Performs the max pooling on the input.
tf.nn.max_pool1d(
input, ksize, strides, padding, data_format='NWC', name=None
)
Note internally this op reshapes and uses the underlying 2d operation.
Args |
input
|
A 3-D Tensor of the format specified by data_format .
|
ksize
|
An int or list of ints that has length 1 or 3 . The size of the
window for each dimension of the input tensor.
|
strides
|
An int or list of ints that has length 1 or 3 . The stride of
the sliding window for each dimension of the input tensor.
|
padding
|
Either the string "SAME" or "VALID" indicating the type of
padding algorithm to use, or a list indicating the explicit paddings at
the start and end of each dimension. See
here
for more information. When explicit padding is used and data_format is
"NWC" , this should be in the form [[0, 0], [pad_left, pad_right], [0,
0]] . When explicit padding used and data_format is "NCW" , this should
be in the form [[0, 0], [0, 0], [pad_left, pad_right]] . When using
explicit padding, the size of the paddings cannot be greater than the
sliding window size.
|
data_format
|
An optional string from: "NWC", "NCW". Defaults to "NWC".
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor of format specified by data_format .
The max pooled output tensor.
|