160 lines
4.0 KiB
Python
160 lines
4.0 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import itertools
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import os
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import unittest
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import onnx.backend.base
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import onnx.backend.test
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from onnx.backend.base import Device, DeviceType
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import onnx.shape_inference
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import onnx.version_converter
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import subprocess
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from pyruntime import ExecutionSession
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CXX = os.getenv('CXX')
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ONNF = os.getenv('ONNF')
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LLC = os.getenv('LLC')
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RT_DIR = os.getenv('RT_DIR')
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assert CXX and ONNF and LLC and RT_DIR, "tools path not set"
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class DummyBackend(onnx.backend.base.Backend):
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@classmethod
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def prepare(
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cls,
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model,
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device='CPU',
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**kwargs
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):
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super(DummyBackend, cls).prepare(model, device, **kwargs)
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# Save model to disk as temp_model.onnx.
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onnx.save(model, "temp_model.onnx")
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# Call frontend to process temp_model.onnx, bit code will be generated.
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subprocess.run([ONNF, "temp_model.onnx"], stdout=subprocess.PIPE)
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# Call llc to generate object file from bitcode.
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subprocess.run([LLC, "-filetype=obj", "model.bc"],
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stdout=subprocess.PIPE)
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# Generate shared library from object file, linking with c runtime.
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subprocess.run([
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CXX, "-shared", "model.o", "-o", "model.so", "-L" + RT_DIR,
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"-lcruntime"
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],
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stdout=subprocess.PIPE)
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return ExecutionSession("./model.so", "_dyn_entry_point_main_graph")
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@classmethod
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def supports_device(cls, device):
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d = Device(device)
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if d.type == DeviceType.CPU:
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return True
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return False
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backend_test = onnx.backend.test.BackendTest(DummyBackend, __name__)
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# Test directories:
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# https://github.com/onnx/onnx/tree/master/onnx/backend/test/data/node
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test_to_enable = [
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# Add Op:
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"test_add_cpu",
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"test_add_bcast_cpu",
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# And Op:
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# Sub Op:
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"test_sub_cpu",
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"test_sub_bcast_cpu",
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"test_sub_example_cpu",
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# Cosh Op:
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"test_cosh_cpu",
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"test_cosh_example_cpu",
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# Div Op:
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"test_div_cpu",
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"test_div_bcast_cpu",
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"test_div_example_cpu",
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# Elu Op:
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"test_elu_cpu",
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"test_elu_default_cpu",
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"test_elu_example_cpu",
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# Exp Op:
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"test_exp_cpu",
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"test_exp_example_cpu",
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# Hard Sigmoid Op:
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"test_hardsigmoid_cpu",
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"test_hardsigmoid_default_cpu",
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"test_hardsigmoid_example_cpu",
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# Leaky Relu Op:
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"test_leakyrelu_cpu",
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"test_leakyrelu_default_cpu",
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"test_leakyrelu_example_cpu",
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# Max Op:
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# "test_max_example_cpu", <- error
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"test_max_one_input_cpu",
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# "test_max_two_inputs_cpu", <- error
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# Min Op:
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# "test_min_example_cpu", <- error
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"test_min_one_input_cpu",
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# "test_min_two_inputs_cpu", <- error
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# Mul Op:
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"test_mul_cpu",
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"test_mul_bcast_cpu",
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"test_mul_example_cpu",
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# Relu Op:
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"test_relu_cpu",
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# Selu Op:
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"test_selu_cpu",
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"test_selu_default_cpu",
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"test_selu_example_cpu",
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# Sigmoid Op:
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"test_sigmoid_cpu",
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"test_sigmoid_example_cpu",
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# Sum Op:
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#"test_sum_example_cpu", <- error
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"test_sum_one_input_cpu",
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#"test_sum_two_inputs_cpu", <- error
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# Reciprocal Op:
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#"test_reciprocal_cpu", <- error on shape inference.
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#"test_reciprocal_example_cpu", <- error on shape inference.
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]
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# Extract name of all test cases.
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import inspect
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all_tests = inspect.getmembers(
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backend_test.test_cases["OnnxBackendNodeModelTest"])
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all_test_names = list(map(lambda x: x[0], all_tests))
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for test_name in test_to_enable:
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assert test_name in all_test_names, "test name {} not found".format(test_name)
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backend_test.include(r"^{}$".format(test_name))
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def tearDownModule():
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print()
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print("*" * 40)
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print("A total of {} tests should have run".format(len(test_to_enable)))
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print("*" * 40)
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# import all test cases at global scope to make them visible to python.unittest
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globals().update(backend_test.test_cases)
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if __name__ == '__main__':
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unittest.main()
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