tensor_array slice in PIR (PaddlePaddle#60503)

* use slice_array, now will meet error of destory opresult still in use

* disable the pir test until the bug fixed

python/paddle/base/variable_index.py

@@ -251,7 +251,19 @@ def deal_advanced_index(ori_tensor, indices, is_for_setitem, values):
 
 
 def parse_index(x, indices):
-    advanced_index = [None] * 2 * len(x.shape)  # content is (dim, index)
+    from .framework import in_pir_mode
+
+    if in_pir_mode():
+        is_tensor_array = x.is_dense_tensor_array_type()
+    else:
+        is_tensor_array = (
+            hasattr(x, "desc")
+            and x.desc.type() == core.VarDesc.VarType.LOD_TENSOR_ARRAY
+        )
+
+    advanced_index = (
+        [] if is_tensor_array else [None] * 2 * len(x.shape)
+    )  # content is (dim, index)
     # for set_value / slice / strided_slice OP
     decrease_axes = []
     axes = []
@@ -268,11 +280,6 @@ def parse_index(x, indices):
     indices = replace_ellipsis(x, indices)
     indices, none_axes = replace_none(indices)
 
-    is_tensor_array = (
-        hasattr(x, "desc")
-        and x.desc.type() == core.VarDesc.VarType.LOD_TENSOR_ARRAY
-    )
-
     estimated_dim = 0
     dim = 0
     for i, slice_item in enumerate(indices):
@@ -691,6 +698,8 @@ def get_tensor_with_basic_indexing(
                     if isinstance(end, (list, tuple)):
                         if paddle.utils._contain_var(end):
                             end = paddle.utils.get_int_tensor_list(end)
+                    if x.is_dense_tensor_array_type():
+                        return paddle._pir_ops.slice_array_dense(x, st)
                 out = paddle._C_ops.slice(
                     x,
                     axes,

test/dygraph_to_static/test_list.py

@@ -292,6 +292,7 @@ def init_dygraph_func(self):
             test_list_pop_in_while_loop,
         ]
 
+    # TODO(zhangbo): Refine BuildOpFrom for op with sub_block
     def train(self, to_static=False):
         with base.dygraph.guard():
             if to_static: