tensorflow::
ops::
QuantizeAndDequantizeV4::
Attrs
#include <array_ops.h>
Optional attribute setters for QuantizeAndDequantizeV4 .
Summary
Public attributes |
|
---|---|
axis_
= -1
|
int64
|
narrow_range_
= false
|
bool
|
num_bits_
= 8
|
int64
|
range_given_
= false
|
bool
|
round_mode_
= "HALF_TO_EVEN"
|
StringPiece
|
signed_input_
= true
|
bool
|
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.
|
Public attributes
axis_
int64 tensorflow::ops::QuantizeAndDequantizeV4::Attrs::axis_ = -1
narrow_range_
bool tensorflow::ops::QuantizeAndDequantizeV4::Attrs::narrow_range_ = false
num_bits_
int64 tensorflow::ops::QuantizeAndDequantizeV4::Attrs::num_bits_ = 8
range_given_
bool tensorflow::ops::QuantizeAndDequantizeV4::Attrs::range_given_ = false
round_mode_
StringPiece tensorflow::ops::QuantizeAndDequantizeV4::Attrs::round_mode_ = "HALF_TO_EVEN"
signed_input_
bool tensorflow::ops::QuantizeAndDequantizeV4::Attrs::signed_input_ = true
Public functions
Axis
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::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
NarrowRange
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::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
NumBits
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::Attrs::NumBits( int64 x )
The bitwidth of the quantization.
Defaults to 8
RangeGiven
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::Attrs::RangeGiven( bool x )
Whether the range is given or should be determined from the
input
tensor.
Defaults to false
RoundMode
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::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"
SignedInput
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV4::Attrs::SignedInput( bool x )
Whether the quantization is signed or unsigned.
(actually this parameter should have been called
signed_output
)
Defaults to true