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19 | 19 | test_data_suite: list[tuple[test_data_t]] = [ |
20 | 20 | # (test_data, dim, index) |
21 | 21 | ((torch.zeros(5, 3, 20), -1, 0),), |
22 | | - ((torch.zeros(5, 3, 20), 0, -1),), |
| 22 | + ((torch.rand(5, 3, 20), 0, -1),), |
23 | 23 | ((torch.zeros(5, 3, 20), 0, 4),), |
24 | 24 | ((torch.ones(10, 10, 10), 0, 2),), |
25 | 25 | ((torch.rand(5, 3, 20, 2), 0, 2),), |
@@ -61,9 +61,7 @@ def _test_select_tosa_MI_pipeline( |
61 | 61 | .check([export_target]) |
62 | 62 | .check_not(["torch.ops.quantized_decomposed"]) |
63 | 63 | .to_edge() |
64 | | - .dump_artifact() |
65 | 64 | .partition() |
66 | | - .dump_artifact() |
67 | 65 | .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
68 | 66 | .to_executorch() |
69 | 67 | .run_method_and_compare_outputs(inputs=test_data) |
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