Remove folder from `AtenStackOp` for single element list inputs (#2626)

`AtenStackOp` defines this folder for list operand containing single
element:
```
OpFoldResult AtenStackOp::fold(FoldAdaptor adaptor) {
  auto list = getOperand(0).getDefiningOp<PrimListConstructOp>();
  if (!list || !list->hasOneUse() || list.getElements().size() != 1)
    return nullptr;
  return list.getElements()[0];
}
```
However, unlike `AtenCatOp`, `AtenStackOp` cannot be folded away for
single element list operand because the result from a stack operation
contains an additional dimension (of size 1, like expand_shape).

This PR removes the `AtenStackOp::fold` method, and adds an e2e test for
single element list input case, which fails on current `main` as
follows:
```
Unexpected outcome summary: (linalg)                                                                                                                                                                   
                                                                                                                                                                                                       
****** Failed tests - 1 tests                                                                                                                                                                          
    FAIL - "TensorsStackSingleElementListModule_basic"                                                                                                                                                 
        @ trace item #0 - call to "forward"                                                                                                                                                            
        @ output of call to "forward"                                                                                                                                                                  
        ERROR: shape (torch.Size([10, 32])) is not equal to golden shape (torch.Size([10, 1, 32]))     
```
Thanks Chris Lalau Keraly for the bug report.

include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td

@@ -11632,7 +11632,6 @@ def Torch_AtenStackOp : Torch_Op<"aten.stack", [
       printDefaultTorchOp(printer, *this, 2, 1);
     }
   }];
-  let hasFolder = 1;
 }
 
 def Torch_AtenAppendTOp : Torch_Op<"aten.append.t", [

lib/Dialect/Torch/IR/TorchOps.cpp

@@ -2444,17 +2444,6 @@ OpFoldResult AtenCatOp::fold(FoldAdaptor adaptor) {
   return list.getElements()[0];
 }
 
-//===----------------------------------------------------------------------===//
-// AtenStackOp
-//===----------------------------------------------------------------------===//
-
-OpFoldResult AtenStackOp::fold(FoldAdaptor adaptor) {
-  auto list = getOperand(0).getDefiningOp<PrimListConstructOp>();
-  if (!list || !list->hasOneUse() || list.getElements().size() != 1)
-    return nullptr;
-  return list.getElements()[0];
-}
-
 //===----------------------------------------------------------------------===//
 // AtenBroadcastToOp
 //===----------------------------------------------------------------------===//

projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py

@@ -691,7 +691,7 @@ def emit_ops(emitter_td: TextEmitter, registry: Registry):
 
     # List ops.
     emit("aten::cat : (Tensor[], int) -> (Tensor)", has_folder=True)
-    emit("aten::stack : (Tensor[], int) -> (Tensor)", has_folder=True)
+    emit("aten::stack : (Tensor[], int) -> (Tensor)")
     emit("aten::append.t : (t[], t) -> (t[])")
     emit("aten::add.t : (t[], t[]) -> (t[])", has_canonicalizer=True)
     emit("aten::eq.int_list : (int[], int[]) -> (bool)", has_folder=True)

projects/pt1/python/torch_mlir_e2e_test/test_suite/basic.py

@@ -884,6 +884,28 @@ def TensorsStackModule_basic(module, tu: TestUtils):
 # ==============================================================================
 
 
+class TensorsStackSingleElementListModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([-1, -1], torch.float32, True),
+    ])
+    def forward(self, x):
+        return torch.stack([x], dim=1)
+
+
+@register_test_case(module_factory=lambda: TensorsStackSingleElementListModule())
+def TensorsStackSingleElementListModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(10, 32))
+
+
+# ==============================================================================
+
+
 class TensorsStackNegativeDimModule(torch.nn.Module):
 
     def __init__(self):