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'])