tensorflow:: ops:: QuantizedConv2D

#include <nn_ops.h>

Computes a 2D convolution given quantized 4D input and filter tensors.

Summary

The inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.

Args:

  • scope: A Scope object
  • filter: filter's input_depth dimension must match input's depth dimensions.
  • min_input: The float value that the lowest quantized input value represents.
  • max_input: The float value that the highest quantized input value represents.
  • min_filter: The float value that the lowest quantized filter value represents.
  • max_filter: The float value that the highest quantized filter value represents.
  • strides: The stride of the sliding window for each dimension of the input tensor.
  • padding: The type of padding algorithm to use.

Optional attributes (see Attrs ):

  • dilations: 1-D tensor of length 4. The dilation factor for each dimension of input . If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format , see above for details. Dilations in the batch and depth dimensions must be 1.

Returns:

  • Output output
  • Output min_output: The float value that the lowest quantized output value represents.
  • Output max_output: The float value that the highest quantized output value represents.

Constructors and Destructors

QuantizedConv2D (const :: tensorflow::Scope & scope, :: tensorflow::Input input, :: tensorflow::Input filter, :: tensorflow::Input min_input, :: tensorflow::Input max_input, :: tensorflow::Input min_filter, :: tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding)
QuantizedConv2D (const :: tensorflow::Scope & scope, :: tensorflow::Input input, :: tensorflow::Input filter, :: tensorflow::Input min_input, :: tensorflow::Input max_input, :: tensorflow::Input min_filter, :: tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding, const QuantizedConv2D::Attrs & attrs)

Public attributes

max_output
min_output
operation
output

Public static functions

Dilations (const gtl::ArraySlice< int > & x)
OutType (DataType x)

Structs

tensorflow:: ops:: QuantizedConv2D:: Attrs

Optional attribute setters for QuantizedConv2D .

Public attributes

max_output 

::tensorflow::Output max_output

min_output 

::tensorflow::Output min_output

operation 

Operation operation

output 

::tensorflow::Output output

Public functions

QuantizedConv2D 

 QuantizedConv2D(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input filter,
  ::tensorflow::Input min_input,
  ::tensorflow::Input max_input,
  ::tensorflow::Input min_filter,
  ::tensorflow::Input max_filter,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding
)

QuantizedConv2D 

 QuantizedConv2D(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input filter,
  ::tensorflow::Input min_input,
  ::tensorflow::Input max_input,
  ::tensorflow::Input min_filter,
  ::tensorflow::Input max_filter,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding,
  const QuantizedConv2D::Attrs & attrs
)

Public static functions

Dilations 

Attrs Dilations(
  const gtl::ArraySlice< int > & x
)

OutType 

Attrs OutType(
  DataType x
)