# Copyright (c) Microsoft Corporation. # Licensed under the MIT License. import unittest import numpy as np import parameterized import onnxscript import onnxscript.evaluator import onnxscript.tensor from onnxscript import opset17 as op from onnxscript import script @parameterized.parameterized_class( ( "name", "evaluator", ), [ ( "reference_runtime", onnxscript.evaluator.OnnxReferenceRuntimeEvaluator(), ), ( "onnxruntime", onnxscript.evaluator.ORTEvaluator(), ), ], ) class EagerModeTest(unittest.TestCase): evaluator: onnxscript.evaluator.Evaluator def setUp(self): self.default_evaluator = onnxscript.evaluator.default() onnxscript.evaluator.set_default(self.evaluator) def tearDown(self): onnxscript.evaluator.set_default(self.default_evaluator) def test_sequence_input(self): @script() def Concat(seq): return op.ConcatFromSequence(seq, axis=0) np_array = np.array([1, 2, 3], dtype=np.float32) output1 = Concat([np_array, np_array]) self.assertIsInstance(output1, np.ndarray) os_tensor = onnxscript.tensor.Tensor(np_array) output2 = Concat([os_tensor, os_tensor]) self.assertIsInstance(output2, onnxscript.tensor.Tensor) @script() def add_with_alpha(this, other, alpha: float = 1.0): alpha = op.CastLike(alpha, other) other = op.Mul(other, alpha) return op.Add(this, other) @parameterized.parameterized_class( ( "name", "evaluator", ), [ ( "reference_runtime", onnxscript.evaluator.OnnxReferenceRuntimeEvaluator(), ), ( "onnxruntime", onnxscript.evaluator.ORTEvaluator(), ), ], ) class TestEagerModeArguments(unittest.TestCase): evaluator: onnxscript.evaluator.Evaluator def setUp(self): self.default_evaluator = onnxscript.evaluator.default() onnxscript.evaluator.set_default(self.evaluator) def tearDown(self): onnxscript.evaluator.set_default(self.default_evaluator) def test_op_some_input_by_kwargs(self): self.assertEqual(op.Add(1, B=2), 3) def test_op_all_input_by_kwargs(self): self.assertEqual(op.Add(A=1, B=2), 3) def test_op_attribute_by_positional_args(self): data = np.array([1, 2, 3, 4, 5, 6], dtype=np.int32) axes = np.array([0], dtype=np.int64) self.assertEqual(op.ReduceSum(data, axes, keepdims=True), 21) def test_op_input_and_attribute_by_kwargs_out_of_order(self): data = np.array([1, 2, 3, 4, 5, 6], dtype=np.int32) axes = np.array([0], dtype=np.int64) self.assertEqual(op.ReduceSum(keepdims=True, axes=axes, data=data), 21) def test_function_some_input_by_kwargs(self): self.assertEqual(add_with_alpha(1.0, other=2.0), 3.0) def test_function_all_input_by_kwargs(self): self.assertEqual(add_with_alpha(this=1.0, other=2.0), 3.0) def test_function_attribute_by_positional_args(self): self.assertEqual(add_with_alpha(1.0, 2.0, 3.0), 7.0) def test_function_input_and_attribute_by_kwargs_out_of_order(self): self.assertEqual(add_with_alpha(alpha=3.0, other=2.0, this=1.0), 7.0) if __name__ == "__main__": unittest.main(verbosity=2)