tensorflow::ops::QuantizeAndDequantizeV2::Attrs
#include <array_ops.h>
Optional attribute setters for QuantizeAndDequantizeV2.
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::QuantizeAndDequantizeV2::Attrs::axis_ = -1
narrow_range_
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::narrow_range_ = false
num_bits_
int64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::num_bits_ = 8
range_given_
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::range_given_ = false
round_mode_
StringPiece tensorflow::ops::QuantizeAndDequantizeV2::Attrs::round_mode_ = "HALF_TO_EVEN"
signed_input_
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::signed_input_ = true
Public functions
Axis
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
NarrowRange
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
NumBits
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NumBits( int64 x )
The bitwidth of the quantization.
Defaults to 8
RangeGiven
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
RoundMode
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"
SignedInput
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
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs