Performs the max pooling on the input.
tf.nn.max_pool(
input, ksize, strides, padding, data_format=None, name=None
)
Args |
|---|
input
|
Tensor of rank N+2, of shape [batch_size] + input_spatial_shape +
[num_channels] if data_format does not start with "NC" (default), or
[batch_size, num_channels] + input_spatial_shape if data_format starts
with "NC". Pooling happens over the spatial dimensions only.
|
ksize
|
An int or list of ints that has length 1, N or N+2. The size
of the window for each dimension of the input tensor.
|
strides
|
An int or list of ints that has length 1, N or N+2. 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"NHWC", this should be in the form[[0, 0], [pad_top,
pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used
and data_format is"NCHW", this should be in the form[[0, 0], [0, 0],
[pad_top, pad_bottom], [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>
A string. Specifies the channel dimension. For N=1 it can be
either "NWC" (default) or "NCW", for N=2 it can be either "NHWC" (default)
or "NCHW" and for N=3 either "NDHWC" (default) or "NCDHW".
</td>
</tr><tr>
<td>name`
|
Optional name for the operation.
|
Returns |
|---|
A Tensor of format specified by data_format.
The max pooled output tensor.
|
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TensorFlow 1 version
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