tensorflow:: ops:: QuantizeAndDequantizeV2:: Attrs


   #include <array_ops.h>

Optional attribute setters for QuantizeAndDequantizeV2 .

Summary

Public functions
`Axis (int64 x)`	`TF_MUST_USE_RESULT Attrs` 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.
`NarrowRange (bool x)`	`TF_MUST_USE_RESULT Attrs` If True, then the absolute value of the quantized minimum value is the same as the quantized maximum value, instead of 1 greater.
`NumBits (int64 x)`	`TF_MUST_USE_RESULT Attrs` The bitwidth of the quantization.
`RangeGiven (bool x)`	`TF_MUST_USE_RESULT Attrs` Whether the range is given or should be determined from the `input` tensor.
`RoundMode (StringPiece x)`	`TF_MUST_USE_RESULT Attrs` The 'round_mode' attribute controls which rounding tie-breaking algorithm is used when rounding float values to their quantized equivalents.
`SignedInput (bool x)`	`TF_MUST_USE_RESULT Attrs` Whether the quantization is signed or unsigned.

int64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::axis_ = -1

bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::narrow_range_ = false

int64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::num_bits_ = 8

bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::range_given_ = false

StringPiece tensorflow::ops::QuantizeAndDequantizeV2::Attrs::round_mode_ = "HALF_TO_EVEN"

bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::signed_input_ = true

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::Axis(
  int64 x
)

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.

Defaults to -1

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NarrowRange(
  bool x
)

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.

Defaults to false

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NumBits(
  int64 x
)

The bitwidth of the quantization.

Defaults to 8

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RangeGiven(
  bool x
)

Whether the range is given or should be determined from the input tensor.

Defaults to false

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RoundMode(
  StringPiece x
)

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.

Defaults to "HALF_TO_EVEN"

TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::SignedInput(
  bool x
)

Whether the quantization is signed or unsigned.

(actually this parameter should have been called signed_output )

Defaults to true