PaddlePaddle
diff --git a/‎python/paddle/sparse/binary.py
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+45-7Lines changed: 45 additions & 7 deletions b/‎python/paddle/sparse/binary.py
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+45-7Lines changed: 45 additions & 7 deletions
diff --git a/‎test/deprecated/legacy_test/test_sparse_elementwise_op.py
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-227Lines changed: 0 additions & 227 deletions b/‎test/deprecated/legacy_test/test_sparse_elementwise_op.py
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-227Lines changed: 0 additions & 227 deletions
@@ -17,7 +17,13 @@
 from typing import TYPE_CHECKING
 
 from paddle import _C_ops
-from paddle.base.framework import core, dygraph_only, in_dynamic_or_pir_mode
+from paddle.base.framework import (
+    core,
+    dygraph_only,
+    in_dygraph_mode,
+    in_dynamic_or_pir_mode,
+    in_pir_mode,
+)
 from paddle.base.layer_helper import LayerHelper
 
 from .unary import cast
@@ -42,6 +48,15 @@
     core.DataType.BOOL,
 ]
 
+_pir_int_dtype_ = {
+    core.DataType.UINT8: 1,
+    core.DataType.INT8: 1,
+    core.DataType.INT16: 2,
+    core.DataType.INT32: 4,
+    core.DataType.INT64: 8,
+    core.DataType.BOOL: 1,
+}
+
 
 @dygraph_only
 def matmul(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
@@ -298,7 +313,6 @@ def add(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
         return out
 
 
-@dygraph_only
 def subtract(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
     """
     Subtract two sparse tensors element-wise. Input x and y's shape should be identical and have same sparse
@@ -336,12 +350,19 @@ def subtract(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
                     [ 2.,  2., -4., -8.]])
 
     """
+
     if y.dtype != x.dtype:
         y = _C_ops.sparse_cast(y, None, x.dtype)
-    return _C_ops.sparse_subtract(x, y)
+    if in_dygraph_mode():
+        return _C_ops.sparse_subtract(x, y)
+    elif in_pir_mode():
+        return _C_ops.sparse_subtract(x, y)
+    else:
+        raise RuntimeError(
+            "We currently only support dynamic graph mode or the new IR mode."
+        )
 
 
-@dygraph_only
 def multiply(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
     """
     Multiply two sparse tensors element-wise. Input x and y's shape should be identical and have same sparse
@@ -379,15 +400,22 @@ def multiply(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
                     [ 8., 15.,  0.,  0.]])
 
     """
+
     if isinstance(y, (int, float)):
         return _C_ops.sparse_scale(x, float(y), 0.0, True)
     else:
         if y.dtype != x.dtype:
             y = _C_ops.sparse_cast(y, None, x.dtype)
-        return _C_ops.sparse_multiply(x, y)
+        if in_dygraph_mode():
+            return _C_ops.sparse_multiply(x, y)
+        elif in_pir_mode():
+            return _C_ops.sparse_multiply(x, y)
+        else:
+            raise RuntimeError(
+                "We currently only support dynamic graph mode or the new IR mode."
+            )
 
 
-@dygraph_only
 def divide(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
     """
     Divide two sparse tensors element-wise. Input x and y's shape should be identical and have same sparse
@@ -425,15 +453,25 @@ def divide(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
                     [ 2.       , 1.66666663,  0.       ,  0.       ]])
 
     """
+
     if x.dtype in _int_dtype_:
         x = _C_ops.sparse_cast(x, None, core.VarDesc.VarType.FP32)
+    if x.dtype in _pir_int_dtype_:
+        x = _C_ops.sparse_cast(x, None, core.DataType.FLOAT32)
 
     if isinstance(y, (int, float)):
         return _C_ops.sparse_divide_scalar(x, float(y))
     else:
         if y.dtype != x.dtype:
             y = _C_ops.sparse_cast(y, None, x.dtype)
-        return _C_ops.sparse_divide(x, y)
+        if in_dygraph_mode():
+            return _C_ops.sparse_divide(x, y)
+        elif in_pir_mode():
+            return _C_ops.sparse_divide(x, y)
+        else:
+            raise RuntimeError(
+                "We currently only support dynamic graph mode or the new IR mode."
+            )
 
 
 @dygraph_only