tf.quantize_and_dequantize_v4

Quantizes then dequantizes a tensor.

tf.quantize_and_dequantize_v4(
    input, input_min, input_max, signed_input=True, num_bits=8, range_given=False,
    round_mode='HALF_TO_EVEN', narrow_range=False, axis=-1, name=None
)

This is almost identical to QuantizeAndDequantizeV2, except that it returns a gradient of 1 for inputs that are within the quantization range, or 0 otherwise.

input A Tensor. Must be one of the following types: bfloat16, half, float32, float64. Tensor to quantize and then dequantize.
input_min A Tensor. Must have the same type as input. If range_given == True, this specifies the minimum input value that needs to be represented, otherwise it is determined from the min value of the input tensor.
input_max A Tensor. Must have the same type as input. If range_given == True, this specifies the maximum input value that needs to be represented, otherwise it is determined from the max value of the input tensor.
signed_input An optional bool. Defaults to True. Whether the quantization is signed or unsigned. (actually this parameter should have been called signed_output)
num_bits An optional int. Defaults to 8. The bitwidth of the quantization.
range_given An optional bool. Defaults to False. Whether the range is given or should be determined from the input tensor.
round_mode An optional string from: "HALF_TO_EVEN", "HALF_UP". Defaults to "HALF_TO_EVEN". The 'round_mode' attribute controls which rounding tie-breaking algorithm is used when rounding float values to their quantized equivalents. The following rounding modes are currently supported:

  • HALF_TO_EVEN: this is the default round_mode.
  • HALF_UP: round towards positive. In this mode 7.5 rounds up to 8 and -7.5 rounds up to -7.
narrow_range An optional bool. Defaults to False. 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 An optional int. Defaults to -1. If specified, this axis is treated as a channel or slice axis, and a separate quantization range is used for each channel or slice along this axis.
name A name for the operation (optional).

A Tensor. Has the same type as input.