[API Compatibility No.48、63、74、215、235] Add parameter alias support for column_stack,dstack,hstack,row_stack,vstack - part (PaddlePaddle#78069)

* fix

* fix

* fix

Author: enkilee

python/paddle/tensor/manipulation.py

@@ -2379,7 +2379,13 @@ def stack(
     return out
 
 
-def hstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
+@param_one_alias(["x", "tensors"])
+def hstack(
+    x: Sequence[Tensor],
+    name: str | None = None,
+    *,
+    out: Tensor | None = None,
+) -> Tensor:
     """
     Stacks all the input tensors ``x`` along horizontal axis.
     All tensors must be of the same dtype.
@@ -2394,8 +2400,12 @@ def hstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     Args:
         x (list[Tensor]|tuple[Tensor]): Input ``x`` can be a ``list`` or ``tuple`` of tensors, the Tensors in ``x`` must be of the same
             shape and dtype. Supported data types: ``float16``, ``float32``, ``float64``, ``int8``, ``int32``, ``int64`` or ``bfloat16``.
+            Alias: ``tensors``.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
+    Keyword args:
+        out(Tensor, optional): The output tensor.
+
     Returns:
         Tensor, The stacked tensor with same data type as input.
 
@@ -2447,7 +2457,13 @@ def hstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
         return paddle.concat(arrays, axis=1, name=name)
 
 
-def vstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
+@param_one_alias(["x", "tensors"])
+def vstack(
+    x: Sequence[Tensor],
+    name: str | None = None,
+    *,
+    out: Tensor | None = None,
+) -> Tensor:
     """
     Stacks all the input tensors ``x`` along vertical axis.
     All tensors must be of the same dtype.
@@ -2462,8 +2478,12 @@ def vstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     Args:
         x (list[Tensor]|tuple[Tensor]): Input ``x`` can be a ``list`` or ``tuple`` of tensors, the Tensors in ``x`` must be of the same
             shape and dtype. Supported data types: ``float16``, ``float32``, ``float64``, ``int8``, ``int32``, ``int64`` or ``bfloat16``.
+            Alias: ``tensors``.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
+    Keyword args:
+        out(Tensor, optional): The output tensor.
+
     Returns:
         Tensor, The stacked tensor with same data type as input.
 
@@ -2516,16 +2536,26 @@ def vstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     return paddle.concat(arrays, axis=0, name=name)
 
 
-def dstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
+@param_one_alias(["x", "tensors"])
+def dstack(
+    x: Sequence[Tensor],
+    name: str | None = None,
+    *,
+    out: Tensor | None = None,
+) -> Tensor:
     """
     Stacks all the input tensors ``x`` along depth axis.
     All tensors must be of the same dtype.
 
     Args:
         x (list[Tensor]|tuple[Tensor]): Input ``x`` can be a ``list`` or ``tuple`` of tensors, the Tensors in ``x`` must be of the same
             shape and dtype. Supported data types: ``float16``, ``float32``, ``float64``, ``int8``, ``int32``, ``int64`` or ``bfloat16``.
+            Alias: ``tensors``.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
+    Keyword args:
+        out(Tensor, optional): The output tensor.
+
     Returns:
         Tensor, The stacked tensor with same data type as input.
 
@@ -2569,7 +2599,13 @@ def dstack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     return paddle.concat(arrays, axis=2, name=name)
 
 
-def column_stack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
+@param_one_alias(["x", "tensors"])
+def column_stack(
+    x: Sequence[Tensor],
+    name: str | None = None,
+    *,
+    out: Tensor | None = None,
+) -> Tensor:
     """
     Stacks all the input tensors ``x`` along horizontal axis. Each tensor in ``x`` will be first reshaped into ``(tensor.numel(), 1)``
     if ``tensor.ndim < 2`` before being stacked.
@@ -2578,8 +2614,12 @@ def column_stack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     Args:
         x (list[Tensor]|tuple[Tensor]): Input ``x`` can be a ``list`` or ``tuple`` of tensors, the Tensors in ``x`` must be of the same
             shape and dtype. Supported data types: ``float16``, ``float32``, ``float64``, ``int32``, ``int64`` or ``bfloat16``.
+            Alias: ``tensors``.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
+    Keyword args:
+        out(Tensor, optional): The output tensor.
+
     Returns:
         Tensor, The stacked tensor with same data type as input.
 
@@ -2629,7 +2669,13 @@ def column_stack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     return paddle.concat(arrays, axis=1, name=name)
 
 
-def row_stack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
+@param_one_alias(["x", "tensors"])
+def row_stack(
+    x: Sequence[Tensor],
+    name: str | None = None,
+    *,
+    out: Tensor | None = None,
+) -> Tensor:
     """
     Alias of `paddle.vstack()`.
     Stacks all the input tensors ``x`` along vertical axis.
@@ -2638,8 +2684,13 @@ def row_stack(x: Sequence[Tensor], name: str | None = None) -> Tensor:
     Args:
         x (list[Tensor]|tuple[Tensor]): Input ``x`` can be a ``list`` or ``tuple`` of tensors, the Tensors in ``x`` must be of the same
             shape and dtype. Supported data types: ``float16``, ``float32``, ``float64``, ``int8``, ``int32``, ``int64`` or ``bfloat16``.
+            Alias: ``tensors``.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
+    Keyword args:
+        out(Tensor, optional): The output tensor.
+
+
     Returns:
         Tensor, The stacked tensor with same data type as input.