[TVMScript] Support starred indices in for-loop

An extension of apache#15404, which
allowed starred expressions in the rhs of
assignments (e.g. `T.decl_buffer(shape=[*dim, 128])`), this PR also
enables starred expressions in the lhs of
assignments (e.g. `for *spatial,reduction in T.grid(*A.shape)`).

python/tvm/script/parser/core/parser.py

@@ -460,6 +460,8 @@ def _duplicate_lhs_check(self, target: doc.expr) -> Union[bool, Set[str]]:
             return vars
         elif isinstance(target, doc.Name):
             return {target.id}
+        elif isinstance(target, doc.Starred):
+            return self._duplicate_lhs_check(target.value)
         else:
             self.report_error(target, "Invalid type in assign statement")
             raise NotImplementedError

python/tvm/script/parser/tir/parser.py

@@ -91,7 +91,7 @@ def bind_for_value(self: Parser, node: doc.expr, var_name: str, value: Any) -> A
     res : Any
         The bound value.
     """
-    if isinstance(value, (list, tuple)):
+    if isinstance(value, (list, tuple, tvm.ir.Array)):
         for i, v in enumerate(value):
             bind_for_value(self, node, f"{var_name}_{i}", v)
         return value
@@ -255,7 +255,7 @@ def visit_assign(self: Parser, node: doc.Assign) -> None:
             for index in lhs.slice.elts:
                 indices.append(self.eval_expr(index))
         else:
-            indices = [self.eval_expr(lhs.slice)]
+            indices = self.eval_expr(lhs.slice)
         T.buffer_store(self.eval_expr(lhs.value), rhs, indices)
     else:
         self.eval_assign(target=lhs, source=rhs, bind_value=bind_assign_value)

tests/python/unittest/test_tvmscript_parser_tir.py

@@ -230,5 +230,67 @@ def non_starred(a: T.handle) -> None:
     tvm.ir.assert_structural_equal(starred, non_starred)
 
 
+def test_tir_starred_shape_expression():
+    dims = (128, 128)
+
+    @T.prim_func(private=True)
+    def starred(a: T.handle) -> None:
+        A = T.match_buffer(a, [128, *dims], "int32")
+        for i, j, k in T.grid(*A.shape):
+            A[i, j, k] = T.int32(1)
+
+    @T.prim_func(private=True)
+    def non_starred(a: T.handle) -> None:
+        A = T.match_buffer(a, [128, 128, 128], "int32")
+        for i, j, k in T.grid(128, 128, 128):
+            A[i, j, k] = T.int32(1)
+
+    tvm.ir.assert_structural_equal(starred, non_starred)
+
+
+def test_tir_dynamic_for_loop():
+    dims = (128, 128)
+
+    @T.prim_func(private=True)
+    def starred(a: T.handle) -> None:
+        A = T.match_buffer(a, [128, *dims], "int32")
+        for iters in T.grid(*A.shape):
+            A[iters] = T.int32(1)
+
+    @T.prim_func(private=True)
+    def non_starred(a: T.handle) -> None:
+        A = T.match_buffer(a, [128, 128, 128], "int32")
+        for i, j, k in T.grid(128, 128, 128):
+            A[i, j, k] = T.int32(1)
+
+    tvm.ir.assert_structural_equal(starred, non_starred)
+
+
+def test_tir_starred_for_loop():
+    dims = (128, 128)
+
+    @T.prim_func(private=True)
+    def starred(a: T.handle, b: T.handle):
+        A = T.match_buffer(a, [*dims, 128], "int32")
+        B = T.match_buffer(a, dims, "int32")
+        for *spatial, reduction in T.grid(*A.shape):
+            with T.block("reduce"):
+                with T.init():
+                    B[spatial] = T.int32(0)
+                B[spatial] = B[spatial] + A[(*spatial, reduction)]
+
+    @T.prim_func(private=True)
+    def non_starred(a: T.handle, b: T.handle):
+        A = T.match_buffer(a, [128, 128, 128], "int32")
+        B = T.match_buffer(a, [128, 128], "int32")
+        for i, j, k in T.grid(128, 128, 128):
+            with T.block("reduce"):
+                with T.init():
+                    B[i, j] = T.int32(0)
+                B[i, j] = B[i, j] + A[i, j, k]
+
+    tvm.ir.assert_structural_equal(starred, non_starred)
+
+
 if __name__ == "__main__":
     tvm.testing.main()