[Torch] Fix PrimListUnpackOp::getCanonicalizationPatterns (llvm#3140)

Fix the case PrimListUnpackOp's result num is not equal to PrimList
length.
See the following example:
```python
    def forward(self, x):
        if len(x.shape) == 5:
            b0, t, c0, h0, w0 = x.shape
            b, c, h, w = torch.mul(b0, t), c0, h0, w0
        else:
            b1, c1, h1, w1 = x.shape
            b, c, h, w = b1, c1, h1, w1
        res = torch.reshape(x, [b, c, h, w])
        return res
```
Without this fix, the following error message will occur：
```
/root/torch-mlir/externals/llvm-project/mlir/lib/IR/PatternMatch.cpp:118: virtual void mlir::RewriterBase::replaceOp(mlir::Operation *, mlir::ValueRange): Assertion `op->getNumResults() == newValues.size() && "incorrect # of replacement values"' failed.
```

lib/Dialect/Torch/IR/TorchOps.cpp

@@ -3088,6 +3088,9 @@ void PrimListUnpackOp::getCanonicalizationPatterns(RewritePatternSet &patterns,
     if (!listConstruct)
       return failure();
 
+    if (op->getNumResults() != listConstruct.getElements().size())
+      return failure();
+
     rewriter.replaceOp(op, listConstruct.getElements());
     return success();
   });

projects/pt1/e2e_testing/xfail_sets.py

@@ -657,6 +657,7 @@
     "PermuteModule_basic",
     "PermuteNegativeIndexModule_basic",
     "PowIntFloatModule_basic",
+    "PrimListUnpackNumMismatchModule_basic",
     "PrimMaxIntModule_basic",
     "PrimMinIntDynamicModule_basic",
     "PrimMinIntModule_basic",
@@ -1216,6 +1217,7 @@
     "Permute0RankModule_basic",
     "PermuteModule_basic",
     "PermuteNegativeIndexModule_basic",
+    "PrimListUnpackNumMismatchModule_basic",
     "PrimsSqueezeEmptyDimensionsModule_basic",
     "PrimsSqueezeModule_basic",
     "PrimsViewOfModule_basic",
@@ -1391,6 +1393,7 @@
     "ElementwisePreluStaticModule_basic", 
 
     # Shape Related failures
+    "PrimListUnpackNumMismatchModule_basic",
     "ReshapeExpandModule_basic",
     "UnsafeViewCollapseModule_basic",
     "UnsafeViewDynamicExpandModule_basic",

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

@@ -674,6 +674,33 @@ def SliceCopyNonZeroDim_Module_basic(module, tu: TestUtils):
     module.forward(tu.rand(10, 4, 4), tu.rand(10, 2, 4))
 
 
+# ==============================================================================
+class PrimListUnpackNumMismatchModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()   
+
+
+    @export
+    @annotate_args([
+        None,
+        ([5, 4, 3, 2, 1], torch.float32, True),
+    ])
+    def forward(self, x):
+        if len(x.shape) == 5:
+            b0, t, c0, h0, w0 = x.shape
+            b, c, h, w = torch.mul(b0, t), c0, h0, w0
+        else:
+            b1, c1, h1, w1 = x.shape
+            b, c, h, w = b1, c1, h1, w1
+        res = torch.reshape(x, [b, c, h, w])
+        return res
+
+
+@register_test_case(module_factory=lambda: PrimListUnpackNumMismatchModule())
+def PrimListUnpackNumMismatchModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(5, 4, 3, 2, 1))
+
+
 # ==============================================================================