Revert "add some Tensor API en doc (#55958)" (#56375)

This reverts commit fd765f61.

paddle/fluid/pybind/eager_method.cc

@@ -1968,32 +1968,6 @@ static PyObject* tensor_method_get_map_tensor(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_method_nnz__doc__,
-             R"DOC(nnz($self, /)
---
-
-Note:
-    **This API is only available for SparseCooTensor or SparseCsrTensor.**
-
-Returns the total number of non zero elements in input SparseCooTensor/SparseCsrTensor.
-
-Returns:
-    int
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.nnz()
-        # 3
-
-)DOC");
-
 static PyObject* tensor_method_get_non_zero_nums(TensorObject* self,
                                                  PyObject* args,
                                                  PyObject* kwargs) {
@@ -2015,34 +1989,6 @@ static PyObject* tensor_method_get_non_zero_nums(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_method_indices__doc__,
-             R"DOC(indices($self, /)
---
-
-Note:
-    **This API is only available for SparseCooTensor.**
-
-Returns the indices of non zero elements in input SparseCooTensor.
-
-Returns:
-    DenseTesnor
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.indices()
-        # Tensor(shape=[2, 3], dtype=int64, place=Place(gpu:0), stop_gradient=True,
-        #        [[0, 1, 2],
-        #         [1, 2, 0]])
-
-)DOC");
-
 static PyObject* tensor_method_get_non_zero_indices(TensorObject* self,
                                                     PyObject* args,
                                                     PyObject* kwargs) {
@@ -2058,33 +2004,6 @@ static PyObject* tensor_method_get_non_zero_indices(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_method_values__doc__,
-             R"DOC(values($self, /)
---
-
-Note:
-    **This API is only available for SparseCooTensor or SparseCsrTensor.**
-
-Returns the values of non zero elements in input SparseCooTensor.
-
-Returns:
-    DenseTesnor
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.values()
-        # Tensor(shape=[3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
-        #        [1., 2., 3.])
-
-)DOC");
-
 static PyObject* tensor_method_get_non_zero_elements(TensorObject* self,
                                                      PyObject* args,
                                                      PyObject* kwargs) {
@@ -2110,34 +2029,6 @@ static PyObject* tensor_method_get_non_zero_elements(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_method_crows__doc__,
-             R"DOC(crows($self, /)
---
-
-Note:
-    **This API is only available for SparseCsrTensor.**
-
-Returns the compressed row index of non zero elements in input SparseCsrTensor.
-
-Returns:
-    DenseTesnor
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        crows = [0, 2, 3, 5]
-        cols = [1, 3, 2, 0, 1]
-        values = [1, 2, 3, 4, 5]
-        dense_shape = [3, 4]
-        csr = paddle.sparse.sparse_csr_tensor(crows, cols, values, dense_shape)
-        csr.crows()
-        # Tensor(shape=[4], dtype=int64, place=Place(gpu:0), stop_gradient=True,
-        #        [0, 2, 3, 5])
-
-)DOC");
-
 static PyObject* tensor_method_get_non_zero_crows(TensorObject* self,
                                                   PyObject* args,
                                                   PyObject* kwargs) {
@@ -2153,34 +2044,6 @@ static PyObject* tensor_method_get_non_zero_crows(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_method_cols__doc__,
-             R"DOC(cols($self, /)
---
-
-Note:
-    **This API is only available for SparseCsrTensor.**
-
-Returns the column index of non zero elements in input SparseCsrTensor.
-
-Returns:
-    DenseTesnor
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        crows = [0, 2, 3, 5]
-        cols = [1, 3, 2, 0, 1]
-        values = [1, 2, 3, 4, 5]
-        dense_shape = [3, 4]
-        csr = paddle.sparse.sparse_csr_tensor(crows, cols, values, dense_shape)
-        csr.cols()
-        # Tensor(shape=[5], dtype=int64, place=Place(gpu:0), stop_gradient=True,
-        #        [1, 3, 2, 0, 1])
-
-)DOC");
-
 static PyObject* tensor_method_get_non_zero_cols(TensorObject* self,
                                                  PyObject* args,
                                                  PyObject* kwargs) {
@@ -2252,31 +2115,6 @@ static PyObject* tensor_method_is_dist(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_is_sparse__doc__,
-             R"DOC(is_sparse($self, /)
---
-
-Returns whether the input Tensor is SparseCooTensor or SparseCsrTensor.
-
-When input is SparseCooTensor/SparseCsrTensor, will return True. When input is DenseTensor, will return False.
-
-Returns:
-    bool
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.is_sparse()
-        # True
-
-)DOC");
-
 static PyObject* tensor_method_is_sparse(TensorObject* self,
                                          PyObject* args,
                                          PyObject* kwargs) {
@@ -2289,31 +2127,6 @@ static PyObject* tensor_method_is_sparse(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_is_sparse_coo__doc__,
-             R"DOC(is_sparse_coo($self, /)
---
-
-Returns whether the input Tensor is SparseCooTensor.
-
-When input is SparseCooTensor, will return True. When input is DenseTensor/SparseCsrTensor, will return False.
-
-Returns:
-    bool
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.is_sparse_coo()
-        # True
-
-)DOC");
-
 static PyObject* tensor_method_is_sparse_coo(TensorObject* self,
                                              PyObject* args,
                                              PyObject* kwargs) {
@@ -2325,32 +2138,6 @@ static PyObject* tensor_method_is_sparse_coo(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_is_sparse_csr__doc__,
-             R"DOC(is_sparse_csr($self, /)
---
-
-Returns whether the input Tensor is SparseCsrTensor.
-
-When input is SparseCsrTensor, will return True. When input is DenseTensor/SparseCooTensor, will return False.
-
-Returns:
-    bool
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        crows = [0, 2, 3, 5]
-        cols = [1, 3, 2, 0, 1]
-        values = [1, 2, 3, 4, 5]
-        dense_shape = [3, 4]
-        csr = paddle.sparse.sparse_csr_tensor(crows, cols, values, dense_shape)
-        csr.is_sparse_csr()
-        # True
-
-)DOC");
-
 static PyObject* tensor_method_is_sparse_csr(TensorObject* self,
                                              PyObject* args,
                                              PyObject* kwargs) {
@@ -2362,37 +2149,6 @@ static PyObject* tensor_method_is_sparse_csr(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_to_sparse_csr__doc__,
-             R"DOC(to_sparse_csr($self, /)
---
-
-Note:
-    **This API is only available for DenseTensor or SparseCooTensor.**
-
-Convert input Tensor to SparseCsrTensor.
-
-When input is SparseCooTensor, will convert `COO` to `CSR` . When input is DenseTensor, will convert `Dense` to `CSR` .
-
-Returns:
-    SparseCsrTensor
-
-Examples:
-    .. code-block:: python
-
-        import paddle
-
-        indices = [[0, 1, 2], [1, 2, 0]]
-        values = [1.0, 2.0, 3.0]
-        dense_shape = [3, 3]
-        coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
-        coo.to_sparse_csr()
-        # Tensor(shape=[3, 3], dtype=paddle.float32, place=Place(gpu:0), stop_gradient=True,
-        #        crows=[0, 1, 2, 3],
-        #        cols=[1, 2, 0],
-        #        values=[1., 2., 3.])
-
-)DOC");
-
 static PyObject* tensor_method_to_sparse_csr(TensorObject* self,
                                              PyObject* args,
                                              PyObject* kwargs) {
@@ -2408,38 +2164,6 @@ static PyObject* tensor_method_to_sparse_csr(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
-PyDoc_STRVAR(tensor_is_same_shape__doc__,
-             R"DOC(is_same_shape($self, y, /)
---
-
-Return the results of shape comparison between two Tensors, check whether x.shape equal to y.shape.
-Any two type Tensor among DenseTensor/SparseCooTensor/SparseCsrTensor are supported.
-
-Args:
-    x (Tensor): The input tensor. It can be DenseTensor/SparseCooTensor/SparseCsrTensor.
-    y (Tensor): The input tensor. It can be DenseTensor/SparseCooTensor/SparseCsrTensor.
-
-Returns:
-    bool: True for same shape and False for different shape.
-
-Examples:
-
-    .. code-block:: python
-
-        import paddle
-
-        x = paddle.rand([2, 3, 8])
-        y = paddle.rand([2, 3, 8])
-        y = y.to_sparse_csr()
-        z = paddle.rand([2, 5])
-
-        x.is_same_shape(y)
-        # True
-        x.is_same_shape(z)
-        # False
-
-)DOC");
-
 static PyObject* tensor_method_is_same_shape(TensorObject* self,
                                              PyObject* args,
                                              PyObject* kwargs) {
@@ -2503,10 +2227,9 @@ PyDoc_STRVAR(tensor_method__bump_inplace_version__doc__,  // NOLINT
              R"DOC(_bump_inplace_version($self, /)
 --
 
