tf.raw_ops.QuantizedAvgPool
Produces the average pool of the input tensor for quantized types.
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. |
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/QuantizedAvgPool