修复 as_strided 转换规则：字节 offset 换算为元素 offset

tester/api_config/11_fix_op/as_strided_unfold_overlap_grad.txt

@@ -0,0 +1,31 @@
+paddle.as_strided(Tensor([4],"float32"), shape=tuple(2,2,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([4],"float64"), shape=tuple(2,2,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([5],"float32"), shape=tuple(3,3,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([5],"float64"), shape=tuple(3,3,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([8],"float32"), shape=tuple(3,3,), stride=tuple(1,1,), offset=4, )
+paddle.as_strided(Tensor([64],"float32"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([64],"float16"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([64],"bfloat16"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([64],"complex64"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([64],"complex128"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.as_strided(Tensor([1],"float32"), shape=tuple(3,4,), stride=tuple(0,0,), )
+paddle.as_strided(Tensor([1],"float32"), shape=tuple(64,64,), stride=tuple(0,0,), )
+paddle.as_strided(Tensor([3],"float32"), shape=tuple(3,4,), stride=tuple(1,0,), )
+paddle.as_strided(Tensor([32],"float32"), shape=tuple(32,16,), stride=tuple(1,0,), )
+paddle.as_strided(Tensor([8, 4],"float32"), shape=tuple(6,4,), stride=tuple(2,1,), )
+paddle.as_strided(Tensor([6],"float32"), shape=tuple(2,3,), stride=tuple(3,1,), )
+paddle.as_strided(Tensor([6],"float32"), shape=tuple(3,2,), stride=tuple(1,3,), )
+paddle.as_strided(Tensor([128, 8],"float32"), shape=tuple(64,8,), stride=tuple(8,1,), )
+paddle.Tensor.as_strided(Tensor([64],"float32"), shape=tuple(32,32,), stride=tuple(1,1,), )
+paddle.Tensor.as_strided(Tensor([6],"float32"), shape=tuple(2,3,), stride=tuple(3,1,), )
+paddle.unfold(Tensor([5],"float32"), 0, 3, 1, )
+paddle.unfold(Tensor([5],"float64"), 0, 3, 1, )
+paddle.unfold(Tensor([16],"float32"), 0, 4, 1, )
+paddle.unfold(Tensor([128],"float32"), 0, 64, 1, )
+paddle.unfold(Tensor([128],"float16"), 0, 64, 1, )
+paddle.unfold(Tensor([128],"bfloat16"), 0, 64, 1, )
+paddle.unfold(Tensor([128],"complex64"), 0, 64, 1, )
+paddle.unfold(Tensor([64, 8],"float32"), 0, 8, 1, )
+paddle.unfold(Tensor([8, 4],"float32"), 0, 4, 2, )
+paddle.unfold(Tensor([12],"float32"), -1, 2, 5, )
+paddle.unfold(Tensor([12],"float32"), 0, 4, 4, )

tester/paddle_to_torch/mapping.json

@@ -229,14 +229,14 @@
         }
     },
     "paddle.as_strided": {
+        "Rule": "AsStridedRule",
         "torch_api": "torch.as_strided",
-        "paddle_torch_args_map": {
-            "x": "input",
-            "shape": "size",
-            "stride": "stride",
-            "offset": "storage_offset"
-        },
-        "description": "result = torch.as_strided(input=x, size=shape, stride=stride, storage_offset=offset)"
+        "description": "Paddle byte offset is converted to Torch element offset"
+    },
+    "paddle.Tensor.as_strided": {
+        "Rule": "AsStridedRule",
+        "torch_api": "torch.Tensor.as_strided",
+        "description": "Paddle byte offset is converted to Torch element offset"
     },
     "paddle.asin": {
         "torch_api": "torch.arcsin",

tester/paddle_to_torch/rules.py

@@ -419,6 +419,44 @@ def apply(self, paddle_api: str) -> ConvertResult:
         )
 
 
+class AsStridedRule(BaseRule):
+    PADDLE_APIS = ("paddle.as_strided", "paddle.Tensor.as_strided")
+
+    def apply(self, paddle_api: str) -> ConvertResult:
+        # Paddle 的 offset 是字节数，Torch 的 storage_offset 是元素序号，不能直接透传。
+        preprocess = """
+_storage_offset = locals().get("offset", 0)
+# 缺省 offset 由绑定器补成 0，独立转换调用也保持相同语义。
+if _storage_offset is None:
+    _storage_offset = 0
+_storage_offset = int(_storage_offset)
+_item_size = int(x.element_size())
+# 非法偏移提前失败，避免 Torch 以不同单位产生静默错位。
+if _storage_offset < 0 or _storage_offset % _item_size:
+    raise ValueError(
+        f"Paddle as_strided offset must be a non-negative multiple of itemsize, "
+        f"got offset={_storage_offset}, itemsize={_item_size}"
+    )
+_storage_offset //= _item_size
+"""
+        # 共享参数绑定器把 Tensor receiver 统一命名为 x，函数与方法只需切换调用入口。
+        if paddle_api == "paddle.Tensor.as_strided":
+            core = (
+                "result = x.as_strided(size=shape, stride=stride, storage_offset=_storage_offset)"
+            )
+        else:
+            core = (
+                "result = torch.as_strided("
+                "input=x, size=shape, stride=stride, storage_offset=_storage_offset)"
+            )
+        return self.build_result(
+            paddle_api,
+            kind=ConversionKind.DIRECT,
+            preprocess=preprocess,
+            core=core,
+        )
+
+
 # a
 class AsComplexRule(BaseRule):
     PADDLE_APIS = ("paddle.as_complex",)