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tf.raw_ops.QuantizedAvgPool Stay organized with collections Save and categorize content based on your preferences.

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

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.QuantizedAvgPool

tf.raw_ops.QuantizedAvgPool(
    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.

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Last updated 2024-04-26 UTC.

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