提交 510601b2 编写于 作者: J JiabinYang

test=develop

上级 982e4892
......@@ -2139,12 +2139,16 @@ def pool2d(input,
input tensor is NCHW, where N is batch size, C is
the number of channels, H is the height of the
feature, and W is the width of the feature.
pool_size (int|list|tuple): The pool kernel size. If pool kernel size is a tuple,
pool_size (int|list|tuple): The pool kernel size. If pool kernel size is a tuple or list,
it must contain two integers, (pool_size_Height, pool_size_Width).
Otherwise, the pool kernel size will be a square of an int.
pool_type: ${pooling_type_comment}
pool_stride (int): stride of the pooling layer.
pool_padding (int): padding size.
pool_stride (int|list|tuple): The pool stride size. If pool stride size is a tuple or list,
it must contain two integers, (pool_stride_Height, pool_stride_Width).
Otherwise, the pool stride size will be a square of an int.
pool_padding (int|list|tuple): The pool padding size. If pool padding size is a tuple,
it must contain two integers, (pool_padding_on_Height, pool_padding_on_Width).
Otherwise, the pool padding size will be a square of an int.
global_pooling (bool): ${global_pooling_comment}
use_cudnn (bool): ${use_cudnn_comment}
ceil_mode (bool): ${ceil_mode_comment}
......
......@@ -206,7 +206,12 @@ class TestBook(unittest.TestCase):
program = Program()
with program_guard(program):
x = layers.data(name='x', shape=[3, 224, 224], dtype='float32')
self.assertIsNotNone(layers.pool2d(x, pool_size=[5, 3]))
self.assertIsNotNone(
layers.pool2d(
x,
pool_size=[5, 3],
pool_stride=[1, 2],
pool_padding=(2, 1)))
def test_lstm_unit(self):
program = Program()
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册