Performs the max pooling on the input.
tf.nn.max_pool2d(
input, ksize, strides, padding, data_format='NHWC', name=None
)
Args |
input
|
A 4-D Tensor of the format specified by data_format .
|
ksize
|
An int or list of ints that has length 1 , 2 or 4 . The size of
the window for each dimension of the input tensor.
|
strides
|
An int or list of ints that has length 1 , 2 or 4 . 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
"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.
|
data_format
|
A string. 'NHWC', 'NCHW' and 'NCHW_VECT_C' are supported.
|
name
|
Optional name for the operation.
|
Returns |
A Tensor of format specified by data_format .
The max pooled output tensor.
|