def test_onnxt_runtime_shape(self):
x = numpy.random.randn(20, 2).astype(numpy.float32)
y = x.shape
onx = OnnxShape('X', output_names=['Y'])
model_def = onx.to_onnx({'X': x.astype(numpy.float32)})
got = OnnxInference(model_def).run({'X': x})
self.assertEqualArray(y, got['Y'])
def test_onnx_micro_runtime_shape(self):
opset = TestOnnxMicroRuntime.opset
x = numpy.array([1, 2, 4, 5, 5, 4]).astype(numpy.float32).reshape(
(3, 2))
cop = OnnxShape('X', op_version=opset, output_names=['Y'])
model_def = cop.to_onnx({'X': x}, target_opset=opset)
rt = OnnxMicroRuntime(model_def)
out = rt.run({'X': x})
self.assertEqual(numpy.array(x.shape, dtype=numpy.int64), out['Y'])
