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# tf.raw_ops.Requantize

Converts the quantized `input` tensor into a lower-precision `output`.

Converts the quantized `input` tensor into a lower-precision `output`, using the output range specified with `requested_output_min` and `requested_output_max`.

`[input_min, input_max]` are scalar floats that specify the range for the float interpretation of the `input` data. For example, if `input_min` is -1.0f and `input_max` is 1.0f, and we are dealing with `quint16` quantized data, then a 0 value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f.

`input` A `Tensor`. Must be one of the following types: `qint8`, `quint8`, `qint32`, `qint16`, `quint16`.
`input_min` A `Tensor` of type `float32`. The float value that the minimum quantized input value represents.
`input_max` A `Tensor` of type `float32`. The float value that the maximum quantized input value represents.
`requested_output_min` A `Tensor` of type `float32`. The float value that the minimum quantized output value represents.
`requested_output_max` A `Tensor` of type `float32`. The float value that the maximum quantized output value represents.
`out_type` A `tf.DType` from: `tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16`. The type of the output. Should be a lower bit depth than Tinput.
`name` A name for the operation (optional).

A tuple of `Tensor` objects (output, output_min, output_max).
`output` A `Tensor` of type `out_type`.
`output_min` A `Tensor` of type `float32`.
`output_max` A `Tensor` of type `float32`.

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