tf.compat.v1.nn.quantized_avg_pool

Produces the average pool of the input tensor for quantized types.

tf.compat.v1.nn.quantized_avg_pool(
    input: _atypes.TensorFuzzingAnnotation[TV_QuantizedAvgPool_T],
    min_input: _atypes.TensorFuzzingAnnotation[_atypes.Float32],
    max_input: _atypes.TensorFuzzingAnnotation[_atypes.Float32],
    ksize,
    strides,
    padding: str,
    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.