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