tf.quantization.quantize

TensorFlow 1 version

View source on GitHub

Quantizes then dequantizes a tensor. (deprecated)

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.quantization.quantize_and_dequantize

tf.quantization.quantize_and_dequantize(
    input, input_min, input_max, signed_input=True, num_bits=8, range_given=False,
    round_mode='HALF_TO_EVEN', name=None, narrow_range=False, axis=None
)

Args
`input`	A `Tensor` to quantize and dequantize.
`input_min`	If range_given=True, the minimum input value, that needs to be represented in the quantized representation. If axis is specified, this should be a vector of minimum values for each slice along axis.
`input_max`	If range_given=True, the maximum input value that needs to be represented in the quantized representation. If axis is specified, this should be a vector of maximum values for each slice along axis.
`signed_input`	True if the quantization is signed or unsigned.
`num_bits`	The bitwidth of the quantization.
`range_given`	If true use `input_min` and `input_max` for the range of the input, otherwise determine min and max from the input `Tensor`.
`round_mode`	Rounding mode when rounding from float values to quantized ones. one of ['HALF_TO_EVEN', 'HALF_UP']
`name`	Optional name for the operation.
`narrow_range`	If true, then the absolute value of the quantized minimum value is the same as the quantized maximum value, instead of 1 greater. i.e. for 8 bit quantization, the minimum value is -127 instead of -128.
`axis`	Integer. If specified, refers to a dimension of the input tensor, such that quantization will be per slice along that dimension.

Returns
A `Tensor`. Each element is the result of quantizing and dequantizing the corresponding element of `input`.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.quantization / quantize

View aliases

Args

Returns