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 | |
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`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 | |
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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 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/QuantizedAvgPool