未验证 提交 f58434ef 编写于 作者: T Thunderbrook 提交者: GitHub

fix slice doc (#27941)

* test=document_fix

* fix slice doctest=document_fix

* test=document_fix

* test=document_fix

* test=document_fix

* test=document_fix
上级 840c521b
......@@ -10846,10 +10846,6 @@ def sum(x):
@templatedoc()
def slice(input, axes, starts, ends):
"""
:alias_main: paddle.slice
:alias: paddle.slice,paddle.tensor.slice,paddle.tensor.manipulation.slice
:old_api: paddle.fluid.layers.slice
This operator produces a slice of ``input`` along multiple axes. Similar to numpy:
https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html
Slice uses ``axes``, ``starts`` and ``ends`` attributes to specify the start and
......@@ -10882,43 +10878,42 @@ def slice(input, axes, starts, ends):
ends = [-1, 1000] # -1 denotes the reverse 0th position of dimension 0.
Then:
result = [ [2, 3, 4], ] # result = data[0:1, 1:4]
Args:
input (Variable): A ``Tensor`` or ``LoDTensor`` . The data type is ``float16``, ``float32``, ``float64``, ``int32`` or ``int64``.
input (Tensor): A ``Tensor`` . The data type is ``float16``, ``float32``, ``float64``, ``int32`` or ``int64``.
axes (list|tuple): The data type is ``int32`` . Axes that `starts` and `ends` apply to .
starts (list|tuple|Variable): The data type is ``int32`` . If ``starts`` is a list or tuple, the elements of
it should be integers or Tensors with shape [1]. If ``starts`` is an Variable, it should be an 1-D Tensor.
starts (list|tuple|Tensor): The data type is ``int32`` . If ``starts`` is a list or tuple, the elements of
it should be integers or Tensors with shape [1]. If ``starts`` is an Tensor, it should be an 1-D Tensor.
It represents starting indices of corresponding axis in ``axes``.
ends (list|tuple|Variable): The data type is ``int32`` . If ``ends`` is a list or tuple, the elements of
it should be integers or Tensors with shape [1]. If ``ends`` is an Variable, it should be an 1-D Tensor .
ends (list|tuple|Tensor): The data type is ``int32`` . If ``ends`` is a list or tuple, the elements of
it should be integers or Tensors with shape [1]. If ``ends`` is an Tensor, it should be an 1-D Tensor .
It represents ending indices of corresponding axis in ``axes``.
Returns:
Variable: A ``Tensor`` or ``LoDTensor``. The data type is same as ``input``.
Tensor: A ``Tensor``. The data type is same as ``input``.
Raises:
TypeError: The type of ``starts`` must be list, tuple or Variable.
TypeError: The type of ``ends`` must be list, tuple or Variable.
TypeError: The type of ``starts`` must be list, tuple or Tensor.
TypeError: The type of ``ends`` must be list, tuple or Tensor.
Examples:
.. code-block:: python
import paddle.fluid as fluid
input = fluid.data(
name="input", shape=[4, 5, 6], dtype='float32')
import paddle
input = paddle.rand(shape=[4, 5, 6], dtype='float32')
# example 1:
# attr starts is a list which doesn't contain tensor Variable.
# attr starts is a list which doesn't contain tensor.
axes = [0, 1, 2]
starts = [-3, 0, 2]
ends = [3, 2, 4]
sliced_1 = fluid.layers.slice(input, axes=axes, starts=starts, ends=ends)
sliced_1 = paddle.slice(input, axes=axes, starts=starts, ends=ends)
# sliced_1 is input[0:3, 0:2, 2:4].
# example 2:
# attr starts is a list which contain tensor Variable.
minus_3 = fluid.layers.fill_constant([1], "int32", -3)
sliced_2 = fluid.layers.slice(input, axes=axes, starts=[minus_3, 0, 2], ends=ends)
# attr starts is a list which contain tensor.
minus_3 = paddle.full([1], -3, "int32")
sliced_2 = paddle.slice(input, axes=axes, starts=[minus_3, 0, 2], ends=ends)
# sliced_2 is input[0:3, 0:2, 2:4].
"""
if in_dygraph_mode():
......
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