[CI] several tests for modifier failed

```py
FAILED tests/modifier_speed_test.py::ModifierForwardTester::test_shufflenet - RuntimeError: Given groups=1, weight of size [12, 11, 1, 1], expected input[1, 12, 28, 28] to have 11 channels, but got 12 channels instead
FAILED tests/modifier_torchvision_test.py::TestModel::test_torchvision_model_inception_v3 - AssertionError
FAILED tests/modifier_torchvision_test.py::TestModel::test_torchvision_model_shufflenet_v2_x0_5 - RuntimeError: Given groups=1, weight of size [12, 11, 1, 1], expected input[1, 12, 28, 28] to have 11 channels, but got 12 channels instead
FAILED tests/modifier_torchvision_test.py::TestModel::test_torchvision_model_shufflenet_v2_x1_0 - RuntimeError: Given groups=1, weight of size [29, 28, 1, 1], expected input[1, 29, 28, 28] to have 28 channels, but got 29 channels instead
FAILED tests/modifier_torchvision_test.py::TestModel::test_torchvision_model_shufflenet_v2_x1_5 - RuntimeError: Given groups=1, weight of size [44, 43, 1, 1], expected input[1, 44, 28, 28] to have 43 channels, but got 44 channels instead
FAILED tests/modifier_torchvision_test.py::TestModel::test_torchvision_model_shufflenet_v2_x2_0 - RuntimeError: Given groups=1, weight of size [61, 60, 1, 1], expected input[1, 61, 28, 28] to have 60 channels, but got 61 channels instead
```

Start by running the failures in tests/modifier_speed_test.py and tests/modifier_torchvision_test.py, focusing on the ShuffleNet and Inception cases. Trace the modifier behavior exercised by those tests and compare the reported channel mismatch and assertion failures. Done means the listed tests pass without regressions.

Written by the indexing model from the issue text.