tensorflow:: ops:: QuantizeAndDequantizeV2:: Attrs
  #include <array_ops.h>
  Optional attribute setters for QuantizeAndDequantizeV2.
Summary
        Public attributes | 
    |
|---|---|
        narrow_range_ = false
       | 
      
        bool
         | 
    
        num_bits_ = 8
       | 
      
        int64
         | 
    
        range_given_ = false
       | 
      
        bool
         | 
    
        round_mode_ = "HALF_TO_EVEN"
       | 
      
        StringPiece
         | 
    
        signed_input_ = true
       | 
      
        bool
         | 
    
        Public functions | 
    |
|---|---|
        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
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
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