max_pool¶
dragon.vm.tensorflow.nn.
max_pool
(
input,
ksize,
strides,
padding='VALID',
data_format='NHWC',
name=None
)[source]¶Apply the n-dimension max pooling.
- If
data_format
is'NCHW'
, excepts input shape \((N, C, D1, D2, ...)\), and output shape is \((N, C, D1_{\text{out}}, D2_{\text{out}}, ...)\). - If
data_format
is'NHWC'
, excepts input shape \((N, D1, D2, ..., C)\), and output shape is \((N, D1_{\text{out}}, D2_{\text{out}}, ..., C)\). padding
could be'VALID'
,'SAME'
or explicit padding size.
Examples:
for i in range(3): ndim = i + 1 x = tf.ones((1,) + (2,) * ndim + (2,)) y = tf.nn.max_pool(x, ksize=(2,) * ndim, strides=2) assert y.shape == (1,) + (1,) * ndim + (2,)
- Parameters:
- input (dragon.Tensor) – The input tensor.
- ksize (Union[int, Sequence[int]]) – The size of pooling window.
- strides (Union[int, Sequence[int]]) – The stride of pooling window.
- padding (Union[int, Sequence[int], str], optional, default='VALID') – The padding algorithm or size.
- data_format (str, optional, default='NHWC') –
'NCHW'
or'NHWC'
. - name (str, optional) – The operation name.
- Returns:
dragon.Tensor – The output tensor.
- If