensions
Publicmirrored fromhttps://github.com/microsoft/onnxruntime-extensionsAvailable
test/test_string_length.py
65lines · modepreview