burn-tensor 0.16.1

Tensor library with user-friendly APIs and automatic differentiation support
Documentation 
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
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262

#[burn_tensor_testgen::testgen(repeat)]
mod tests {
    use super::*;
    use burn_tensor::{backend::Backend, Bool, Int, Tensor, TensorData};

    #[test]
    fn should_support_repeat_ops_one_dimension() {
        let data = TensorData::from([[0.0f32, 1.0f32, 2.0f32]]);
        let tensor = TestTensor::<2>::from_data(data, &Default::default());

        let output = tensor.repeat(&[4, 1, 1]);
        let expected = TensorData::from([
            [0.0f32, 1.0f32, 2.0f32],
            [0.0f32, 1.0f32, 2.0f32],
            [0.0f32, 1.0f32, 2.0f32],
            [0.0f32, 1.0f32, 2.0f32],
        ]);

        output.into_data().assert_eq(&expected, false);
    }

    #[test]
    fn should_support_bool_repeat_ops_one_dimension() {
        let data = TensorData::from([[true, false, false]]);
        let tensor = TestTensorBool::<2>::from_data(data, &Default::default());

        let output = tensor.repeat(&[4, 1, 1]);
        let expected = TensorData::from([
            [true, false, false],
            [true, false, false],
            [true, false, false],
            [true, false, false],
        ]);
        output.into_data().assert_eq(&expected, true);
    }

    #[test]
    fn should_support_int_repeat_ops_one_dimension() {
        let data = TensorData::from([[0i32, 1i32, 2i32]]);
        let tensor = TestTensorInt::<2>::from_data(data, &Default::default());

        let output = tensor.repeat(&[4, 1, 1]);
        let expected = TensorData::from([
            [0i32, 1i32, 2i32],
            [0i32, 1i32, 2i32],
            [0i32, 1i32, 2i32],
            [0i32, 1i32, 2i32],
        ]);

        output.into_data().assert_eq(&expected, false);
    }

    #[test]
    fn should_support_float_repeat_repeating_on_many_dimensions() {
        let data = TensorData::from([
            [[1.0f32, 2.0f32], [3.0f32, 4.0f32]],
            [[5.0f32, 6.0f32], [7.0f32, 8.0f32]],
            [[9.0f32, 10.0f32], [11.0f32, 12.0f32]],
            [[13.0f32, 14.0f32], [15.0f32, 16.0f32]],
        ]);
        let tensor = TestTensor::<3>::from_data(data, &Default::default());

        let output = tensor.repeat(&[2, 3, 2]);
        let expected = TensorData::from([
            [
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
            ],
            [
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
            ],
            [
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
            ],
            [
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
            ],
            [
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
                [1.0f32, 2.0f32, 1.0f32, 2.0f32],
                [3.0f32, 4.0f32, 3.0f32, 4.0f32],
            ],
            [
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
                [5.0f32, 6.0f32, 5.0f32, 6.0f32],
                [7.0f32, 8.0f32, 7.0f32, 8.0f32],
            ],
            [
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
                [9.0f32, 10.0f32, 9.0f32, 10.0f32],
                [11.0f32, 12.0f32, 11.0f32, 12.0f32],
            ],
            [
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
                [13.0f32, 14.0f32, 13.0f32, 14.0f32],
                [15.0f32, 16.0f32, 15.0f32, 16.0f32],
            ],
        ]);

        output.into_data().assert_eq(&expected, false);
    }

    #[test]
    fn should_support_int_repeat_on_many_dims() {
        let data = TensorData::from([
            [[1i32, 2i32], [3i32, 4i32]],
            [[5i32, 6i32], [7i32, 8i32]],
            [[9i32, 10i32], [11i32, 12i32]],
            [[13i32, 14i32], [15i32, 16i32]],
        ]);
        let tensor = TestTensorInt::<3>::from_data(data, &Default::default());

        let output = tensor.repeat(&[2, 3, 2]);

        let expected = TensorData::from([
            [
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
            ],
            [
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
            ],
            [
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
            ],
            [
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
            ],
            [
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
                [1i32, 2i32, 1i32, 2i32],
                [3i32, 4i32, 3i32, 4i32],
            ],
            [
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
                [5i32, 6i32, 5i32, 6i32],
                [7i32, 8i32, 7i32, 8i32],
            ],
            [
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
                [9i32, 10i32, 9i32, 10i32],
                [11i32, 12i32, 11i32, 12i32],
            ],
            [
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
                [13i32, 14i32, 13i32, 14i32],
                [15i32, 16i32, 15i32, 16i32],
            ],
        ]);

        output.into_data().assert_eq(&expected, false);
    }

    #[test]
    fn should_support_bool_repeat_on_many_dimension() {
        let data = TensorData::from([
            [[false, true], [true, false]],
            [[true, true], [false, false]],
        ]);
        let tensor = TestTensorBool::<3>::from_data(data, &Default::default());

        let output = tensor.repeat(&[2, 3, 2]);
        let expected = TensorData::from([
            [
                [false, true, false, true],
                [true, false, true, false],
                [false, true, false, true],
                [true, false, true, false],
                [false, true, false, true],
                [true, false, true, false],
            ],
            [
                [true, true, true, true],
                [false, false, false, false],
                [true, true, true, true],
                [false, false, false, false],
                [true, true, true, true],
                [false, false, false, false],
            ],
            [
                [false, true, false, true],
                [true, false, true, false],
                [false, true, false, true],
                [true, false, true, false],
                [false, true, false, true],
                [true, false, true, false],
            ],
            [
                [true, true, true, true],
                [false, false, false, false],
                [true, true, true, true],
                [false, false, false, false],
                [true, true, true, true],
                [false, false, false, false],
            ],
        ]);

        output.into_data().assert_eq(&expected, true);
    }
}