wyc-ruiker commented on a change in pull request #8443:
URL: https://github.com/apache/tvm/pull/8443#discussion_r668389145
##########
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:
Hi @delldu, the other parts LGTM. But the unit test I think we can
rewrite it more concisely and support more situations by pass some params. Here
is a simple example.
```suggestion
class Im2col(Module):
def __init__(self, kernel_size, dilation, padding, stride):
super(Im2col, self).__init__()
self.kernel_size = kernel_size
self.dilation = dilation
self.padding = padding
self.stride = stride
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, (kernel_size, kernel_size), (1,
1), (1, 1), (1, 1))
input = torch.randn(2, 3, 32, 32)
verify_model(Im2col(3, 1, 1, 1), input_data=input)
verify_model(Im2col(5, 1, 1, 1), input_data=input)
verify_model(Im2col(3, 1, 2, 1), input_data=input)
verify_model(Im2col(5, 1, 2, 1), input_data=input)
verify_script_model(Im2col(3, 1, 1, 1).eval(), [(2, 3, 32, 32)],
_get_default_vm_targets())
verify_script_model(Im2col(5, 1, 1, 1).eval(), [(2, 3, 32, 32)],
_get_default_vm_targets())
verify_script_model(Im2col(3, 1, 2, 1).eval(), [(2, 3, 32, 32)],
_get_default_vm_targets())
verify_script_model(Im2col(5, 1, 2, 1).eval(), [(2, 3, 32, 32)],
_get_default_vm_targets())
```
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