-Note:
+**Notes**:
     **This API is ONLY available in Dygraph mode.**
     **This is a very low level API. Users should not use it directly. **
-
   Bump the version whenever the Tensor is modified through an inplace operation.
 )DOC");
 static PyObject* tensor__bump_inplace_version(TensorObject* self,
@@ -3029,48 +2752,48 @@ PyMethodDef variable_methods[] = {  // NOLINT
     {"nnz",
      (PyCFunction)(void (*)())tensor_method_get_non_zero_nums,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_method_nnz__doc__},
+     nullptr},
     {"indices",
      (PyCFunction)(void (*)())tensor_method_get_non_zero_indices,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_method_indices__doc__},
+     nullptr},
     {"values",
      (PyCFunction)(void (*)())tensor_method_get_non_zero_elements,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_method_values__doc__},
+     nullptr},
     {"crows",
      (PyCFunction)(void (*)())tensor_method_get_non_zero_crows,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_method_crows__doc__},
+     nullptr},
     {"cols",
      (PyCFunction)(void (*)())tensor_method_get_non_zero_cols,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_method_cols__doc__},
+     nullptr},
     {"is_sparse",
      (PyCFunction)(void (*)())tensor_method_is_sparse,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_is_sparse__doc__},
+     nullptr},
     {"is_sparse_coo",
      (PyCFunction)(void (*)())tensor_method_is_sparse_coo,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_is_sparse_coo__doc__},
+     nullptr},
     {"is_sparse_csr",
      (PyCFunction)(void (*)())tensor_method_is_sparse_csr,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_is_sparse_csr__doc__},
+     nullptr},
     {"is_same_shape",
      (PyCFunction)(void (*)())tensor_method_is_same_shape,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_is_same_shape__doc__},
+     nullptr},
     {"to_sparse_csr",
      (PyCFunction)(void (*)())tensor_method_to_sparse_csr,
      METH_VARARGS | METH_KEYWORDS,
-     tensor_to_sparse_csr__doc__},
-    /***the method of sparse tensor****/
+     nullptr},
     {"element_size",
      (PyCFunction)(void (*)())tensor_method_element_size,
      METH_VARARGS | METH_KEYWORDS,
      tensor_method_element_size__doc__},
+    /***the method of sparse tensor****/
     {"_inplace_version",
      (PyCFunction)(void (*)())tensor__inplace_version,
      METH_VARARGS | METH_KEYWORDS,

