crawlingcub opened a new issue, #12590:
URL: https://github.com/apache/tvm/issues/12590
The BatchNorm operator for PyTorch's frontend fails when eps is -ive. I
modiied the `test_forward_batchnorm` test in
`tests/python/frontend/pytorch/test_forward.py` by adding a -ive eps, and the
test failed. Is this expected? Does the batchnorm implementation ignore the
-ive eps value?
### Modified Test:
```python
def test_forward_batchnorm():
"""test_forward_batchnorm"""
def init_weight(m):
torch.nn.init.normal_(m.weight, 0, 0.01)
torch.nn.init.normal_(m.bias)
inp_2d = torch.rand((1, 16, 10, 10))
inp_3d = torch.rand((1, 16, 10, 10, 10))
for bn, inp in [(torch.nn.BatchNorm2d(16, eps=-1.0), inp_2d),
(torch.nn.BatchNorm3d(16, eps=-1.0), inp_3d)]:
init_weight(bn.eval())
verify_model(bn.eval(), input_data=inp)
```
### Output:
```
for bn, inp in [(torch.nn.BatchNorm2d(16, eps=-1.0), inp_2d),
(torch.nn.BatchNorm3d(16, eps=-1.0), inp_3d)]:
init_weight(bn.eval())
> verify_model(bn.eval(), input_data=inp)
tests/python/frontend/pytorch/test_forward.py:1317:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/python/frontend/pytorch/test_forward.py:204: in verify_model
tvm.testing.assert_allclose(baseline_output, output, rtol=rtol,
atol=atol)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
actual = array([[[[ inf, inf, inf, ..., inf, inf, inf],
[ inf, inf, inf, ..., inf, inf, inf],
[ inf... [ inf, inf, inf, ..., inf, inf, inf],
[ inf, inf, inf, ..., inf, inf, inf]]]], dtype=float32)
desired = array([[[[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ....an, nan],
[nan, nan, nan, ..., nan, nan, nan],
[nan, nan, nan, ..., nan, nan, nan]]]], dtype=float32)
rtol = 1e-05, atol = 1e-05
def assert_allclose(actual, desired, rtol=1e-7, atol=1e-7):
"""Version of np.testing.assert_allclose with `atol` and `rtol`
fields set
in reasonable defaults.
Arguments `actual` and `desired` are not interchangeable, since the
function
compares the `abs(actual-desired)` with `atol+rtol*abs(desired)`.
Since we
often allow `desired` to be close to zero, we generally want
non-zero `atol`.
"""
actual = np.asanyarray(actual)
desired = np.asanyarray(desired)
np.testing.assert_allclose(actual.shape, desired.shape)
> np.testing.assert_allclose(actual, desired, rtol=rtol, atol=atol,
verbose=True)
E AssertionError:
E Not equal to tolerance rtol=1e-05, atol=1e-05
E
E x and y nan location mismatch:
E x: array([[[[ inf, inf, inf, ..., inf, inf, inf],
E [ inf, inf, inf, ..., inf, inf, inf],
E [ inf, inf, inf, ..., inf, inf, inf],...
E y: array([[[[nan, nan, nan, ..., nan, nan, nan],
E [nan, nan, nan, ..., nan, nan, nan],
E [nan, nan, nan, ..., nan, nan, nan],...
```
### Excepted output:
Test should pass
### Environment:
```
torch 1.8.0+cu111
torchvision 0.9.0+cu111
TVM version: latest
Python 3.7.12
```
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