rename python files

python/paddle/sparse/functional/__init__.py

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .activation import relu  # noqa: F401
-from .activation import tanh  # noqa: F401
-from .math import sqrt  # noqa: F401
-from .math import sin  # noqa: F401
+from .unary import relu  # noqa: F401
+from .unary import tanh  # noqa: F401
+from .unary import sqrt  # noqa: F401
+from .unary import sin  # noqa: F401
 from .conv import conv3d  # noqa: F401
 from .conv import subm_conv3d  # noqa: F401
 from .pooling import max_pool3d  # noqa: F401

python/paddle/sparse/functional/activation.py → python/paddle/sparse/functional/unary.py

@@ -95,3 +95,83 @@ def tanh(x, name=None):
         raise ValueError(
             "Currently, sparse.tanh only support the input of SparseCooTensor or SparseCsrTensor"
         )
+
+
+def sqrt(x, name=None):
+    """
+    Calculate square root of x, requiring x to be a sparse coo or sparse csr tensor.
+
+    .. math::
+
+        out = sqrt(x)
+
+    Parameters:
+        x (Tensor): The input Sparse Tensor with data type float32, float64.
+        name (str, optional): Name for the operation (optional, default is None).
+            For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        A Sparse Tensor with the same data type and shape as ``x`` .
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+            from paddle.fluid.framework import _test_eager_guard
+
+            with _test_eager_guard():
+                dense_x = paddle.to_tensor([4, 0, 1], dtype='float32')
+                sparse_x = dense_x.to_sparse_coo(1)
+                out = paddle.sparse.sqrt(sparse_x)
+    """
+
+    assert in_dynamic_mode(), "Currently, Sparse API only support dynamic mode"
+
+    if x.is_sparse_coo():
+        return _C_ops.final_state_sparse_coo_sqrt(x)
+    elif x.is_sparse_csr():
+        return _C_ops.final_state_sparse_csr_sqrt(x)
+    else:
+        raise ValueError(
+            "Currently, sparse.sqrt only support the input of SparseCooTensor or SparseCsrTensor"
+        )
+
+
+def sin(x, name=None):
+    """
+    Calculate sin of x, requiring x to be a sparse coo or sparse csr tensor.
+
+    .. math::
+
+        out = sin(x)
+
+    Parameters:
+        x (Tensor): The input Sparse Tensor with data type float32, float64.
+        name (str, optional): Name for the operation (optional, default is None).
+            For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        A Sparse Tensor with the same data type and shape as ``x`` .
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+            from paddle.fluid.framework import _test_eager_guard
+
+            with _test_eager_guard():
+                dense_x = paddle.to_tensor([-2, 0, 3], dtype='float32')
+                sparse_x = dense_x.to_sparse_coo(1)
+                out = paddle.sparse.sin(sparse_x)
+    """
+
+    assert in_dynamic_mode(), "Currently, Sparse API only support dynamic mode"
+
+    if x.is_sparse_coo():
+        return _C_ops.final_state_sparse_coo_sin(x)
+    elif x.is_sparse_csr():
+        return _C_ops.final_state_sparse_csr_sin(x)
+    else:
+        raise ValueError(
+            "Currently, sparse.sin only support the input of SparseCooTensor or SparseCsrTensor"
+        )

python/paddle/sparse/layer/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .activation import ReLU
+from .unary import ReLU
 from .norm import BatchNorm
 from .conv import Conv3D
 from .conv import SubmConv3D