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. 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.
</td>
</tr><tr>
<td> data_format</td>
<td>
An optional string from: "NWC", "NCW". Defaults to "NWC".
</td>
</tr><tr>
<td> name`
|
A name for the operation (optional).
|
Returns |
A Tensor of format specified by data_format .
The max pooled output tensor.
|