tf.raw_ops.QuantizedAvgPool

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

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tf.compat.v1.raw_ops.QuantizedAvgPool

tf.raw_ops.QuantizedAvgPool(
    input, min_input, max_input, ksize, strides, padding, name=None
)

Args
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).

Returns
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.