tf.nn.avg_pool

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Performs the avg pooling on the input.

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.