1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
|
# 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)
|
