未验证 提交 4b41edd6 编写于 作者: W Wei Shengyu 提交者: GitHub

fix doc of max_pool_2d (#45604)

* fix doc of max_pool_2d

* dbg

* fix format
上级 3879f6b8
......@@ -1047,6 +1047,7 @@ def max_pool2d(x,
"""
This API implements max pooling 2d operation.
See more details in :ref:`api_nn_pooling_MaxPool2d` .
Args:
x (Tensor): The input tensor of pooling operator which is a 4-D tensor with
shape [N, C, H, W]. The format of input tensor is `"NCHW"` or
......@@ -1084,24 +1085,19 @@ def max_pool2d(x,
Examples:
.. code-block:: python
import paddle
import paddle.nn.functional as F
import numpy as np
# max pool2d
x = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32, 32]).astype(np.float32))
out = F.max_pool2d(x,
kernel_size=2,
stride=2, padding=0)
x = paddle.uniform([1, 3, 32, 32], paddle.float32)
out = F.max_pool2d(x, kernel_size=2, stride=2, padding=0)
# output.shape [1, 3, 16, 16]
# for return_mask=True
out, max_indices = F.max_pool2d(x,
kernel_size=2,
stride=2,
padding=0,
return_mask=True)
out, max_indices = F.max_pool2d(x, kernel_size=2, stride=2, padding=0, return_mask=True)
# out.shape [1, 3, 16, 16], max_indices.shape [1, 3, 16, 16],
"""
kernel_size = utils.convert_to_list(kernel_size, 2, 'pool_size')
if stride is None:
stride = kernel_size
......@@ -1193,6 +1189,7 @@ def max_pool3d(x,
"""
This API implements max pooling 2d operation.
See more details in :ref:`api_nn_pooling_MaxPool3d` .
Args:
x (Tensor): The input tensor of pooling operator, which is a 5-D tensor with
shape [N, C, D, H, W]. The format of input tensor is `"NCDHW"` or `"NDHWC"`, where N represents batch size, C represents the number of channels, D, H and W represent the depth, height and width of the feature respectively.
......@@ -1242,12 +1239,14 @@ def max_pool3d(x,
# for return_mask=True
x = paddle.uniform([1, 3, 32, 32, 32])
output, max_indices = paddle.nn.functional.max_pool3d(x,
kernel_size = 2,
stride = 2,
kernel_size=2,
stride=2,
padding=0,
return_mask=True)
# output.shape [1, 3, 16, 16, 16], max_indices.shape [1, 3, 16, 16, 16]
"""
kernel_size = utils.convert_to_list(kernel_size, 3, 'pool_size')
if stride is None:
stride = kernel_size
......
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