paddle/phi/core/sparse_coo_tensor.h

@@ -63,15 +63,15 @@ class SparseCooTensor : public TensorBase,
   /// \brief Destroy the tensor object and release exclusive resources.
   virtual ~SparseCooTensor() = default;
 
-  /// \brief Returns the indices of non zero elements in original dense tensor.
-  /// \return The indices of non zero elements in original dense tensor.
+  /// \brief Returns the indices of non zero elemetns in original dense tensor.
+  /// \return The indices of non zero elemetns in original dense tensor.
   const DenseTensor& indices() const { return non_zero_indices_; }
 
   /// Note: This function will removed soon. It is recommended to use indices()
   const DenseTensor& non_zero_indices() const { return non_zero_indices_; }
 
-  /// \brief Returns the non zero elements in original dense tensor.
-  /// \return The non zero elements in original dense tensor.
+  /// \brief Returns the non zero elemetns in original dense tensor.
+  /// \return The non zero elemetns in original dense tensor.
   const DenseTensor& values() const { return non_zero_elements_; }
 
   /// Note: This function will removed soon. It is recommended to use values()

paddle/phi/core/sparse_csr_tensor.h

@@ -70,25 +70,25 @@ class SparseCsrTensor : public TensorBase,
   /// \return The name of the class.
   static const char* name() { return "SparseCsrTensor"; }
 
-  /// \brief Returns the compressed row index of non zero elements in original
+  /// \brief Returns the compressed row index of non zero elemetns in original
   /// dense tensor.
-  /// \return The compressed row index of non zero elements in original dense
+  /// \return The compressed row index of non zero elemetns in original dense
   /// tensor.
   const DenseTensor& crows() const { return non_zero_crows_; }
 
   /// Note: This function will removed soon. It is recommended to use crows()
   const DenseTensor& non_zero_crows() const { return non_zero_crows_; }
 
-  /// \brief Returns the column index of non zero elements in original dense
+  /// \brief Returns the column index of non zero elemetns in original dense
   /// tensor.
-  /// \return The column index of non zero elements in original dense tensor.
+  /// \return The column index of non zero elemetns in original dense tensor.
   const DenseTensor& cols() const { return non_zero_cols_; }
 
   /// Note: This function will removed soon. It is recommended to use cols()
   const DenseTensor& non_zero_cols() const { return non_zero_cols_; }
 
-  /// \brief Returns the non zero elements in original dense tensor.
-  /// \return The non zero elements in original dense tensor.
+  /// \brief Returns the non zero elemetns in original dense tensor.
+  /// \return The non zero elemetns in original dense tensor.
   const DenseTensor& values() const { return non_zero_elements_; }
 
   /// Note: This function will removed soon. It is recommended to use indices()

flashattn @ b5bdb79d

-Subproject commit 18106c1ba0ccee81b97ca947397c08a141815a47
+Subproject commit b5bdb79d5e1f2f88b1ef62e86899a14f82fa079a