delldu commented on a change in pull request #8443:
URL: https://github.com/apache/tvm/pull/8443#discussion_r669321288
##########
File path: tests/python/frontend/pytorch/test_forward.py
##########
@@ -3912,6 +3912,109 @@ def forward(self, x):
verify_model(Flip(axis=-1), input_data=input)
[email protected]_gpu
+def test_forward_im2col():
+ torch.set_grad_enabled(False)
+
+ class Im2col3x3(Module):
+ def __init__(self):
+ super(Im2col3x3, self).__init__()
+
+ def forward(self, x):
+ #
***********************************************************************************
+ #
+ # !!! DO NOT USE !!!
+ # F.unfold(x, kernel_size=3, dilation=1, padding=1, stride=1)
+ # for it broken TVM "if conditional expression" in torch script
mode
+ #
+ #
***********************************************************************************
+
+ return torch._C._nn.im2col(x, (3, 3), (1, 1), (1, 1), (1, 1))
+
+ class Im2col5x5(Module):
+ def __init__(self):
+ super(Im2col5x5, self).__init__()
+
+ def forward(self, x):
+ #
***********************************************************************************
+ #
+ # !!! DO NOT USE !!!
+ # F.unfold(x, kernel_size=5, dilation=1, padding=1, stride=2)
+ # for it broken TVM "if conditional expression" in torch script
mode
+ #
+ #
***********************************************************************************
+
+ return torch._C._nn.im2col(x, (5, 5), (1, 1), (1, 1), (2, 2))
+
+ model = Im2col3x3()
+ input = torch.randn(2, 3, 32, 32)
+ verify_model(model, input_data=input)
+
+ verify_script_model(Im2col5x5().eval(), [(2, 3, 32, 32)],
_get_default_vm_targets())
Review comment:
Because we have a model with control flow, meet missing [aten::im2col]
from F.unfold in practice.
That's why we develop im2col and write a test unit with script mode . Simple
patches as below:
```
def forward(self, x):
x = self.simple_forward(x)
B = x.size(0)
C = x.size(1)
H = x.size(2)
W = x.size(3)
# x = F.unfold(x, 3, dilation=1, padding=1, stride=1)
x = torch._C._nn.im2col(x, (3, 3), (1, 1), (1, 1), (1, 1))
return x.view(B, C * 9, H, W)
```
```
bs: int = 65536
preds = []
start: int = 0
while start < n:
stop: int = start + bs
if stop > n:
stop = n
pred = ...
preds += [pred.view(stop - start, 1, 3)]
start = stop
y = torch.stack(preds, dim=0)
return y
```
First patch, we need aten::im2col, second patch, we real need control flow.
We try to remove while in second patches, but memory cost beyond 64G !
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