Produces the average pool of the input tensor for quantized types.
tf.compat.v1.nn.quantized_avg_pool(
input, min_input, max_input, ksize, strides, padding, name=None
)
input: A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16.
4-D with shape [batch, height, width, channels].min_input: A Tensor of type float32.
The float value that the lowest quantized input value represents.max_input: A Tensor of type float32.
The float value that the highest quantized input value represents.ksize: A list of ints.
The size of the window for each dimension of the input tensor.
The length must be 4 to match the number of dimensions of the input.strides: A list of ints.
The stride of the sliding window for each dimension of the input
tensor. The length must be 4 to match the number of dimensions of the input.padding: A string from: "SAME", "VALID".
The type of padding algorithm to use.name: A name for the operation (optional).A tuple of Tensor objects (output, min_output, max_output).
output: A Tensor. Has the same type as input.min_output: A Tensor of type float32.max_output: A Tensor of type float32.