locnd182644 opened a new pull request, #18583:
URL: https://github.com/apache/tvm/pull/18583
## Issue 1: Without Dim
### Summary:
In _sum function (BaseFXGraphImporter), after retrieve_args, args[1] = []
and still pass into relax.op.sum so the result is incorrect.
### Steps to Reproduce
- Module
```
class SumWithoutDim(nn.Module):
def forward(self, x):
return torch.sum(x)
```
```
@I.ir_module
class Module:
@R.function
def main(x: R.Tensor((2, 3), dtype="float32")) -> R.Tuple(R.Tensor((2,
3), dtype="float32")):
with R.dataflow():
lv: R.Tensor((2, 3), dtype="float32") = R.sum(x, axis=[],
keepdims=False)
gv: R.Tuple(R.Tensor((2, 3), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
- Result:
Input: tensor([[1., 1., 1.], [1., 1., 1.]])
Torch output: tensor(6.)
Torch output shape: torch.Size([])
TVM output: [[1. 1. 1.] [1. 1. 1.]]
TVM output shape: (2, 3)
### Expected
```
@I.ir_module
class Module:
@R.function
def main(x: R.Tensor((2, 3), dtype="float32")) -> R.Tuple(R.Tensor((),
dtype="float32")):
with R.dataflow():
lv: R.Tensor((), dtype="float32") = R.sum(x, axis=None,
keepdims=False)
gv: R.Tuple(R.Tensor((), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
- Result: TVM output: 6.0; TVM output shape: ()
## Issue 2: Keep Dim
### Summary:
In _sum function (BaseFXGraphImporter), previously keepdim value get only
from node.kwargs and no pass into relax.op.sum. Now keepdim get more from
args[2] and pass into.
### Steps to Reproduce
- Module
```
class SumKeepDim(nn.Module):
def forward(self, x):
return torch.sum(x, dim=1, keepdim=True)
```
```
@I.ir_module
class Module:
@R.function
def main(x: R.Tensor((2, 3), dtype="float32")) -> R.Tuple(R.Tensor((2,),
dtype="float32")):
with R.dataflow():
lv: R.Tensor((2,), dtype="float32") = R.sum(x, axis=[1],
keepdims=False)
gv: R.Tuple(R.Tensor((2,), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
- Result:
Input: tensor([[1., 1., 1.], [1., 1., 1.]])
Torch output: tensor([[3.], [3.]])
Torch output shape: torch.Size([2, 1])
TVM VM output: [3. 3.]
TVM VM output shape: (2,)
### Expected
```
@I.ir_module
class Module:
@R.function
def main(x: R.Tensor((2, 3), dtype="float32")) -> R.Tuple(R.Tensor((2,
1), dtype="float32")):
with R.dataflow():
lv: R.Tensor((2, 1), dtype="float32") = R.sum(x, axis=[1],
keepdims=True)
gv: R.Tuple(R.Tensor((2, 1), dtype="float32")) = (lv,)
R.output(gv)
return gv
```
- Result: TVM output: [[3.] [3.]] ;TVM output shape: (2, 1)
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