tf.nn.avg_pool

Performs the avg pooling on the input.

Compat aliases for migration

See Migration guide for more details.

tf.nn.avg_pool(
    input, ksize, strides, padding, data_format=None, name=None
)

Each entry in output is the mean of the corresponding size ksize window in value.

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`	A string, either `'VALID'` or `'SAME'`. The padding algorithm. See the "returns" section of `tf.nn.convolution` for details.
`data_format`	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".
`name`	Optional name for the operation.

Returns
A `Tensor` of format specified by `data_format`. The average pooled output tensor.

Args