Changes the perm order of ``x`` without changing its data, requiring x to be a SparseCooTensor or SparseCsrTensor.
.. math::
out = transpose(x, perm)
Parameters:
x (Tensor): The input Sparse Tensor with data type float32, float64.
perm (list|tuple): Permute the input according to the data of perm.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
A transposed Sparse Tensor with the same data type as ``x``.
Examples:
.. code-block:: python
import paddle
dense_x = paddle.to_tensor([[-2., 0.], [1., 2.]])
sparse_x = dense_x.to_sparse_coo(1)
out = paddle.incubate.sparse.transpose(sparse_x, [1, 0])
"""
return_C_ops.sparse_transpose(x,perm)
@dygraph_only
@dygraph_only
defatan(x,name=None):
defatan(x,name=None):
"""
"""
...
@@ -608,3 +639,60 @@ def expm1(x, name=None):
...
@@ -608,3 +639,60 @@ def expm1(x, name=None):
out = paddle.incubate.sparse.expm1(sparse_x)
out = paddle.incubate.sparse.expm1(sparse_x)
"""
"""
return_C_ops.sparse_expm1(x)
return_C_ops.sparse_expm1(x)
@dygraph_only
defreshape(x,shape,name=None):
"""
Changes the shape of ``x`` without changing its value, requiring x to be a SparseCooTensor or SparseCsrTensor.
Currently this function can only reshape the sparse dims of ``x`` , but ``shape`` argument must be specified
as the shape of the reshaped tensor.
Note that if x is a SparseCsrTensor, then len(shape) must be 2 or 3.
There are some tricks when specifying the target shape.
- 1. -1 means the value of this dimension is inferred from the total element number of x and remaining dimensions. Thus one and only one dimension can be set -1.
- 2. 0 means the actual dimension value is going to be copied from the corresponding dimension of x. The indices of 0 in the target shape can not exceed the rank of x.
Here are some examples to explain it.
- 1. Given a 3-D tensor x with a shape [2, 4, 6], and the target shape is [6, 8], the reshape operator will transform x into a 2-D tensor with shape [6, 8] and leaving x's data unchanged.
- 2. Given a 3-D tensor x with a shape [2, 4, 6], and the target shape is [2, 3, -1, 2], the reshape operator will transform x into a 4-D tensor with shape [2, 3, 4, 2] and leaving x's data unchanged. In this case, one dimension of the target shape is set to -1, the value of this dimension is inferred from the total element number of x and remaining dimensions.
- 3. Given a 3-D tensor x with a shape [2, 4, 6], and the target shape is [-1, 0, 3, 2], the reshape operator will transform x into a 4-D tensor with shape [2, 4, 3, 2] and leaving x's data unchanged. In this case, besides -1, 0 means the actual dimension value is going to be copied from the corresponding dimension of x.
Args:
x (Tensor): The input sparse tensor with data type ``float32``, ``float64``, ``int32``, ``int64`` or ``bool``.
shape (list|tuple): Define the target shape. At most one dimension of the target shape can be -1.
The data type is ``int32``.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: A reshaped Tensor with the same data type as ``x``.